Portrait of Dr Pradip Tapadar

Dr Pradip Tapadar

Senior Lecturer in Actuarial Science

About

Pradip is a Fellow of the Institute and Faculty of Actuaries in the UK. He is also a Fellow of the Institute of Actuaries of India. Pradip's doctoral thesis The impact of multifactorial genetic disorders on long-term Insurance was researched at Heriot-Watt University. His undergraduate and postgraduate studies were in Statistics at the Indian Statistical Institute, Kolkata, India, and he holds a postgraduate diploma in Actuarial Science from Heriot-Watt University.

Pradip joined CASRI in December 2006. He serves on the Research and Enterprise Committee, is the Head of Research for CASRI, and co-ordinates the Actuarial Science seminar programme.

He has worked in the life insurance industry for more than 5 years; his business exposure includes product development, pricing, valuation, financial reporting, and business planning experience with HDFC Standard Life Insurance Company, a joint venture life insurance firm between Standard Life and HDFC, based in Mumbai, India. He has similar UK experience gained with Standard Life in Edinburgh, and has carried out research at the Genetics and Insurance Research Centre at Heriot-Watt University, Edinburgh.

Together with Guy Thomas, Pradip runs the blog Loss Coverage - why insurance works better with some adverse selection.

Research interests

Economic capital and financial risk management

With the advent of new risk-based regulations for financial services firms, specifically Basel 2 and Basel 3 for banks and Solvency 2 for insurers, there is now a heightened focus on the practical implementation of quantitative risk management techniques for firms and defined benefit pension schemes operating within the financial services sector.

In particular, financial services firms are now expected to self-assess and quantify the amount of capital they need to cover the risks they are running. This self-assessed quantum of capital is commonly termed risk, or economic, capital.

At Kent we are actively involved in developing rigorous risk management techniques to explicitly measure how much risk a firm or pension scheme is taking, holistically, across the entire spectrum of risks it accepts.

More about this area of research

Public policy aspects of risk classification

Restrictions on risk classification can lead to adverse selection, and actuaries usually regard this as a bad thing. However, restrictions do exist in many countries, suggesting that policymakers often perceive some merit in such restrictions. Careful re-examination of the usual actuarial arguments can help to reconcile these observations.

Models of insurance purchasing behaviour under different risk classification regimes can quantify the effects of particular bans, e.g. on insurers’ use of genetic test results, or gender classification in the European Union.

More about this area of research

Supervision

  • Aniketh Pittea - Impact of changing population demographics on pension plans
  • Indradeb Chatterjee - Insurance loss coverage and social welfare

Graduated PhD students

  • Mingjie Hao (2017): Insurance loss coverage under restricted risk classification
  • Mayukh Gayen (2012): Quantification of economic capital and its constituent risk components for life insurance annuity portfolios
  • Wei Yang (2012): Risk assessment of defined benefit pension schemes - an economic capital approach

Professional

  • Fellow of the Institute and Faculty of Actuaries
  • Fellow of the Institute of Actuaries of India.

Publications

Showing 50 of 57 total publications in the Kent Academic Repository. View all publications.

