market risk management thesis

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• Published: 03 September 2022

A literature review of risk, regulation, and profitability of banks using a scientometric study

• Shailesh Rastogi 1 ,
• Arpita Sharma 1 ,
• Geetanjali Pinto 2 &
• Venkata Mrudula Bhimavarapu   ORCID: orcid.org/0000-0002-9757-1904 1 , 3  

Future Business Journal volume  8 , Article number:  28 ( 2022 ) Cite this article

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This study presents a systematic literature review of regulation, profitability, and risk in the banking industry and explores the relationship between them. It proposes a policy initiative using a model that offers guidelines to establish the right mix among these variables. This is a systematic literature review study. Firstly, the necessary data are extracted using the relevant keywords from the Scopus database. The initial search results are then narrowed down, and the refined results are stored in a file. This file is finally used for data analysis. Data analysis is done using scientometrics tools, such as Table2net and Sciences cape software, and Gephi to conduct network, citation analysis, and page rank analysis. Additionally, content analysis of the relevant literature is done to construct a theoretical framework. The study identifies the prominent authors, keywords, and journals that researchers can use to understand the publication pattern in banking and the link between bank regulation, performance, and risk. It also finds that concentration banking, market power, large banks, and less competition significantly affect banks’ financial stability, profitability, and risk. Ownership structure and its impact on the performance of banks need to be investigated but have been inadequately explored in this study. This is an organized literature review exploring the relationship between regulation and bank performance. The limitations of the regulations and the importance of concentration banking are part of the findings.

Introduction

Globally, banks are under extreme pressure to enhance their performance and risk management. The financial industry still recalls the ignoble 2008 World Financial Crisis (WFC) as the worst economic disaster after the Great Depression of 1929. The regulatory mechanism before 2008 (mainly Basel II) was strongly criticized for its failure to address banks’ risks [ 47 , 87 ]. Thus, it is essential to investigate the regulation of banks [ 75 ]. This study systematically reviews the relevant literature on banks’ performance and risk management and proposes a probable solution.

Issues of performance and risk management of banks

Banks have always been hailed as engines of economic growth and have been the axis of the development of financial systems [ 70 , 85 ]. A vital parameter of a bank’s financial health is the volume of its non-performing assets (NPAs) on its balance sheet. NPAs are advances that delay in payment of interest or principal beyond a few quarters [ 108 , 118 ]. According to Ghosh [ 51 ], NPAs negatively affect the liquidity and profitability of banks, thus affecting credit growth and leading to financial instability in the economy. Hence, healthy banks translate into a healthy economy.

Despite regulations, such as high capital buffers and liquidity ratio requirements, during the second decade of the twenty-first century, the Indian banking sector still witnessed a substantial increase in NPAs. A recent report by the Indian central bank indicates that the gross NPA ratio reached an all-time peak of 11% in March 2018 and 12.2% in March 2019 [ 49 ]. Basel II has been criticized for several reasons [ 98 ]. Schwerter [ 116 ] and Pakravan [ 98 ] highlighted the systemic risk and gaps in Basel II, which could not address the systemic risk of WFC 2008. Basel III was designed to close the gaps in Basel II. However, Schwerter [ 116 ] criticized Basel III and suggested that more focus should have been on active risk management practices to avoid any impending financial crisis. Basel III was proposed to solve these issues, but it could not [ 3 , 116 ]. Samitas and Polyzos [ 113 ] found that Basel III had made banking challenging since it had reduced liquidity and failed to shield the contagion effect. Therefore, exploring some solutions to establish the right balance between regulation, performance, and risk management of banks is vital.

Keeley [ 67 ] introduced the idea of a balance among banks’ profitability, regulation, and NPA (risk-taking). This study presents the balancing act of profitability, regulation, and NPA (risk-taking) of banks as a probable solution to the issues of bank performance and risk management and calls it a triad . Figure  1 illustrates the concept of a triad. Several authors have discussed the triad in parts [ 32 , 96 , 110 , 112 ]. Triad was empirically tested in different countries by Agoraki et al. [ 1 ]. Though the idea of a triad is quite old, it is relevant in the current scenario. The spirit of the triad strongly and collectively admonishes the Basel Accord and exhibits new and exhaustive measures to take up and solve the issue of performance and risk management in banks [ 16 , 98 ]. The 2008 WFC may have caused an imbalance among profitability, regulation, and risk-taking of banks [ 57 ]. Less regulation , more competition (less profitability ), and incentive to take the risk were the cornerstones of the 2008 WFC [ 56 ]. Achieving a balance among the three elements of a triad is a real challenge for banks’ performance and risk management, which this study addresses.

Triad of Profitability, regulation, and NPA (risk-taking). Note The triad [ 131 ] of profitability, regulation, and NPA (risk-taking) is shown in Fig.  1

Triki et al. [ 130 ] revealed that a bank’s performance is a trade-off between the elements of the triad. Reduction in competition increases the profitability of banks. However, in the long run, reduction in competition leads to either the success or failure of banks. Flexible but well-expressed regulation and less competition add value to a bank’s performance. The current review paper is an attempt to explore the literature on this triad of bank performance, regulation, and risk management. This paper has the following objectives:

To systematically explore the existing literature on the triad: performance, regulation, and risk management of banks; and

To propose a model for effective bank performance and risk management of banks.

Literature is replete with discussion across the world on the triad. However, there is a lack of acceptance of the triad as a solution to the woes of bank performance and risk management. Therefore, the findings of the current papers significantly contribute to this regard. This paper collates all the previous studies on the triad systematically and presents a curated view to facilitate the policy makers and stakeholders to make more informed decisions on the issue of bank performance and risk management. This paper also contributes significantly by proposing a DBS (differential banking system) model to solve the problem of banks (Fig.  7 ). This paper examines studies worldwide and therefore ensures the wider applicability of its findings. Applicability of the DBS model is not only limited to one nation but can also be implemented worldwide. To the best of the authors’ knowledge, this is the first study to systematically evaluate the publication pattern in banking using a blend of scientometrics analysis tools, network analysis tools, and content analysis to understand the link between bank regulation, performance, and risk.

This paper is divided into five sections. “ Data and research methods ” section discusses the research methodology used for the study. The data analysis for this study is presented in two parts. “ Bibliometric and network analysis ” section presents the results obtained using bibliometric and network analysis tools, followed by “ Content Analysis ” section, which presents the content analysis of the selected literature. “ Discussion of the findings ” section discusses the results and explains the study’s conclusion, followed by limitations and scope for further research.

Data and research methods

A literature review is a systematic, reproducible, and explicit way of identifying, evaluating, and synthesizing relevant research produced and published by researchers [ 50 , 100 ]. Analyzing existing literature helps researchers generate new themes and ideas to justify the contribution made to literature. The knowledge obtained through evidence-based research also improves decision-making leading to better practical implementation in the real corporate world [ 100 , 129 ].

As Kumar et al. [ 77 , 78 ] and Rowley and Slack [ 111 ] recommended conducting an SLR, this study also employs a three-step approach to understand the publication pattern in the banking area and establish a link between bank performance, regulation, and risk.

Determining the appropriate keywords for exploring the data

Many databases such as Google Scholar, Web of Science, and Scopus are available to extract the relevant data. The quality of a publication is associated with listing a journal in a database. Scopus is a quality database as it has a wider coverage of data [ 100 , 137 ]. Hence, this study uses the Scopus database to extract the relevant data.

For conducting an SLR, there is a need to determine the most appropriate keywords to be used in the database search engine [ 26 ]. Since this study seeks to explore a link between regulation, performance, and risk management of banks, the keywords used were “risk,” “regulation,” “profitability,” “bank,” and “banking.”

Initial search results and limiting criteria

Using the keywords identified in step 1, the search for relevant literature was conducted in December 2020 in the Scopus database. This resulted in the search of 4525 documents from inception till December 2020. Further, we limited our search to include “article” publications only and included subject areas: “Economics, Econometrics and Finance,” “Business, Management and Accounting,” and “Social sciences” only. This resulted in a final search result of 3457 articles. These results were stored in a.csv file which is then used as an input to conduct the SLR.

Data analysis tools and techniques

This study uses bibliometric and network analysis tools to understand the publication pattern in the area of research [ 13 , 48 , 100 , 122 , 129 , 134 ]. Some sub-analyses of network analysis are keyword word, author, citation, and page rank analysis. Author analysis explains the author’s contribution to literature or research collaboration, national and international [ 59 , 99 ]. Citation analysis focuses on many researchers’ most cited research articles [ 100 , 102 , 131 ].

The.csv file consists of all bibliometric data for 3457 articles. Gephi and other scientometrics tools, such as Table2net and ScienceScape software, were used for the network analysis. This.csv file is directly used as an input for this software to obtain network diagrams for better data visualization [ 77 ]. To ensure the study’s quality, the articles with 50 or more citations (216 in number) are selected for content analysis [ 53 , 102 ]. The contents of these 216 articles are analyzed to develop a conceptual model of banks’ triad of risk, regulation, and profitability. Figure  2 explains the data retrieval process for SLR.

Data retrieval process for SLR. Note Stepwise SLR process and corresponding results obtained

Bibliometric and network analysis

Figure  3 [ 58 ] depicts the total number of studies that have been published on “risk,” “regulation,” “profitability,” “bank,” and “banking.” Figure  3 also depicts the pattern of the quality of the publications from the beginning till 2020. It undoubtedly shows an increasing trend in the number of articles published in the area of the triad: “risk” regulation” and “profitability.” Moreover, out of the 3457 articles published in the said area, 2098 were published recently in the last five years and contribute to 61% of total publications in this area.

Articles published from 1976 till 2020 . Note The graph shows the number of documents published from 1976 till 2020 obtained from the Scopus database

Source of publications

A total of 160 journals have contributed to the publication of 3457 articles extracted from Scopus on the triad of risk, regulation, and profitability. Table 1 shows the top 10 sources of the publications based on the citation measure. Table 1 considers two sets of data. One data set is the universe of 3457 articles, and another is the set of 216 articles used for content analysis along with their corresponding citations. The global citations are considered for the study from the Scopus dataset, and the local citations are considered for the articles in the nodes [ 53 , 135 ]. The top 10 journals with 50 or more citations resulted in 96 articles. This is almost 45% of the literature used for content analysis ( n  = 216). Table 1 also shows that the Journal of Banking and Finance is the most prominent in terms of the number of publications and citations. It has 46 articles published, which is about 21% of the literature used for content analysis. Table 1 also shows these core journals’ SCImago Journal Rank indicator and H index. SCImago Journal Rank indicator reflects the impact and prestige of the Journal. This indicator is calculated as the previous three years’ weighted average of the number of citations in the Journal since the year that the article was published. The h index is the number of articles (h) published in a journal and received at least h. The number explains the scientific impact and the scientific productivity of the Journal. Table 1 also explains the time span of the journals covering articles in the area of the triad of risk, regulation, and profitability [ 7 ].

Figure  4 depicts the network analysis, where the connections between the authors and source title (journals) are made. The network has 674 nodes and 911 edges. The network between the author and Journal is classified into 36 modularities. Sections of the graph with dense connections indicate high modularity. A modularity algorithm is a design that measures how strong the divided networks are grouped into modules; this means how well the nodes are connected through a denser route relative to other networks.

Network analysis between authors and journals. Note A node size explains the more linked authors to a journal

The size of the nodes is based on the rank of the degree. The degree explains the number of connections or edges linked to a node. In the current graph, a node represents the name of the Journal and authors; they are connected through the edges. Therefore, the more the authors are associated with the Journal, the higher the degree. The algorithm used for the layout is Yifan Hu’s.

Many authors are associated with the Journal of Banking and Finance, Journal of Accounting and Economics, Journal of Financial Economics, Journal of Financial Services Research, and Journal of Business Ethics. Therefore, they are the most relevant journals on banks’ risk, regulation, and profitability.

Location and affiliation analysis

Affiliation analysis helps to identify the top contributing countries and universities. Figure  5 shows the countries across the globe where articles have been published in the triad. The size of the circle in the map indicates the number of articles published in that country. Table 2 provides the details of the top contributing organizations.

Location of articles published on Triad of profitability, regulation, and risk

Figure  5 shows that the most significant number of articles is published in the USA, followed by the UK. Malaysia and China have also contributed many articles in this area. Table 2 shows that the top contributing universities are also from Malaysia, the UK, and the USA.

Key author analysis

Table 3 shows the number of articles written by the authors out of the 3457 articles. The table also shows the top 10 authors of bank risk, regulation, and profitability.

Fadzlan Sufian, affiliated with the Universiti Islam Malaysia, has the maximum number, with 33 articles. Philip Molyneux and M. Kabir Hassan are from the University of Sharjah and the University of New Orleans, respectively; they contributed significantly, with 20 and 18 articles, respectively.

However, when the quality of the article is selected based on 50 or more citations, Fadzlan Sufian has only 3 articles with more than 50 citations. At the same time, Philip Molyneux and Allen Berger contributed more quality articles, with 8 and 11 articles, respectively.

Keyword analysis

Table 4 shows the keyword analysis (times they appeared in the articles). The top 10 keywords are listed in Table 4 . Banking and banks appeared 324 and 194 times, respectively, which forms the scope of this study, covering articles from the beginning till 2020. The keyword analysis helps to determine the factors affecting banks, such as profitability (244), efficiency (129), performance (107, corporate governance (153), risk (90), and regulation (89).

The keywords also show that efficiency through data envelopment analysis is a determinant of the performance of banks. The other significant determinants that appeared as keywords are credit risk (73), competition (70), financial stability (69), ownership structure (57), capital (56), corporate social responsibility (56), liquidity (46), diversification (45), sustainability (44), credit provision (41), economic growth (41), capital structure (39), microfinance (39), Basel III (37), non-performing assets (37), cost efficiency (30), lending behavior (30), interest rate (29), mergers and acquisition (28), capital adequacy (26), developing countries (23), net interest margin (23), board of directors (21), disclosure (21), leverage (21), productivity (20), innovation (18), firm size (16), and firm value (16).

Keyword analysis also shows the theories of banking and their determinants. Some of the theories are agency theory (23), information asymmetry (21), moral hazard (17), and market efficiency (16), which can be used by researchers when building a theory. The analysis also helps to determine the methodology that was used in the published articles; some of them are data envelopment analysis (89), which measures technical efficiency, panel data analysis (61), DEA (32), Z scores (27), regression analysis (23), stochastic frontier analysis (20), event study (15), and literature review (15). The count for literature review is only 15, which confirms that very few studies have conducted an SLR on bank risk, regulation, and profitability.

Citation analysis

One of the parameters used in judging the quality of the article is its “citation.” Table 5 shows the top 10 published articles with the highest number of citations. Ding and Cronin [ 44 ] indicated that the popularity of an article depends on the number of times it has been cited.

Tahamtan et al. [ 126 ] explained that the journal’s quality also affects its published articles’ citations. A quality journal will have a high impact factor and, therefore, more citations. The citation analysis helps researchers to identify seminal articles. The title of an article with 5900 citations is “A survey of corporate governance.”

Page Rank analysis

Goyal and Kumar [ 53 ] explain that the citation analysis indicates the ‘popularity’ and ‘prestige’ of the published research article. Apart from the citation analysis, one more analysis is essential: Page rank analysis. PageRank is given by Page et al. [ 97 ]. The impact of an article can be measured with one indicator called PageRank [ 135 ]. Page rank analysis indicates how many times an article is cited by other highly cited articles. The method helps analyze the web pages, which get the priority during any search done on google. The analysis helps in understanding the citation networks. Equation  1 explains the page rank (PR) of a published paper, N refers to the number of articles.

T 1,… T n indicates the paper, which refers paper P . C ( Ti ) indicates the number of citations. The damping factor is denoted by a “ d ” which varies in the range of 0 and 1. The page rank of all the papers is equal to 1. Table 6 shows the top papers based on page rank. Tables 5 and 6 together show a contrast in the top ranked articles based on citations and page rank, respectively. Only one article “A survey of corporate governance” falls under the prestigious articles based on the page rank.

Content analysis

Content Analysis is a research technique for conducting qualitative and quantitative analyses [ 124 ]. The content analysis is a helpful technique that provides the required information in classifying the articles depending on their nature (empirical or conceptual) [ 76 ]. By adopting the content analysis method [ 53 , 102 ], the selected articles are examined to determine their content. The classification of available content from the selected set of sample articles that are categorized under different subheads. The themes identified in the relationship between banking regulation, risk, and profitability are as follows.

Regulation and profitability of banks

The performance indicators of the banking industry have always been a topic of interest to researchers and practitioners. This area of research has assumed a special interest after the 2008 WFC [ 25 , 51 , 86 , 114 , 127 , 132 ]. According to research, the causes of poor performance and risk management are lousy banking practices, ineffective monitoring, inadequate supervision, and weak regulatory mechanisms [ 94 ]. Increased competition, deregulation, and complex financial instruments have made banks, including Indian banks, more vulnerable to risks [ 18 , 93 , 119 , 123 ]. Hence, it is essential to investigate the present regulatory machinery for the performance of banks.

There are two schools of thought on regulation and its possible impact on profitability. The first asserts that regulation does not affect profitability. The second asserts that regulation adds significant value to banks’ profitability and other performance indicators. This supports the concept that Delis et al. [ 41 ] advocated that the capital adequacy requirement and supervisory power do not affect productivity or profitability unless there is a financial crisis. Laeven and Majnoni [ 81 ] insisted that provision for loan loss should be part of capital requirements. This will significantly improve active risk management practices and ensure banks’ profitability.

Lee and Hsieh [ 83 ] proposed ambiguous findings that do not support either school of thought. According to Nguyen and Nghiem [ 95 ], while regulation is beneficial, it has a negative impact on bank profitability. As a result, when proposing regulations, it is critical to consider bank performance and risk management. According to Erfani and Vasigh [ 46 ], Islamic banks maintained their efficiency between 2006 and 2013, while most commercial banks lost, furthermore claimed that the financial crisis had no significant impact on Islamic bank profitability.

Regulation and NPA (risk-taking of banks)

The regulatory mechanism of banks in any country must address the following issues: capital adequacy ratio, prudent provisioning, concentration banking, the ownership structure of banks, market discipline, regulatory devices, presence of foreign capital, bank competition, official supervisory power, independence of supervisory bodies, private monitoring, and NPAs [ 25 ].

Kanoujiya et al. [ 64 ] revealed through empirical evidence that Indian bank regulations lack a proper understanding of what banks require and propose reforming and transforming regulation in Indian banks so that responsive governance and regulation can occur to make banks safer, supported by Rastogi et al. [ 105 ]. The positive impact of regulation on NPAs is widely discussed in the literature. [ 94 ] argue that regulation has multiple effects on banks, including reducing NPAs. The influence is more powerful if the country’s banking system is fragile. Regulation, particularly capital regulation, is extremely effective in reducing risk-taking in banks [ 103 ].

Rastogi and Kanoujiya [ 106 ] discovered evidence that disclosure regulations do not affect the profitability of Indian banks, supported by Karyani et al. [ 65 ] for the banks located in Asia. Furthermore, Rastogi and Kanoujiya [ 106 ] explain that disclosure is a difficult task as a regulatory requirement. It is less sustainable due to the nature of the imposed regulations in banks and may thus be perceived as a burden and may be overcome by realizing the benefits associated with disclosure regulation [ 31 , 54 , 101 ]. Zheng et al. [ 138 ] empirically discovered that regulation has no impact on the banks’ profitability in Bangladesh.

Governments enforce banking regulations to achieve a stable and efficient financial system [ 20 , 94 ]. The existing literature is inconclusive on the effects of regulatory compliance on banks’ risks or the reduction of NPAs [ 10 , 11 ]. Boudriga et al. [ 25 ] concluded that the regulatory mechanism plays an insignificant role in reducing NPAs. This is especially true in weak institutions, which are susceptible to corruption. Gonzalez [ 52 ] reported that firm regulations have a positive relationship with banks’ risk-taking, increasing the probability of NPAs. However, Boudriga et al. [ 25 ], Samitas and Polyzos [ 113 ], and Allen et al. [ 3 ] strongly oppose the use of regulation as a tool to reduce banks’ risk-taking.

Kwan and Laderman [ 79 ] proposed three levels in regulating banks, which are lax, liberal, and strict. The liberal regulatory framework leads to more diversification in banks. By contrast, the strict regulatory framework forces the banks to take inappropriate risks to compensate for the loss of business; this is a global problem [ 73 ].