Article

  • Oberoi, J., Pittea, A. and Tapadar, P. (2019). A graphical model approach to simulating economic variables over long horizons. Annals of Actuarial Science [Online]:1-22. Available at: https://doi.org/10.1017/S1748499519000022.
    We present an application of statistical graphical models to simulate economic variables for the purpose of risk calculations over long time horizons. We show that this approach is relatively easy to implement, and argue that it is appealing because of the transparent yet flexible means of achieving dimension reduction when many variables must be modelled. Using United Kingdom data as an example, we demonstrate the development of an economic scenario generator that can be used by life insurance companies and pension funds. We compare different algorithms to select a graphical model, based on p-values, AIC, BIC, and deviance. We find them to yield reasonable results and relatively stable structures in our example, suggesting that it would be beneficial for actuaries to include these models in their toolkit.
  • Hao, M., Macdonald, A., Tapadar, P. and Thomas, R. (2019). Insurance loss coverage and social welfare. Scandinavian Actuarial Journal [Online] 2019:113-128. Available at: https://doi.org/10.1080/03461238.2018.1513865.
    Restrictions on insurance risk classification may induce adverse selection, which is usually perceived as a bad outcome, both for insurers and for society. However, a social benefit of modest adverse selection is that it can lead to an increase in `loss coverage', defined as expected losses compensated by insurance for the whole population. We reconcile the concept of loss coverage to a utilitarian concept of social welfare commonly found in economic literature on risk classification. For iso-elastic insurance demand, ranking risk classification schemes by (observable) loss coverage always gives the same ordering as ranking by (unobservable) social welfare.
  • Hao, M., Macdonald, A., Tapadar, P. and Thomas, R. (2018). Insurance loss coverage and demand elasticities. Insurance: Mathematics and Economics [Online] 79:15-25. Available at: https://doi.org/10.1016/j.insmatheco.2017.12.002.
    Restrictions on insurance risk classification may induce adverse selection, which is usually perceived as a bad outcome. We suggest a counter-argument to this perception in circumstances where modest levels of adverse selection lead to an increase in `loss coverage', defined as expected losses compensated by insurance for the whole population. This happens if the shift in coverage towards higher risks under adverse selection more than offsets the fall in number of individuals insured. The possibility of this outcome depends on insurance demand elasticities for higher and lower risks. We state elasticity conditions which ensure that for any downward-sloping insurance demand functions, loss coverage when all risks are pooled at a common price is higher than under fully risk-differentiated prices. Empirical evidence suggests that these conditions may be realistic for some insurance markets.
  • Hao, M., Macdonald, A., Tapadar, P. and Thomas, R. (2016). Insurance loss coverage under restricted risk classification: The case of iso-elastic demand. ASTIN Bulletin [Online] 46:265-291. Available at: http://dx.doi.org/10.1017/asb.2016.6.
    This paper investigates equilibrium in an insurance market where risk classification is restricted. Insurance demand is characterised by an iso-elastic function with a single elasticity parameter. We characterise the equilibrium by three quantities: equilibrium premium; level of adverse selection (in the economist’s sense); and “loss coverage”, defined as the expected population losses compensated by insurance. We consider both equal elasticities for high and low risk-groups, and then different elasticities. In the equal elasticities case, adverse selection is always higher under pooling than under risk-differentiated premiums, while loss coverage first increases and then decreases with demand elasticity. We argue that loss coverage represents the efficacy of insurance for the whole population; and therefore that if demand elasticity is sufficiently low, adverse selection is not always a bad thing.
  • Yang, W. and Tapadar, P. (2015). Role of the Pension Protection Fund in financial risk management of UK defined benefit pension sector: a multi-period economic capital study. Annals of Actuarial Science [Online] 9:134-166. Available at: http://dx.doi.org/10.1017/S1748499514000256.
    With the advent of formal regulatory requirements for rigorous risk-based, or economic, capital quantification for the financial risk management of banking and insurance sectors, regulators and policy-makers are turning their attention to the pension sector, the other integral player in the financial markets. In this paper, we analyse the impact of applying economic capital techniques to defined benefit pension schemes in the United Kingdom. We propose two alternative economic capital quantification approaches, first, for individual defined benefit pension schemes on a stand-alone basis and then for the pension sector as a whole by quantifying economic capital of the UK’s Pension Protection Fund, which takes over eligible schemes with deficit, in the event of sponsor insolvency. We find that economic capital requirements for individual schemes are significantly high. However, we show that sharing risks through the Pension Protection Fund reduces the aggregate economic capital requirement of the entire sector.