Capital regulation reduces banks’ risk-taking [ 103 , 110 ]. Capital regulation leads to cost escalation, but the benefits outweigh the cost [ 103 ]. The trade-off is worth striking. Altman Z score is used to predict banks’ bankruptcy, and it found that the regulation increased the Altman’s Z-score [ 4 , 46 , 63 , 68 , 72 , 120 ]. Jin et al. [ 62 ] report a negative relationship between regulation and banks’ risk-taking. Capital requirements empowered regulators, and competition significantly reduced banks’ risk-taking [ 1 , 122 ]. Capital regulation has a limited impact on banks’ risk-taking [ 90 , 103 ].

Maji and De [ 90 ] suggested that human capital is more effective in managing banks’ credit risks. Besanko and Kanatas [ 21 ] highlighted that regulation on capital requirements might not mitigate risks in all scenarios, especially when recapitalization has been enforced. Klomp and De Haan [ 72 ] proposed that capital requirements and supervision substantially reduce banks’ risks.

A third-party audit may impart more legitimacy to the banking system [ 23 ]. The absence of third-party intervention is conspicuous, and this may raise a doubt about the reliability and effectiveness of the impact of regulation on bank’s risk-taking.

NPA (risk-taking) in banks and profitability

Profitability affects NPAs, and NPAs, in turn, affect profitability. According to the bad management hypothesis [ 17 ], higher profits would negatively affect NPAs. By contrast, higher profits may lead management to resort to a liberal credit policy (high earnings), which may eventually lead to higher NPAs [ 104 ].

Balasubramaniam [ 8 ] demonstrated that NPA has double negative effects on banks. NPAs increase stressed assets, reducing banks’ productive assets [ 92 , 117 , 136 ]. This phenomenon is relatively underexplored and therefore renders itself for future research.

Triad and the performance of banks

Regulation and triad.

Regulations and their impact on banks have been a matter of debate for a long time. Barth et al. [ 12 ] demonstrated that countries with a central bank as the sole regulatory body are prone to high NPAs. Although countries with multiple regulatory bodies have high liquidity risks, they have low capital requirements [ 40 ]. Barth et al. [ 12 ] supported the following steps to rationalize the existing regulatory mechanism on banks: (1) mandatory information [ 22 ], (2) empowered management of banks, and (3) increased incentive for private agents to exert corporate control. They show that profitability has an inverse relationship with banks’ risk-taking [ 114 ]. Therefore, standard regulatory practices, such as capital requirements, are not beneficial. However, small domestic banks benefit from capital restrictions.

DeYoung and Jang [ 43 ] showed that Basel III-based policies of liquidity convergence ratio (LCR) and net stable funding ratio (NSFR) are not fully executed across the globe, including the US. Dahir et al. [ 39 ] found that a decrease in liquidity and funding increases banks’ risk-taking, making banks vulnerable and reducing stability. Therefore, any regulation on liquidity risk is more likely to create problems for banks.

Concentration banking and triad

Kiran and Jones [ 71 ] asserted that large banks are marginally affected by NPAs, whereas small banks are significantly affected by high NPAs. They added a new dimension to NPAs and their impact on profitability: concentration banking or banks’ market power. Market power leads to less cost and more profitability, which can easily counter the adverse impact of NPAs on profitability [ 6 , 15 ].

The connection between the huge volume of research on the performance of banks and competition is the underlying concept of market power. Competition reduces market power, whereas concentration banking increases market power [ 25 ]. Concentration banking reduces competition, increases market power, rationalizes the banks’ risk-taking, and ensures profitability.

Tabak et al. [ 125 ] advocated that market power incentivizes banks to become risk-averse, leading to lower costs and high profits. They explained that an increase in market power reduces the risk-taking requirement of banks. Reducing banks’ risks due to market power significantly increases when capital regulation is executed objectively. Ariss [ 6 ] suggested that increased market power decreases competition, and thus, NPAs reduce, leading to increased banks’ stability.

Competition, the performance of banks, and triad

Boyd and De Nicolo [ 27 ] supported that competition and concentration banking are inversely related, whereas competition increases risk, and concentration banking decreases risk. A mere shift toward concentration banking can lead to risk rationalization. This finding has significant policy implications. Risk reduction can also be achieved through stringent regulations. Bolt and Tieman [ 24 ] explained that stringent regulation coupled with intense competition does more harm than good, especially concerning banks’ risk-taking.

Market deregulation, as well as intensifying competition, would reduce the market power of large banks. Thus, the entire banking system might take inappropriate and irrational risks [ 112 ]. Maji and Hazarika [ 91 ] added more confusion to the existing policy by proposing that, often, there is no relationship between capital regulation and banks’ risk-taking. However, some cases have reported a positive relationship. This implies that banks’ risk-taking is neutral to regulation or leads to increased risk. Furthermore, Maji and Hazarika [ 91 ] revealed that competition reduces banks’ risk-taking, contrary to popular belief.

Claessens and Laeven [ 36 ] posited that concentration banking influences competition. However, this competition exists only within the restricted circle of banks, which are part of concentration banking. Kasman and Kasman [ 66 ] found that low concentration banking increases banks’ stability. However, they were silent on the impact of low concentration banking on banks’ risk-taking. Baselga-Pascual et al. [ 14 ] endorsed the earlier findings that concentration banking reduces banks’ risk-taking.

Concentration banking and competition are inversely related because of the inherent design of concentration banking. Market power increases when only a few large banks are operating; thus, reduced competition is an obvious outcome. Barra and Zotti [ 9 ] supported the idea that market power, coupled with competition between the given players, injects financial stability into banks. Market power and concentration banking affect each other. Therefore, concentration banking with a moderate level of regulation, instead of indiscriminate regulation, would serve the purpose better. Baselga-Pascual et al. [ 14 ] also showed that concentration banking addresses banks’ risk-taking.

Schaeck et al. [ 115 ], in a landmark study, presented that concentration banking and competition reduce banks’ risk-taking. However, they did not address the relationship between concentration banking and competition, which are usually inversely related. This could be a subject for future research. Research on the relationship between concentration banking and competition is scant, identified as a research gap (“ Research Implications of the study ” section).

Transparency, corporate governance, and triad

One of the big problems with NPAs is the lack of transparency in both the regulatory bodies and banks [ 25 ]. Boudriga et al. [ 25 ] preferred to view NPAs as a governance issue and thus, recommended viewing it from a governance perspective. Ahmad and Ariff [ 2 ] concluded that regulatory capital and top-management quality determine banks’ credit risk. Furthermore, they asserted that credit risk in emerging economies is higher than that of developed economies.

Bad management practices and moral vulnerabilities are the key determinants of insolvency risks of Indian banks [ 95 ]. Banks are an integral part of the economy and engines of social growth. Therefore, banks enjoy liberal insolvency protection in India, especially public sector banks, which is a critical issue. Such a benevolent insolvency cover encourages a bank to be indifferent to its capital requirements. This indifference takes its toll on insolvency risk and profit efficiency. Insolvency protection makes the bank operationally inefficient and complacent.

Foreign equity and corporate governance practices help manage the adverse impact of banks’ risk-taking to ensure the profitability and stability of banks [ 33 , 34 ]. Eastburn and Sharland [ 45 ] advocated that sound management and a risk management system that can anticipate any impending risk are essential. A pragmatic risk mechanism should replace the existing conceptual risk management system.

Lo [ 87 ] found and advocated that the existing legislation and regulations are outdated. He insisted on a new perspective and asserted that giving equal importance to behavioral aspects and the rational expectations of customers of banks is vital. Buston [ 29 ] critiqued the balance sheet risk management practices prevailing globally. He proposed active risk management practices that provided risk protection measures to contain banks’ liquidity and solvency risks.

Klomp and De Haan [ 72 ] championed the cause of giving more autonomy to central banks of countries to provide stability in the banking system. Louzis et al. [ 88 ] showed that macroeconomic variables and the quality of bank management determine banks’ level of NPAs. Regulatory authorities are striving hard to make regulatory frameworks more structured and stringent. However, the recent increase in loan defaults (NPAs), scams, frauds, and cyber-attacks raise concerns about the effectiveness [ 19 ] of the existing banking regulations in India as well as globally.

Discussion of the findings

The findings of this study are based on the bibliometric and content analysis of the sample published articles.

The bibliometric study concludes that there is a growing demand for researchers and good quality research

The keyword analysis suggests that risk regulation, competition, profitability, and performance are key elements in understanding the banking system. The main authors, keywords, and journals are grouped in a Sankey diagram in Fig.  6 . Researchers can use the following information to understand the publication pattern on banking and its determinants.

Sankey Diagram of main authors, keywords, and journals. Note Authors contribution using scientometrics tools

Research Implications of the study

The study also concludes that a balance among the three components of triad is the solution to the challenges of banks worldwide, including India. We propose the following recommendations and implications for banks:

This study found that “the lesser the better,” that is, less regulation enhances the performance and risk management of banks. However, less regulation does not imply the absence of regulation. Less regulation means the following:

Flexible but full enforcement of the regulations

Customization, instead of a one-size-fits-all regulatory system rooted in a nation’s indigenous requirements, is needed. Basel or generic regulation can never achieve what a customized compliance system can.

A third-party audit, which is above the country's central bank, should be mandatory, and this would ensure that all three aspects of audit (policy formulation, execution, and audit) are handled by different entities.

Competition

This study asserts that the existing literature is replete with poor performance and risk management due to excessive competition. Banking is an industry of a different genre, and it would be unfair to compare it with the fast-moving consumer goods (FMCG) or telecommunication industry, where competition injects efficiency into the system, leading to customer empowerment and satisfaction. By contrast, competition is a deterrent to the basic tenets of safe banking. Concentration banking is more effective in handling the multi-pronged balance between the elements of the triad. Concentration banking reduces competition to lower and manageable levels, reduces banks’ risk-taking, and enhances profitability.

No incentive to take risks

It is found that unless banks’ risk-taking is discouraged, the problem of high NPA (risk-taking) cannot be addressed. Concentration banking is a disincentive to risk-taking and can be a game-changer in handling banks’ performance and risk management.