  • Porteous, B., Tapadar, P. and Yang, W. (2012). Economic capital for defined benefit pension schemes: An application to the UK Universities Superannuation Scheme. Journal of Pension Economics and Finance [Online] 11:471-499. Available at: http://dx.doi.org/10.1017/S1474747212000029.
    This article considers the amount of economic capital that defined benefit (DB) pension schemes potentially need to cover the risks they are running. A real open scheme, the Universities Superannuation Scheme, is modelled and used to illustrate our results and, as expected, economic capital requirements are large. We discuss the appropriateness of these results and what they mean for the DB pension scheme industry and their sponsors. The article is particularly pertinent following the recent European Commission Green Paper on the future of European pensions systems, its call for advice on reviewing the Institutions for Occupational Retirement Provision Directive and the introduction of the Basel 2 and Solvency 2 risk-based regulatory regimes for banking and insurance, respectively.
  • Tapadar, P. and Macdonald, A. (2010). Multifactorial Genetic Disorders and Adverse Selection: Epidemiology Meets Economics. Journal of Risk and Insurance [Online] 77:155-182. Available at: http://dx.doi.org/10.1111/j.1539-6975.2009.01342.x.
    The focus of genetics is shifting its contribution to common, complex disorders. New genetic risk factors will be discovered, which if undisclosed may allow adverse selection. However, this should happen only if low-risk individuals would reduce their expected utility by insuring at the average price. We explore this boundary, focusing on critical illness insurance and heart attack risk. Adverse selection is, in many cases, impossible. Otherwise, it appears only for lower risk aversion and smaller insured losses, or if the genetic risk is implausibly high. We find no strong evidence that adverse selection from this source is a threat.
  • Porteous, B. and Tapadar, P. (2008). The Impact of Capital Structure on Economic Capital and Risk Adjusted Performance. ASTIN Bulletin [Online] 38:341-380. Available at: http://dx.doi.org/10.2143/AST.38.1.2030416.
    The impact that capital structure and capital asset allocation have on financial services firm economic capital and risk adjusted performance is considered. A stochastic modelling approach is used in conjunction with banking and insurance examples. It is demonstrated that gearing up Tier 1 capital with Tier 2 capital can be in the interests of bank Tier 1 capital providers, but may not always be so for insurance Tier 1 capital providers. It is also shown that, by allocating a bank or insurance firm’s Tier 1 and Tier 2 capital to higher yielding, more risky assets, risk adjusted performance can be enhanced. These results are particularly pertinent with the advent of the new Basel 2 and Solvency 2 risk based capital initiatives, for banks and insurers respectively.
  • Porteous, B. and Tapadar, P. (2008). Asset Allocation to Optimise Life Insurance Annuity Firm Economic Capital and Risk Adjusted Performance. Annals of Actuarial Science [Online] 3:187-214. Available at: http://dx.doi.org/10.1017/S1748499500000506.
    The impact that asset allocation has on the economic capital and the risk adjusted performance of financial services firms is considered in this article. A stochastic modelling approach is used in conjunction with a life insurance annuity firm illustrative example. It is shown that traditional solvency driven deterministic approaches to financial services firm asset allocation can yield sub optimal results in terms of minimising economic capital or maximising risk adjusted performance. Our results challenge the conventional wisdom that the assets backing life insurance annuities and financial services firm capital should be invested in low risk, bond type, assets. Implications for firms, customers, capital providers and regulators are discussed.
  • Macdonald, A., Pritchard, D. and Tapadar, P. (2006). The Impact of Multifactorial Genetic Disorders on Critical Illness Insurance: A Simulation Study Based on UK Biobank. ASTIN Bulletin [Online] 36:311-346. Available at: http://dx.doi.org/10.2143/AST.36.2.2017924.
    The UK Biobank project is a proposed large-scale investigation of the combined effects of genotype and environmental exposures on the risk of common diseases. It is intended to recruit 500,000 subjects aged 40-69, to obtain medical histories and blood samples at outset, and to follow them up for at least 10 years. This will have a major impact on our knowledge of multifactorial genetic disorders, rather than the rare but severe single-gene disorders that have been studied to date.What use may insurance companies make of this knowledge, particularly if genetic tests can identify persons at different risk? We describe here a simulation study of the UK Biobank project. We specify a simple hypothetical model of genetic and environmental influences on the risk of heart attack. A single simulation of UK Biobank consists of 500,000 life histories over
    10 years; we suppose that case-control studies are carried out to estimate age-specific odds ratios, and that an actuary uses these odds ratios to parameterise a model of critical illness insurance. From a large number of such simulations we obtain sampling distributions of premium rates in different strata defined by genotype and environmental exposure. We conclude that the ability of such
    a study reliably to discriminate between different underwriting classes is limited, and depends on large numbers of cases being analysed.