Research on the risk and performance of banks reveals that the existing regulatory and policy arrangement is not a sustainable proposition, especially for a country where half of the people are unbanked [ 37 ]. Further, the triad presented by Keeley [ 67 ] is a formidable real challenge to bankers. The balance among profitability, risk-taking, and regulation is very subtle and becomes harder to strike, just as the banks globally have tried hard to achieve it. A pragmatic intervention is needed; hence, this study proposes a change in the banking structure by having two types of banks functioning simultaneously to solve the problems of risk and performance of banks. The proposed two-tier banking system explained in Fig.  7 can be a great solution. This arrangement will help achieve the much-needed balance among the elements of triad as presented by Keeley [ 67 ].

Conceptual Framework. Note Fig.  7 describes the conceptual framework of the study

The first set of banks could be conventional in terms of their structure and should primarily be large-sized. The number of such banks should be moderate. There is a logic in having only a few such banks to restrict competition; thus, reasonable market power could be assigned to them [ 55 ]. However, a reduction in competition cannot be over-assumed, and banks cannot become complacent. As customary, lending would be the main source of revenue and income for these banks (fund based activities) [ 82 ]. The proposed two-tier system can be successful only when regulation especially for risk is objectively executed [ 29 ]. The second set of banks could be smaller in size and more in number. Since they are more in number, they would encounter intense competition for survival and for generating more business. Small is beautiful, and thus, this set of banks would be more agile and adaptable and consequently more efficient and profitable. The main source of revenue for this set of banks would not be loans and advances. However, non-funding and non-interest-bearing activities would be the major revenue source. Unlike their traditional and large-sized counterparts, since these banks are smaller in size, they are less likely to face risk-taking and NPAs [ 74 ].

Sarmiento and Galán [ 114 ] presented the concerns of large and small banks and their relative ability and appetite for risk-taking. High risk could threaten the existence of small-sized banks; thus, they need robust risk shielding. Small size makes them prone to failure, and they cannot convert their risk into profitability. However, large banks benefit from their size and are thus less vulnerable and can convert risk into profitable opportunities.

India has experimented with this Differential Banking System (DBS) (two-tier system) only at the policy planning level. The execution is impending, and it highly depends on the political will, which does not appear to be strong now. The current agenda behind the DBS model is not to ensure the long-term sustainability of banks. However, it is currently being directed to support the agenda of financial inclusion by extending the formal credit system to the unbanked masses [ 107 ]. A shift in goal is needed to employ the DBS as a strategic decision, but not merely a tool for financial inclusion. Thus, the proposed two-tier banking system (DBS) can solve the issue of profitability through proper regulation and less risk-taking.

The findings of Triki et al. [ 130 ] support the proposed DBS model, in this study. Triki et al. [ 130 ] advocated that different component of regulations affect banks based on their size, risk-taking, and concentration banking (or market power). Large size, more concentration banking with high market power, and high risk-taking coupled with stringent regulation make the most efficient banks in African countries. Sharifi et al. [ 119 ] confirmed that size advantage offers better risk management to large banks than small banks. The banks should modify and work according to the economic environment in the country [ 69 ], and therefore, the proposed model could help in solving the current economic problems.

This is a fact that DBS is running across the world, including in India [ 60 ] and other countries [ 133 ]. India experimented with DBS in the form of not only regional rural banks (RRBs) but payments banks [ 109 ] and small finance banks as well [ 61 ]. However, the purpose of all the existing DBS models, whether RRBs [ 60 ], payment banks, or small finance banks, is financial inclusion, not bank performance and risk management. Hence, they are unable to sustain and are failing because their model is only social instead of a much-needed dual business-cum-social model. The two-tier model of DBS proposed in the current paper can help serve the dual purpose. It may not only be able to ensure bank performance and risk management but also serve the purpose of inclusive growth of the economy.

Conclusion of the study

The study’s conclusions have some significant ramifications. This study can assist researchers in determining their study plan on the current topic by using a scientific approach. Citation analysis has aided in the objective identification of essential papers and scholars. More collaboration between authors from various countries/universities may help countries/universities better understand risk regulation, competition, profitability, and performance, which are critical elements in understanding the banking system. The regulatory mechanism in place prior to 2008 failed to address the risk associated with banks [ 47 , 87 ]. There arises a necessity and motivates authors to investigate the current topic. The present study systematically explores the existing literature on banks’ triad: performance, regulation, and risk management and proposes a probable solution.

To conclude the bibliometric results obtained from the current study, from the number of articles published from 1976 to 2020, it is evident that most of the articles were published from the year 2010, and the highest number of articles were published in the last five years, i.e., is from 2015. The authors discovered that researchers evaluate articles based on the scope of critical journals within the subject area based on the detailed review. Most risk, regulation, and profitability articles are published in peer-reviewed journals like; “Journal of Banking and Finance,” “Journal of Accounting and Economics,” and “Journal of Financial Economics.” The rest of the journals are presented in Table 1 . From the affiliation statistics, it is clear that most of the research conducted was affiliated with developed countries such as Malaysia, the USA, and the UK. The researchers perform content analysis and Citation analysis to access the type of content where the research on the current field of knowledge is focused, and citation analysis helps the academicians understand the highest cited articles that have more impact in the current research area.

Practical implications of the study

The current study is unique in that it is the first to systematically evaluate the publication pattern in banking using a combination of scientometrics analysis tools, network analysis tools, and content analysis to understand the relationship between bank regulation, performance, and risk. The study’s practical implications are that analyzing existing literature helps researchers generate new themes and ideas to justify their contribution to literature. Evidence-based research knowledge also improves decision-making, resulting in better practical implementation in the real corporate world [ 100 , 129 ].

Limitations and scope for future research

The current study only considers a single database Scopus to conduct the study, and this is one of the limitations of the study spanning around the multiple databases can provide diverse results. The proposed DBS model is a conceptual framework that requires empirical testing, which is a limitation of this study. As a result, empirical testing of the proposed DBS model could be a future research topic.

Availability of data and materials

SCOPUS database.

Abbreviations

Systematic literature review

World Financial Crisis

Non-performing assets

Differential banking system

SCImago Journal Rank Indicator

Liquidity convergence ratio

Net stable funding ratio

Fast moving consumer goods

Regional rural banks

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‘SR’ performed Abstract, Introduction, and Data methodology sections and was the major contributor; ‘AS’ performed Bibliometric and Network analysis and conceptual framework; ‘GP’ performed citation analysis and discussion section; ‘VMB’ collated data from the database and concluded the article. All authors read and approved the final manuscript.

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50 Best Finance Dissertation Topics For Research Students

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Finance Dissertation Made Easier!

Embarking on your dissertation adventure? Look no further! Choosing the right finance dissertation topics is like laying the foundation for your research journey in Finance, and we're here to light up your path. In this blog, we're diving deep into why dissertation topics in finance matter so much. We've got some golden writing tips to share with you! We're also unveiling the secret recipe for structuring a stellar finance dissertation and exploring intriguing topics across various finance sub-fields. Whether you're captivated by cryptocurrency, risk management strategies, or exploring the wonders of Internet banking, microfinance, retail and commercial banking - our buffet of Finance dissertation topics will surely set your research spirit on fire!

What is a Finance Dissertation?

Finance dissertations are academic papers that delve into specific finance topics chosen by students, covering areas such as stock markets, banking, risk management, and healthcare finance. These dissertations require extensive research to create a compelling report and contribute to the student's confidence and satisfaction in the field of Finance. Now, let's understand why these dissertations are so important and why choosing the right Finance dissertation topics is crucial!

Why Are Finance Dissertation Topics Important?

Choosing the dissertation topics for Finance students is essential as it will influence the course of your research. It determines the direction and scope of your study. You must make sure that the Finance dissertation topics you choose are relevant to your field of interest, or you may end up finding it more challenging to write. Here are a few reasons why finance thesis topics are important:

1. Relevance

Opting for relevant finance thesis topics ensures that your research contributes to the existing body of knowledge and addresses contemporary issues in the field of Finance. Choosing a dissertation topic in Finance that is relevant to the industry can make a meaningful impact and advance understanding in your chosen area.

2. Personal Interest

Selecting Finance dissertation topics that align with your interests and career goals is vital. When genuinely passionate about your research area, you are more likely to stay motivated during the dissertation process. Your interest will drive you to explore the subject thoroughly and produce high-quality work.

3. Future Opportunities

Well-chosen Finance dissertation topics can open doors to various future opportunities. It can enhance your employability by showcasing your expertise in a specific finance area. It may lead to potential research collaborations and invitations to conferences in your field of interest.

4. Academic Supervision

Your choice of topics for dissertation in Finance also influences the availability of academic supervisors with expertise in your chosen area. Selecting a well-defined research area increases the likelihood of finding a supervisor to guide you effectively throughout the dissertation. Their knowledge and guidance will greatly contribute to the success of your research.

Writing Tips for Finance Dissertation

A lot of planning, formatting, and structuring goes into writing a dissertation. It starts with deciding on topics for a dissertation in Finance and conducting tons of research, deciding on methods, and so on. However, you can navigate the process more effectively with proper planning and organisation. Below are some tips to assist you along the way, and here is a blog on the 10 tips on writing a dissertation that can give you more information, should you need it!

1. Select a Manageable Topic

Choosing Finance research topics within the given timeframe and resources is important. Select a research area that interests you and aligns with your career goals. It will help you stay inspired throughout the dissertation process.

2. Conduct a Thorough Literature Review

A comprehensive literature review forms the backbone of your research. After choosing the Finance dissertation topics, dive deep into academic papers, books, and industry reports, gaining a solid understanding of your chosen area to identify research gaps and establish the significance of your study.

3. Define Clear Research Objectives

Clearly define your dissertation's research questions and objectives. It will provide a clear direction for your research and guide your data collection, analysis, and overall structure. Ensure your objectives are specific, measurable, achievable, relevant, and time-bound (SMART).

4. Collect and Analyse Data

Depending on your research methodology and your Finance dissertation topics, collect and analyze relevant data to support your findings. It may involve conducting surveys, interviews, experiments, and analyzing existing datasets. Choose appropriate statistical techniques and qualitative methods to derive meaningful insights from your data.

5. Structure and Organization

Pay attention to the structure and organization of your dissertation. Follow a logical progression of chapters and sections, ensuring that each chapter contributes to the overall coherence of your study. Use headings, subheadings, and clear signposts to guide the reader through your work.

6. Proofread and Edit

Once you have completed the writing process, take the time to proofread and edit your dissertation carefully. Check for clarity, coherence, and proper grammar. Ensure that your arguments are well-supported, and eliminate any inconsistencies or repetitions. Pay attention to formatting, citation styles, and consistency in referencing throughout your dissertation.

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Finance Dissertation Topics

Now that you know what a finance dissertation is and why they are important, it's time to have a look at some of the best Finance dissertation topics. For your convenience, we have segregated these topics into categories, including cryptocurrency, risk management, internet banking, and so many more. So, let's dive right in and explore the best Finance dissertation topics:

Dissertation topics in Finance related to Cryptocurrency

1. The Impact of Regulatory Frameworks on the Volatility and Liquidity of Cryptocurrencies.

2. Exploring the Factors Influencing Cryptocurrency Adoption: A Comparative Study.

3. Assessing the Efficiency and Market Integration of Cryptocurrency Exchanges.

4. An Analysis of the Relationship between Cryptocurrency Prices and Macroeconomic Factors.

5. The Role of Initial Coin Offerings (ICOs) in Financing Startups: Opportunities and Challenges.

Dissertation topics in Finance related to Risk Management

1. The Effectiveness of Different Risk Management Strategies in Mitigating Financial Risks in Banking Institutions.

2. The Role of Derivatives in Hedging Financial Risks: A Comparative Study.

3. Analyzing the Impact of Risk Management Practices on Firm Performance: A Case Study of a Specific Industry.

4. The Use of Stress Testing in Evaluating Systemic Risk: Lessons from the Global Financial Crisis.

5. Assessing the Relationship between Corporate Governance and Risk Management in Financial Institutions.

Dissertation topics in Finance related to Internet Banking

1. Customer Adoption of Internet Banking: An Empirical Study on Factors Influencing Usage.

Enhancing Security in Internet Banking: Exploring Biometric Authentication Technologies.

2. The Impact of Mobile Banking Applications on Customer Engagement and Satisfaction.

3. Evaluating the Efficiency and Effectiveness of Internet Banking Services in Emerging Markets.

4. The Role of Social Media in Shaping Customer Perception and Adoption of Internet Banking.

Dissertation topics in Finance related to Microfinance

1. The Impact of Microfinance on Poverty Alleviation: A Comparative Study of Different Models.

2. Exploring the Role of Microfinance in Empowering Women Entrepreneurs.

3. Assessing the Financial Sustainability of Microfinance Institutions in Developing Countries.

4. The Effectiveness of Microfinance in Promoting Rural Development: Evidence from a Specific Region.

5. Analyzing the Relationship between Microfinance and Entrepreneurial Success: A Longitudinal Study.

Dissertation topics in Finance related to Retail and Commercial Banking

1. The Impact of Digital Transformation on Retail and Commercial Banking: A Case Study of a Specific Bank.

2. Customer Satisfaction and Loyalty in Retail Banking: An Analysis of Service Quality Dimensions.

3. Analyzing the Relationship between Bank Branch Expansion and Financial Performance.

4. The Role of Fintech Startups in Disrupting Retail and Commercial Banking: Opportunities and Challenges.

5. Assessing the Impact of Mergers and Acquisitions on the Performance of Retail and Commercial Banks.

Dissertation topics in Finance related to Alternative Investment

1. The Performance and Risk Characteristics of Hedge Funds: A Comparative Analysis.

2. Exploring the Role of Private Equity in Financing and Growing Small and Medium-Sized Enterprises.

3. Analyzing the Relationship between Real Estate Investments and Portfolio Diversification.

4. The Potential of Impact Investing: Evaluating the Social and Financial Returns.

5. Assessing the Risk-Return Tradeoff in Cryptocurrency Investments: A Comparative Study.

Dissertation topics in Finance related to International Affairs

1. The Impact of Exchange Rate Volatility on International Trade: A Case Study of a Specific Industry.

2. Analyzing the Effectiveness of Capital Controls in Managing Financial Crises: Comparative Study of Different Countries.

3. The Role of International Financial Institutions in Promoting Economic Development in Developing Countries.

4. Evaluating the Implications of Trade Wars on Global Financial Markets.

5. Assessing the Role of Central Banks in Managing Financial Stability in a Globalized Economy.

Dissertation topics in Finance related to Sustainable Finance

1. The impact of sustainable investing on financial performance.

2. The role of green bonds in financing climate change mitigation and adaptation.

3. The development of carbon markets.

4. The use of environmental, social, and governance (ESG) factors in investment decision-making.

5. The challenges and opportunities of sustainable Finance in emerging markets.

Dissertation topics in Finance related to Investment Banking

1. The valuation of distressed assets.

2. The pricing of derivatives.

3. The risk management of financial institutions.

4. The regulation of investment banks.

5. The impact of technology on the investment banking industry.

Dissertation topics in Finance related to Actuarial Science

1. The development of new actuarial models for pricing insurance products.

2. The use of big data in actuarial analysis.

3. The impact of climate change on insurance risk.

4. The design of pension plans that are sustainable in the long term.

5. The use of actuarial science to manage risk in other industries, such as healthcare and Finance.

Tips To Find Good Finance Dissertation Topics 

Embarking on a financial dissertation journey requires careful consideration of various factors. Your choice of topic in finance research topics is pivotal, as it sets the stage for the entire research process. Finding a good financial dissertation topic is essential to blend your interests with the current trends in the financial landscape. We suggest the following tips that can help you pick the perfect dissertation topic:

1. Identify your interests and strengths 

2. Check for current relevance

3. Feedback from your superiors

4. Finalise the research methods

5. Gather the data

6. Work on the outline of your dissertation

7. Make a draft and proofread it

In this blog, we have discussed the importance of finance thesis topics and provided valuable writing tips and tips for finding the right topic, too. We have also presented a list of topics within various subfields of Finance. With this, we hope you have great ideas for finance dissertations. Good luck with your finance research journey!

Frequently Asked Questions

How do i research for my dissertation project topics in finance, what is the best topic for dissertation topics for mba finance, what is the hardest finance topic, how do i choose the right topic for my dissertation in finance, where can i find a dissertation topic in finance.

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Financial risks: how stock market predictions lead to losses.

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Switch button positioned on the word minimum, black background and blue light. Conceptual image for ... [+] illustration of Risk management or assessment.

The pursuit of market predictions by investors becomes risky given the potential for a single tweet to cause a stock market avalanche. As they traverse an intricate network of economic information, psychological prejudices, and unanticipated worldwide occurrences, the consequences are frequently severe, and the stakes are impossibly high. Investors who acknowledge these challenges often use a range of strategies to mitigate risk, such as diversification, hedging, and continuous monitoring of market conditions and assumptions. The inherent uncertainty in markets means that even with sophisticated models and deep experience, predictions are often just educated guesses.

I am an individual company investor. I invest in the future outcomes of the company and rarely, if ever, do macro-economic conditions and numbers come into play in my analysis. I don’t invest in biotech, and I don’t invest in commodities.

Notable financial institutions like Morgan Stanley Morgan Stanley , J.P. Morgan, and BlackRock BlackRock have issued recent market forecasts for 2024 that reflect worries about valuation, economic growth, and possible geopolitical dangers. While J.P. Morgan projects little earnings growth and highlights the effect of recalcitrant inflation on interest rates, Morgan Stanley cautions against overvalued stocks and too-rosy corporate earnings projections. BlackRock recommends keeping a balanced and diversified investing approach even if it finds chances for active management in the face of market dispersion. These studies emphasize the difficulties in precisely forecasting market trends in a complicated and unpredictable international setting.

Complexity Of Market Dynamics

Knowing how many elements interact to drive market dynamics is essential for seasoned investors. Many things can have a big impact on market mood and results, including political events, economic indicators, and company activities. Fundamental economic indicators include employment numbers, GDP growth rates, and inflation figures. Usually, optimistic market data sparks possible rallies. If the same statistics raise worries about inflation and ensuing central bank interest rate increases, it can nevertheless cause market volatility.

Elections, policy changes, and geopolitical developments are all political events that play significant roles. The anticipation of regulatory changes, for instance, can cause market anxiety, even though it might also help the market rise. These incidents can have a big and instantaneous effect, which shows how sensitive markets are to political stability and government acts.

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Corporate actions can have an impact on the market at large as well as immediately affect the stock prices of the companies concerned. Examples of these decisions are earnings reports, mergers, and leadership changes. Sector revaluations may result from strategic business mergers, although poor performance by a top company can also lower the sector.

Unexpected actions in the market may result from the convergence of these elements. The cumulative effects of several dynamics are what markets react to, not to any one element acting alone. Complex market reactions might arise from this interaction when political instability, for instance, may obscure strong economic signals or vice versa.

Navigating the markets successfully requires an understanding of their intricacy. Understanding the relationships and effects between these factors facilitates the creation of a sophisticated investment plan that considers the inherent volatility of the markets as well as the predictable trends. Long-term investing success requires this comprehensive approach.

Information Overload

Investors are inundated with a ton of data in the digital era of today, from news stories, market reports, economic indicators, and social media feeds. Though it may appear helpful, having so much information can make decision-making more difficult and result in information overload. The main difficulty is being able to sort through this information and determine what is important for making wise financial choices. Information is not equal; certain data can significantly influence market changes, while others are just noise that may confuse or divert attention. Important economic announcements, such as changes in interest rates or unemployment statistics, can direct investment plans, for instance. Sensational news headlines, however, can elicit strong market responses right away but frequently have little lasting impact.

Investors need to have strong analytical abilities and instruments to sift through the deluge of information and concentrate on the important. The challenge lies in the variety and speed of the information, as well as its amount. Rapid updating of the information frequently results in contradictory interpretations that impair judgment.

Emotional And Psychological Factors

Experienced investors frequently control this overload with artificial intelligence, computerized trading algorithms, and sophisticated data analytics. By sifting through huge databases, these tools can help extract useful insights and spot less obvious underlying trends. Still, a big problem is the possibility of analysis paralysis, in which an excess of data prevents decision-making.

In the end, wise discernment of the caliber and applicability of the information is just as important for successful investing in the current climate. In the choppy world of finance, keeping a clear perspective requires striking a balance between being knowledgeable and overwhelmed.

Not only do market movements and numerical data form the world of investing, but the psychological composition of the investors themselves has a big impact. Especially confirmation bias and overconfidence, cognitive biases are important in influencing financial decisions and frequently result in worse than ideal results.