Book

  • Porteous, B. and Tapadar, P. (2005). Economic Capital and Financial Risk Management for Financial Services Firms and Conglomerates. Palgrave Macmillan.

Conference or workshop item

  • Tapadar, P. (2019). How can adverse selection increase social welfare?. In: Actuarial Teachers’ and Researchers’ Conference.
    This talk will focus on the effects of bans on insurance risk classification on utilitarian social welfare. We consider two regimes: full risk classification, where insurers charge the actuarially fair premium for each risk; and pooling, where risk classification is banned and for institutional or regulatory reasons, insurers do not attempt to separate risk classes, but charge a common premium for all risks. For the case of iso-elastic insurance demand, we derive sufficient conditions on higher and lower risks' demand elasticities which ensure that utilitarian social welfare is higher under pooling than under full risk classification. Empirical evidence suggests that these conditions may be realistic for some insurance markets.
  • Bonnar, S., Pittea, A. and Tapadar, P. (2019). Measuring pension plan risk from an economic capital perspective. In: Joint CIA, IFoA, SOA Webcast. Available at: https://www.actuaries.org.uk/learn-develop/attend-event/joint-cia-ifoa-soa-webcast-measuring-pension-plan-risk-economic-capital-perspective.
    Economic capital, the 0.5th percentile result of a stochastic projection, is the primary risk measure employed. The research examines not only the difference in economic capital requirements between typical plans in the three countries, but also its sensitivity to changes in asset allocation, contributions, and starting funded status.
  • Tapadar, P. (2019). Insurance risk pooling, loss coverage and social welfare: When is adverse selection not adverse?. In: IFAM Seminars, University of Liverpool.
    Restrictions on insurance risk classification may induce adverse selection, which is usually perceived as a bad outcome, both for insurers and for society. We suggest a counter-argument to this perception in circumstances where modest levels of adverse selection lead to an increase in `loss coverage’, defined as expected losses compensated by insurance for the whole population. This happens if the shift in coverage towards higher risks under adverse selection more than offsets the fall in number of individuals insured. We also reconcile the concept of loss coverage to a utilitarian concept of social welfare commonly found in economic literature. For iso-elastic insurance demand, ranking risk classification schemes by (observable) loss coverage always gives the same ordering as ranking by (unobservable) social welfare.
  • Chatterjee, I., Macdonald, A., Tapadar, P. and Thomas, R. (2018). When is utilitarian welfare higher under insurance risk pooling?. In: Mathematical and Statistical Methods for Actuarial Sciences and Finance (MAF 2018). Springer, pp. 219-223. Available at: https://doi.org/10.1007/978-3-319-89824-7_40.
    This paper focuses on the effects of bans on insurance risk classification on utilitarian social welfare. We consider two regimes: full risk classification, where insurers charge the actuarially fair premium for each risk, and pooling, where risk
    classification is banned and for institutional or regulatory reasons, insurers do not attempt to separate risk classes, but charge a common premium for all risks. For the case of iso-elastic insurance demand, we derive sufficient conditions on higher and lower risks’ demand elasticities which ensure that utilitarian social welfare is higher under pooling than under full risk classification. Empirical evidence suggests that these conditions may be realistic for some insurance markets.
  • Tapadar, P. and Thomas, R. (2018). Why insurance works better with some adverse selection. In: International Congress of Actuaries.
    Regulatory restrictions on insurance risk classification are a common feature of personal insurance markets. Whilst such
    restrictions appear motivated by social objectives, they may also induce adverse selection. This is usually perceived as a
    disadvantage, both for insurers and for society. We suggest a counter-argument to this perception in circumstances where
    modest levels of adverse selection lead to an increase in ‘loss coverage’, defined as expected losses compensated by
    insurance for society as a whole. This happens if the shift in coverage towards higher risks more than offsets the fall in
    number of individuals insured.

    The possibility of this outcome depends on insurance demand elasticities for higher and lower risks. We state elasticity
    conditions which ensure that for any downward-sloping insurance demand functions, loss coverage when all risks are pooled
    at a common price is higher than under fully risk-differentiated prices. We also discuss some empirical evidence on
    insurance demand elasticities, and some limitations of the loss coverage concept. For a more discursive treatment, see our
    recent book Thomas (2017) and papers (Hao et al. (2016, 2016a, 2016b)).
  • Tapadar, P. (2016). Insurance Risk Classification: How much is socially optimal?. In: Heriot-Watt University Seminar Series.
    Restrictions on insurance risk classification can lead to troublesome adverse selection. A simple version of the usual argument is as follows. If insurers cannot charge risk-differentiated premiums, more insurance is bought by higher risks and less insurance is bought by lower risks. This raises the equilibrium pooled price of insurance above a population-weighted average of true risk premiums. Also, since the number of higher risks is usually smaller than the number of lower risks, the total number of risks insured usually falls. This combination of a rise in price and fall in demand is usually portrayed as a bad outcome, both for insurers and for society.

    However, some restrictions on insurance risk classification are common in practice. For example, since 2012 insurers in the European Union has been barred from using gender in underwriting; and many countries have placed some limits on insurers' use of genetic test results. We can observe that policy-makers often appear to perceive some merit in such restrictions. This observation motivates a careful re-examination of the usual adverse selection argument.