Confidence is too high when investors place unduly strong trust in their own instincts or analytical abilities, resulting in biased results. Investors who suffer from this prejudice overestimate the precision of their forecasts and underestimate the dangers. For example, an overly confident investor could disregard warning indicators of a downturn because they are so confident in their chosen approach or in their previous success, which they credit too much to their own abilities rather than to chance or market conditions.

Investors who have confirmation bias look for or value information that supports their preexisting ideas or theories more highly than information that might challenge them. This can create a risky loop whereby an investor sticks with a failing investment because of the biased information that backs up their original choice instead of reassessing their position and considering a more nuanced analysis of fresh information.

These prejudices cause erroneous thinking and, eventually, investment decisions that do not correspond with impartial evaluations of risk and reward, therefore compromising decision-making. Frequently, the outcome is a confirmation of false beliefs and a rise in investing mistakes, such hanging onto losing positions too long or placing unduly large wagers on speculative results.

Investors hoping to make reasonable, well-informed judgments must recognize and lessen the impact of these psychological biases. Methods for overcoming these prejudices include looking for different viewpoints, methodically analyzing contradicting data, and establishing preset guidelines for financial decisions.

External Factors And Their Unpredictability

Uncertainties arising from hard-to-forecast and model outside variables frequently surround investing. Few things may quickly and dramatically impact the investing environment, such as geopolitical tensions, natural disasters, and unforeseen regulatory changes.

Global financial markets can be volatile due to geopolitical tensions, including wars, trade conflicts, and political change and upheaval. Trade tariffs, for instance, have the potential to upset international supply networks and lower corporate profitability all around. Similar swings in commodity prices, such as oil, or the quick devaluation of currencies can result from political unrest.

Natural calamities provide other formidable obstacles. Because they wreck so much, earthquakes, hurricanes, and other calamities can cause insurance firms to lose a lot of money, severely disrupt supply networks, and lower consumer spending. These occurrences are extremely difficult to model in investment strategies because of their unpredictable timing and impact.

Including these unpredictably changing factors in prediction models is quite difficult. Shocks from without can upset the rational conduct and market efficiency that are common assumptions in traditional financial models. Since unusual and unprecedented events lack previous data, these models are useless for predicting these events. Usually, these models use historical data to forecast future trends.

It is also difficult to forecast market reactions because of the interdependence of global markets, which allows an incident in one region of the world to have repercussions elsewhere. A large commodity-exporting nation's political change, for example, can have an impact on commodity prices globally, which in turn affects businesses and economies everywhere.

Managing these difficulties calls for investors to keep some flexibility in their approaches and to keep an eye on a broad spectrum of possible risk variables. To reduce the risks connected to the unpredictable nature of external events, scenario planning, hedging techniques, and diversification are crucial instruments. These strategies protect investments from sudden market changes brought about by unforeseen circumstances through their preparation for potential outcomes.

Limitations Of Predictive Models

Predicting future market behaviors is sometimes quite difficult because of the dependence on prior data and the underlying assumptions of financial models. Although these models are necessary instruments for investors, several important elements can undermine their efficacy.

Financial models often use previous data and assumptions to project future results. This method makes the potentially seriously incorrect assumption that relationships and patterns from the past will persist into the future. A complex, dynamic array of factors affects market dynamics. When future conditions differ significantly from the past, depending just on historical tendencies can result in serious mistakes.

Market Structure Changes: The financial markets change with time; they are never static. Changes in consumer behavior, regulatory environments, or technological breakthroughs can all affect market structures. Because algorithmic trading has grown, for example, trade volumes and price movements have changed, which affects how predictable stock prices are based on past trends. In the same vein, new financial goods and instruments can bring about behaviors that were not taken into consideration in previous models.

Economic Fundamentals: Unexpected variations in interest rates, employment levels, or inflation rates can quickly make current models out of date. Models relying on data from stable economic conditions, for instance, could not be able to forecast market collapses or the actions of investors in panic during times of economic crisis.

Another crucial flaw is the dependence on the presumption that economic links stay the same across time. Variables like unemployment and stock market performance might have different relationships as the economy changes structurally or as new economic policies are implemented.

Investors and analysts must constantly test and update their models against current data to reduce these risks, and they must also be wary of the limitations of any model-based forecast. Stress-testing portfolios against unforeseen events and including a variety of scenarios can also help control the risks connected to depending too much on previous data. More accurate forecasts need models to be adjusted to reflect current market conditions rather than presuming historical continuity.

Seeking market forecasts in the ever-changing world of investment is like trying to navigate a maze that is always being renovated; new routes appear and disappear overnight. Macroeconomic changes, unanticipated geopolitical developments, and ingrained psychological prejudices that warp perception and decision-making processes are only a few of the interrelated causes of this complexity.

The difficulties abound. First, investors can experience information overload from the abundance of material available to them, which frequently obscures the important from the insignificant. Business activities, political events, and economic indicators all create a complex tapestry from which it takes keen analytical skills to separate the significant from the insignificant. Second, the unpredictability of outside factors—whether they be natural disasters or geopolitical tensions—adds levels of complexity to investment strategies and frequently makes conventional models useless. Built on past data, these models find it difficult to keep up with the quick changes in economic foundations and market structures.

According to recent evaluations by renowned companies like Morgan Stanley, J.P. Morgan, and BlackRock, relying solely on forecast models that ignore new, evolving economic realities is risky. These projections emphasize the few growth opportunities in the face of increased prices and emphasize the need for a well-rounded and diverse investment strategy.

It takes recognition of these complex issues together with strong risk management techniques to successfully negotiate this complex investment terrain. Not only strategic decisions but also necessary strategies to reduce possible losses include diversification, ongoing market condition monitoring, and hedging. Furthermore, the underlying risks of the market require investors to pledge to ongoing education and flexibility to make well-informed and current investing choices. This strategy strengthens the investor's ability to weather the shocks of unanticipated market volatility, in addition to increasing the possibility of obtaining long-term rewards.

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Climate risk and the opportunity for real estate

Climate change, previously a relatively peripheral concern for many real-estate players, has moved to the top of the agenda. Recently, investors  made net-zero commitments, regulators developed reporting standards, governments passed laws targeting emissions, employees demanded action, and tenants demanded more sustainable buildings. At the same time, the accelerating physical consequences of a changing climate are becoming more pronounced as communities face storms, floods, fires, extreme heat, and other risks.

These changes have brought a sense of urgency to the critical role of real-estate leaders in the climate transition, the period until 2050 during which the world will feel both the physical effects of climate change and the economic, social, and regulatory changes necessary to decarbonize. The climate transition not only creates new responsibilities for real-estate players to both revalue and future-proof their portfolios but also brings opportunities to create fresh sources of value.

The combination of this economic transition and the physical risks of climate change has created a significant risk of mispricing real estate across markets and asset classes. For example, a major North American bank conducted analysis that found dozens of assets in its real-estate portfolio that would likely be exposed to significant devaluations within the next ten years due to factors including increased rates of flooding and job losses due to the climate transition. Additionally, a study of a diversified equity portfolio found that, absent mitigating actions, climate risks could reduce annual returns toward the end of the decade by as much as 40 percent.

Leading real-estate players will figure out which of their assets are mispriced and in what direction and use this insight to inform their investment, asset management, and disposition choices. They will also decarbonize their assets, attracting the trillions of dollars of capital that has been committed to net zero and the thousands of tenants that have made similar commitments. They will then create new revenue sources related to the climate transition.

Building climate intelligence is central to value creation and strategic differentiation in the real-estate industry. But the reverse is also true: real estate is central to global climate change mitigation efforts. Real estate drives approximately 39 percent of total global emissions. Approximately 11 percent of these emissions are generated by manufacturing materials used in buildings (including steel and cement), while the rest is emitted from buildings themselves and by generating the energy that powers buildings. 1 2019 global status report for buildings and construction , International Energy Agency, December 2019.

In addition to the scale of its contribution to total emissions, real estate is critical in global decarbonization efforts for reasons likely to be compelling for investors, tenants, and governments. Significant reductions in emissions associated with real estate can be achieved with positive economics through technologies that already exist. For example, upgrading to more energy-efficient lighting systems and installing better insulation have positive financial returns. Today, newer technologies also make low-carbon heating and cooling systems, such as heat pumps and energy-efficient air conditioning, more cost competitive in many markets and climates. These cost-effective upgrades can create meaningful change while also derisking assets.

We suggest three actions real-estate players can take to thrive throughout the climate transition:

• Incorporate climate change risks into asset and portfolio valuations. This requires building the analytical capabilities to understand both direct and indirect physical and transition risks.
• Decarbonize real-estate assets and portfolios.
• Create new sources of value and revenue streams for investors, tenants, and communities.

Fundamental changes brought on by the climate transition will open new dimensions of competitive differentiation and value creation for real-estate players. More important, leaders will make a valuable contribution to the world’s ability to meet the global climate challenge.

Incorporate climate change risks into asset and portfolio valuations

Climate change’s physical and transition risks touch almost every aspect of a building’s operations and value. Physical risks are hazards caused by a changing climate, including both acute events, such as floods, fires, extreme heat, and storms, and chronic conditions, such as steadily rising sea levels and changing average temperatures. Transition risks include changes in the economy, regulation, consumer behavior, technology, and other human responses to climate change.

We do mind the gap

As we work with real-estate firms, we notice that investment teams increasingly recognize the impact of climate change on asset values. As one leader of valuations at a major real-estate-services firm recently commented to us: “This is the greatest deviation between modeled valuation and actual price that I’ve ever seen, and it’s because of climate.” A chief operating officer of a diversified real-estate investor told us, “We’ve seen underperformance of a cluster of our assets due to climate-related factors that just weren’t considered in our investment theses.”

The industry at large senses how values are shifting. A recent survey of finance experts and professionals conducted by researchers at New York University found that those who think real-estate asset prices reflect climate risks “not enough” outnumber those who think they reflect climate risks “too much” by 67 to 1 (in comparison with stock prices, in which the ratio was 20 to 1). 1 Johannes Stroebel and Jeffrey Wurgler, “What do you think about climate finance?,” Harvard Law School Forum on Corporate Governance, September 3, 2021. The International Renewable Energy Agency has estimated that $7.5 trillion worth of real estate could be “stranded”; these are assets that will experience major write-downs in value given climate risks and the economic transition, making real estate one of the hardest-hit sectors. 2 Jean Eaglesham and Vipal Monga, “Trillions in assets may be left stranded as companies address climate change,” Wall Street Journal , November 20, 2021.

Physical and transition risks can affect assets, such as buildings, directly or indirectly, by having an impact on the markets with which the assets interact. A carbon-intensive building obviously faces regulatory, tenancy, investor, and other risks; over the long term, so does a building that exists in a carbon-intensive ecosystem. For example, a building supplied by a carbon-intensive energy grid or a carbon-intensive transportation system is exposed to the transition risks of those systems as well. All these changes add up to substantial valuation impacts for even diversified portfolios—an increasingly pressing concern for real-estate companies (see sidebar, “We do mind the gap”).

Physical risks, both direct and indirect, have an uneven effect on asset performance

Several major real-estate companies have recently conducted climate stress tests on their portfolios and found a significant impact on portfolio value, with potential losses for some debt portfolios doubling over the next several years. Notably, they found significant variation within the portfolios. Some assets, because of their carbon footprint, location, or tenant composition, would benefit from changes brought on by the climate transition, while others would suffer significant drops in value. The challenge for players is to determine which assets will be affected, in what ways, and how to respond. There is also opportunity for investors who can identify mispriced assets.

Direct physical consequences can be conspicuous: the value of homes in Florida exposed to changing climate-related risks are depressed by roughly $5 billion relative to unexposed homes. According to the Journal of Urban Economics , after Hurricane Sandy, housing prices were reduced by up to 8 percent in New York’s flood zones by 2017, reflecting a greater perception of risk by potential buyers. 2 Francesc Ortega and Süleyman Taspinar, “Rising sea levels and sinking property values: Hurricane Sandy and New York’s housing market,” Journal of Urban Economics , July 2018, Volume 106. In California, there has been a 61 percent annual jump in nonrenewals of insurance (due to higher prices and refused coverage) in areas of moderate-to-very-high fire risk. 3 Elaine Chen and Katherine Chiglinsky, “Many Californians being left without homeowners insurance due to wildfire risk,” Insurance Journal , December 4, 2020.

The indirect impacts of physical risk on assets can be harder to perceive, causing some real-estate players to underestimate them. For example, in 2020, the McKinsey Global Institute modeled expected changes in flooding due to climate change in Bristol, England . A cluster of major corporate headquarters was not directly affected, but the transportation arteries to and from the area were. The water may never enter the lobby of the building, but neither will the tenants.

The climate transition will affect both individual buildings and entire real-estate markets

The investments required to avoid or derisk the worst physical risks will drive a historic reallocation of capital . This will change the structure of our economy and impact the value of the markets, companies, and companies’ locations. These momentous changes require real-estate players to look ahead for regulatory, economic, and social changes that could impact assets.

Among the most direct climate-transition impacts are regulatory requirements to decarbonize buildings, such as New York City’s Local Law 97. In June 2019, the Urban Green Council found that retrofitting all 50,000 buildings covered by the law would create retrofit demand of up to $24.3 billion through 2030. 4 Justin Gerdes, “After pandemic, New York’s buildings face daunting decarbonization mandate,” Greentech Media, April 23, 2020. Standard property valuation models generally do not account for the capital costs required for a building to decarbonize, and investors and operators are often left with a major capital expense or tax that wasn’t considered in the investment memo.

There is also a host of less direct but potentially more significant transition risks that affect whole markets. For example, some carbon-intensive industries are already experiencing rapid declines or fluctuations. In Calgary, for example, the combination of oil price volatility and market-access issues (driven by climate change–related opposition to pipelines) has dramatically depressed revenues from some buildings. Vacancy rates in downtown Calgary reached about 30 percent, a record high, as of January 2021. Investors exposed to the Calgary market have seen their asset values drop precipitously and are left trying to either hold on and hope for a reversal of fortunes or exit the assets and take a significant loss.

Real-estate players should build the capabilities to understand climate-related impacts on asset performance and values

Real-estate owners and investors will need to improve their climate intelligence to understand the potential impact of revenue, operating costs, capital costs, and capitalization rate on assets. This includes developing the analytical capabilities to consistently assess both physical and transition risks. Analyses should encompass both direct effects on assets and indirect effects on the markets, systems, and societies with which assets interact (Exhibit 1).

Portfolio and asset managers can map, quantify, and forecast climate change’s asset value impact

To understand climate change impact on asset values, landlords and investors can develop the following capabilities to understand and quantify risks and opportunities:

• Prioritize. Create a detailed assessment of the asset or portfolio to determine which physical and transition risks are most important and which are less important (using criteria such as the probability of a risk occurring or the severity of that risk).
• Map building exposures. Determine which buildings are exposed to risks, either directly (for example, having to pay a carbon tax on building emissions) or indirectly (for example, exposure to reduction in occupancy as tenants’ industries decline because of a carbon tax), and the degree of exposure (for example, how high floodwaters would reach). This could require detailed modeling of physical hazards (for example, projected changes in flood risks as the climate changes) or macro- or microeconomic modeling (for example, projected GDP impacts based on the carbon price impact on a local geography’s energy production mix).
• Quantify portfolio impact. Combine assessments of the economic risks on individual buildings into an impact map that enables visualization of the entire portfolio (Exhibit 2). This requires combining knowledge of the potential risk or opportunity and an understanding of what drives the economics of a building (including drivers of net operating income, tenancy mix, and areas of cost variability).
• Take action. These capabilities cannot be isolated in a research or environmental, social, and governance (ESG) function but should directly inform investment management, lease pricing, capital attraction and investor relations, asset management, tenant attraction, development, and other core businesses. The processes within organizations must shift to ensure that climate-related insights can be a source of real competitive advantage.

A portfolio revaluation informed by climate change risks can lead to hard choices but will also open the door to acting on decarbonization and exploring new opportunities.

Decarbonize buildings and portfolios

McKinsey research estimates approximately $9.2 trillion in annual investment will be required globally to support the net-zero transition . If the world successfully decarbonizes, the 2050 economy will look fundamentally different from the current economy. If it doesn’t successfully decarbonize, the world will experience mounting physical risks that will strain the foundations of the global economy and society. In either case, the places where people live, work, shop, and play will fundamentally change.

Decarbonizing real estate requires considering a building’s ecosystem

Ultimately, the only way to reduce the risks of climate change is to decarbonize. Real-estate players have a wide array of options for how to proceed, including low-carbon development and construction ; building retrofits to improve energy efficiency; upgrades to heating, cooling, and lighting technology; and technology to manage demand and consumption. But decarbonization is not solely a technical challenge. To develop the most appropriate path, real-estate players need to understand the range of decarbonization options and their financial and strategic costs and benefits.

Decarbonizing real estate

To decarbonize, industry players can take the following steps:

• Understand the starting point. Quantify baseline emissions of each building. This helps real-estate players prioritize where to start (for example, individual buildings, asset classes, or regions) and determine how far there is to go to reach zero emissions.
• Set targets. Decide which type of decarbonization target to set. There is a range of potential target-setting standards that take different approaches (for example, measuring absolute emissions versus emissions intensity, or setting targets at the sector level versus asset level). Players should develop a “house view” on targets that achieve business, investor, stakeholder, regulatory, and other objectives.
• Identify decarbonization levers. Build an asset- or portfolio-level abatement curve. A marginal abatement cost curve  provides a clear view of the potential cost/return on investment of a given emissions-reduction lever along with the impact of that lever on emissions reduction. This approach can be complemented with market and policy scenarios that change the relative costs and benefits of each potential abatement lever.
• Execute. Set up the mechanisms to effectively deploy the decarbonization plan. These may involve making changes to financing and governance, stakeholder engagement (investors, joint-venture partners, operators, and tenants), and a range of operational and risk-management aspects of the business.
• Track and improve. As investors, lenders, and tenants make their own decarbonization commitments, they will need to demonstrate that their real estate is indeed decarbonizing. Thus, much of the value of decarbonizing will come from the ability to demonstrate emissions reduction to potential stakeholders. Building the ability to monitor and progressively reduce emissions on the path to net zero will create an opportunity for players to differentiate.

Create new sources of value and revenue streams for investors, tenants, and communities

As the economy decarbonizes, real-estate players can use their locations, connections to utility systems, local operational footprints, and climate intelligence to create new revenue streams, improve asset values, or launch entirely new businesses.

Opportunities include the following:

• Local energy generation and storage. Real-estate firms can use their physical presence to generate and store energy. For example, property developers have been outfitting buildings with solar arrays and batteries, helping to stabilize energy grids and reduce the costs associated with clean energy. 5 “5 ways clean tech is making commercial RE more energy efficient,” Jones Lang LaSalle, April 20, 2021.
• Green buildings to attract more tenants. Developers and property managers can invest in developing green buildings or retrofitting older buildings to make them green to meet the growing appetite for sustainable workplaces and homes.
• Green-building materials. Players can explore the advantages of green steel, tall timber, modular construction, and other emerging technologies and materials that may have additional benefits, such as faster and lower-cost construction.
• Extra services on-site. Firms can introduce new revenue streams, including vehicle charging, green-facilities management, and other on-site services that enable occupants’ sustainable preferences.
• Services for reducing and tracking emissions. Firms can support occupants by tracking emissions and offering solutions to reduce carbon footprints. These services could include smart sensors and tracking energy consumption through heating, cooling, lighting, and space management.
• Differentiated capital attraction. Given the volume of capital that has already been committed to achieving net zero, firms that are able to decarbonize will have an advantage in attracting capital. Real-estate players may, for example, create specific funds for net-zero buildings or investment themes that support community-scale decarbonization.

The coming climate transition will create seismic shifts in the real-estate industry, changing tenants’ and investors’ demands, the value of individual assets, and the fundamental approaches to developing and operating real estate. Smart players will get ahead of these changes and build climate intelligence early by understanding the implications for asset values, finding opportunities to decarbonize, and creating opportunity through supporting the transition.

Real estate not only will play a critical role in determining whether the world successfully decarbonizes but also will continue to reinvent the way we live, work, and play through these profound physical and economic changes.

This article was edited by Katy McLaughlin, a senior editor in the southern California office.

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Dissertations / Theses on the topic 'Risk management - Insurance'

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Lin, Yijia. "Mortality Risk Management." Digital Archive @ GSU, 2006. http://digitalarchive.gsu.edu/rmi_diss/14.

Fischer, Tom. "Valuation and risk management in life insurance." Phd thesis, [S.l. : s.n.], 2004. http://elib.tu-darmstadt.de/diss/000412.

Siyi, Zhou. "Essays on financial and insurance risk management." Thesis, Imperial College London, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.586894.

Mutenga, Stanley. "Risk management for property casualty insurance companies." Thesis, City University London, 2001. http://openaccess.city.ac.uk/7600/.

Siokis, Vasilios. "Risk measurement and management of insurance companies." Thesis, City University London, 2001. http://openaccess.city.ac.uk/8400/.

Agarwal, Ruchi. "Implementation of Enterprise Risk Management practices." Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/25823.

Jabbour, Mirna. "Investigation of risk management changes in insurance companies." Thesis, Brunel University, 2013. http://bura.brunel.ac.uk/handle/2438/7964.

Siu, Tak-kuen. "Risk measures in finance and insurance." Hong Kong : University of Hong Kong, 2001. http://sunzi.lib.hku.hk/hkuto/record.jsp?B2323426X.

Li, Chenxuan. "Risk management in ship finance : a marine insurance perspective." Thesis, University of Exeter, 2017. http://hdl.handle.net/10871/33735.

Leboho, Nakedi Wilson. "Quantitative Risk Management and Pricing for Equity Based Insurance Guarantees." Thesis, Stellenbosch : Stellenbosch University, 2015. http://hdl.handle.net/10019.1/96980.

Paiz, Fernando. "Political risk insurance : a solution to capital flight?" Thesis, Massachusetts Institute of Technology, 1989. http://hdl.handle.net/1721.1/67102.

Sundin, Jesper. "Risk contribution and its application in asset and risk management for life insurance." Thesis, KTH, Matematisk statistik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-188873.

Taylan, Arzu. "Urban Disaster Risk Management With Compulsory Earthquake Insurance In Turkey." Phd thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/3/12611234/index.pdf.

Jiang, Yuansheng. "Health insurance demand and health risk management in rural China /." Frankfurt am Main [u.a.] : Lang, 2004. http://www.gbv.de/dms/zbw/387845968.pdf.

蕭德權 and Tak-kuen Siu. "Risk measures in finance and insurance." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B31242297.

Chen, Shu-Ling. "Three essays on agricultural and catastrophic risk management." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1179368620.

Roselle, Russell Paul. "Rational Corporate Risk Management Policy: An Extension of Traditional Risk Management Theory to Incorporate Observed Managerial Behavior." Thesis, Virginia Tech, 2006. http://hdl.handle.net/10919/31910.

Reynecke, Werner Nielen. "Enterprise risk management in the South African insurance industry / W.N. Reynecke." Thesis, North-West University, 2008. http://hdl.handle.net/10394/4215.

Vo, Dinh-Tri. "Essays on enterprise risk management : the case of european insurance industry." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLE018/document.

Strydom, Johann J. (Johann Jurie). "Risk warehousing within insurance firms and the role of securitization." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/65789.

ZHANG, Jian. "Insurance and self-protection for increased risk aversion." Digital Commons @ Lingnan University, 2017. https://commons.ln.edu.hk/fin_etd/18.

Krauss, George E. Kuhne Gary William. "Continuing professional education of insurance and risk management practitioners a comparative case study of customer service representatives, insurance agents and risk managers /." [University Park, Pa.] : Pennsylvania State University, 2009. http://etda.libraries.psu.edu/theses/approved/WorldWideIndex/ETD-4837/index.html.

Huh, Jungmoo. "A study of risk management and capital allocation in Korean Insurance Companies." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/65804.

Maj, Mateusz. "Essays in risk management: conditional expectation with applications in finance and insurance." Doctoral thesis, Universite Libre de Bruxelles, 2012. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209668.

Rinaldo, Iversen Pierre. "A Case Study on Long-tail Risks and Risk Mitigation in Risk Management : How can AGCS make best use of risk mitigation measures for drafting product liability policy wordings?" Thesis, Umeå universitet, Företagsekonomi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-150522.

Gallenstein, Richard Anthony GALLENSTEIN. "Three Essays on Agricultural Microfinance and Risk Management." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1500565176891763.

Hunter, John, and Jakob Westin. "Credit risk management : Possibilities for a housing price insurance on the Swedish market - lessons from Canada." Thesis, KTH, Bygg- och fastighetsekonomi, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-76091.

Mustika, Ganjar. "Optimal bank regulation and risk management for Indonesia." Thesis, Loughborough University, 2004. https://dspace.lboro.ac.uk/2134/8000.

Giesbert, Lena-Anna. "Microinsurance and risk management." Doctoral thesis, Humboldt-Universität zu Berlin, Landwirtschaftlich-Gärtnerische Fakultät, 2014. http://dx.doi.org/10.18452/16900.

Schreiber, Irene [Verfasser], and Francesca [Akademischer Betreuer] Biagini. "Risk-minimization for life insurance liabilities / Irene Schreiber. Betreuer: Francesca Biagini." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2012. http://d-nb.info/1031380809/34.

Smith, Etienne Roche. "A critical analysis of current vs proposed risk underwriting and claims management procedures at Sasguard Insurance Company Ltd." Thesis, Stellenbosch : University of Stellenbosch, 2007. http://hdl.handle.net/10019.1/847.

Coffey, Brian K. "NEW INPUT AND OUTPUT RISK MANAGEMENT STRATEGIES FOR LIVESTOCK PRODUCERS." UKnowledge, 2001. http://uknowledge.uky.edu/gradschool_theses/164.

Doff, René Roelof. "Risk management for insurance firms a framework for fair value and economic capital /." Enschede : University of Twente [Host], 2006. http://doc.utwente.nl/57118.

Collin, Constance. "Towards a working crop insurance market : an integrated strategy of systemic risk management." Thesis, Paris 10, 2018. http://www.theses.fr/2018PA100006.

Daňková, Marcela. "Pojištění pro kynologickou organizaci a její členy." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2008. http://www.nusl.cz/ntk/nusl-376772.

Chen, Hua. "Contingent Claim Pricing with Applications to Financial Risk Management." Digital Archive @ GSU, 2008. http://digitalarchive.gsu.edu/rmi_diss/22.

Matsdotter, Lina, and Ellinor Drevendal. "Solvens II : Hur påverkas Svenska försäkringsbolag av de ökade kraven på intern kontroll, riskhantering och rapportering till marknaden?" Thesis, Södertörns högskola, Institutionen för samhällsvetenskaper, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-19854.

Yang, Jie. "Incentives of Managed Care Insurance and Treatment Choices in Low-Risk Primary Cesarean Delivery." Thesis, Wayne State University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10929029.

In response to climbing health care costs in the United States, many insurers and policy makers would like to eliminate waste in healthcare by steering spending toward the most cost-effective treatments. Obstacles to achieving this goal include identifying specific medical settings where overuse occurs, and then developing strategies to prevent overuse without harming patient welfare. My study examined childbirth, the number one reason for hospitalization in the US, where the overuse of medical resources primarily takes the form of nonmedically indicated cesarean deliveries.

The financial tools (physician payment differential and patient’s cost sharing) and other tools (utilization management, physician profiling, and practice guidelines) of managed care insurance create varied incentives that could affect behaviors of physicians and patients. Using data from the MarketScan commercial database, I proved that in a fee-for-service setting, physician’s financial incentives (physician payment differential) and patient’s financial disincentive (patient’s cost-sharing) affect treatment choices on childbirth delivery method, and other incentives from managed care insurance have little effect. My study also found that more restrictive nonfinancial tools in non-capitated HMOs which are expected to reduce the use of cesarean sections turn out to have little effect, while lower cost-sharing in non-capitated HMOs leads to more use of cesareans. It could provide two health policy implications: (1) health plans with generous benefits may need more restrictions and effective regulations aimed at cost control, and (2) raising patients cost-sharing may prove effective for managing medical expenses. Finally, a “What if” analysis sheds light on the likely effectiveness of various changes in managed care insurance design intended to reduce low-risk primary cesarean deliveries.

Bierth, Christopher [Verfasser], Gregor Nikolaus Felix [Akademischer Betreuer] Weiß, and Denefa [Gutachter] Bostandzic. "Essays on risk management and systemic risk in insurance / Christopher Bierth. Betreuer: Gregor Nikolaus Felix Weiß. Gutachter: Denefa Bostandzic." Dortmund : Universitätsbibliothek Dortmund, 2016. http://d-nb.info/1112268367/34.

Bierth, Christopher [Verfasser], Gregor [Akademischer Betreuer] Weiß, and Denefa [Gutachter] Bostandzic. "Essays on risk management and systemic risk in insurance / Christopher Bierth. Betreuer: Gregor Nikolaus Felix Weiß. Gutachter: Denefa Bostandzic." Dortmund : Universitätsbibliothek Dortmund, 2016. http://nbn-resolving.de/urn:nbn:de:101:1-201608252317.

Prud'homme, Andrea McGee. "Business continuity in the supply chain planning for disruptive events /." Diss., Connect to online resource - MSU authorized users, 2008.

Berg, Isak, and Richard Stadig. "Market-consistent valuation of a pension product with guarantee in line with Solvency II : An applied case study to improve knowledge about how rationality and stressed conditions with respect to market- and insurance risk will impact the balance sheet." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-123141.

Essel, Rudolf. "Short-term insurance of political risks in South Africa." Thesis, Stellenbosch : Stellenbosch University, 2012. http://hdl.handle.net/10019.1/20005.

Seo, Sangtaek. "Effects of federal risk management programs on investment, production, and contract design under uncertainty." Texas A&M University, 2004. http://hdl.handle.net/1969.1/3117.

Tian, Ruilin. "Moment Problems with Applications to Value-At-Risk and Portfolio Management." Digital Archive @ GSU, 2008. http://digitalarchive.gsu.edu/rmi_diss/21.

Wu, Mei Lan Actuarial Studies Australian School of Business UNSW. "Modelling dependent risks for insurer risk management: experimental studies with copulas." 2007. http://handle.unsw.edu.au/1959.4/40645.

Ho, Chao-chin, and 賀照芹. "Life Insurance Industry Risk Management Study." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/55666702064175425738.

Lin, Yi-Yun, and 林意芸. "Risk Management and Risk Taking of Life Insurance Industry in Taiwan." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/65084300921386079307.

Lin, Yi-Hsin, and 林宜欣. "Determinants of Aviation Insurance and Risk Management Strategy." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/89502941702179698483.

賴昱誠. "The risk management by the life insurance agents." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/35743281676269487694.