    In this talk, we study the implications of insurers not being allowed to use risk-differentiated premiums. First, we provide a micro-foundation in variations across individuals' utility of wealth to obtain an aggregate insurance demand function. Then, within this framework, we formulate the concept of loss coverage, defined as expected losses compensated by insurance, as a metric for evaluating different insurance risk classification schemes. Finally, we reconcile loss coverage to a utilitarian concept of social welfare, defined as the sum of individuals' expected utilities over the entire population.

    Specifically, we show that if insurance premiums are small relative to wealth, maximising loss coverage maximises social welfare. From a policy perspective, this may be a useful result because maximising loss coverage does not require knowledge of individuals' (unobservable) utility functions; loss coverage is based solely on observable quantities.
  • Tapadar, P. (2016). Adverse selection and loss coverage in insurance markets. In: CASRI Seminar.
  • Tapadar, P. (2016). Risk assessment of UK DB pension schemes. In: CASRI Seminar.
  • Tapadar, P. (2016). Risk assessment of UK DB pension schemes. In: University of Waterloo Workshop.
  • Hao, M., Tapadar, P. and Thomas, R. (2015). Loss coverage in insurance markets: why adverse selection is not always a bad thing. In: International Actuarial Association Colloquium. Available at: http://www.actuaries.org/oslo2015/papers/IAALS-Hao&Tapadar&Thomas.pdf.
    This paper investigates equilibrium in an insurance market where risk classification is restricted. Insurance demand is characterised by an iso-elastic function with a single elasticity
    parameter. We characterise the equilibrium by three quantities: equilibrium premium; level of adverse selection; and “loss coverage”, defined as the expected population losses compensated
    by insurance. We find that equilibrium premium and adverse selection increase monotonically with demand elasticity, but loss coverage first increases and then decreases. We argue that
    loss coverage represents the efficacy of insurance for the whole population; and therefore, if demand elasticity is sufficiently low, adverse selection is not always a bad thing.
  • Tapadar, P. (2015). Insurance Risk Classification: How much is socially optimal?. In: Lecture at Indian Statistical Institute.
  • Tapadar, P. (2015). Why Adverse Selection Need Not Be Adverse. In: Actuarial Teachers’ and Researchers’ Conference.
    Restrictions on insurance risk classification can lead to troublesome adverse selection. A simple version of the usual argument is as follows. If insurers cannot charge risk-differentiated premiums, more insurance is bought by higher risks and less insurance is bought by lower risks. This raises the equilibrium pooled price of insurance above a population-weighted average of true risk premiums. Also, since the number of higher risks is usually smaller than the number of lower risks, the total number of risks insured usually falls. This combination of a rise in price and fall in demand is usually portrayed as a bad outcome, both for insurers and for society.

    However, some restrictions on insurance risk classification are common in practice. For example, since 2012 insurers in the European Union has been barred from using gender in underwriting; and many countries have placed some limits on insurers' use of genetic test results. We can observe that policymakers often appear to perceive some merit in such restrictions. This observation motivates a careful re-examination of the usual adverse selection argument.

    In this talk, we study the implications of insurers not being allowed to use risk-differentiated premiums. We model the insurance purchasing behaviour of individuals based on their degrees of risk aversion and utility of wealth. We assume that an equilibrium has been reached, where insurers break even by charging the same `pooled' premium to both high and low risks. We characterise this equilibrium by two quantities: adverse selection, defined as the correlation of insurance coverage and losses; and `loss coverage', defined as the expected losses compensated by insurance.

    We find that adverse selection is always higher under pooling than under risk-differentiated premiums, as expected. However, loss coverage can be higher or lower under pooling than under risk-differentiated premiums. Loss coverage is higher under pooling if the shift in coverage towards higher risks more than compensates for the fall in number of risks insured. In other words, loss coverage is higher under pooling if adverse selection at the equilibrium is modest, but lower under pooling if adverse selection at the equilibrium is severe.

    Loss coverage represents the expected losses compensated by insurance for the whole population. We argue that this is a good metric for the social efficacy of insurance, and hence one which public policymakers may reasonably wish to maximise. If this argument is accepted, modest adverse selection under pooling can be a good thing, because it leads to higher loss
    coverage than risk-differentiated premiums.
  • Tapadar, P. (2015). Role of the Pension Protection Fund in financial risk management of UK defined benefit pension sector: a multi-period economic capital study. In: International Actuarial Association Colloquium. Available at: http://www.actuaries.org/oslo2015/presentations/PBSS-Tapadar&al-P.pdf.
    With the advent of formal regulatory requirements for rigorous risk-based, or economic, capital quantification for the financial risk management of banking and insurance sectors, regulators and policy-makers are turning their attention to the pension sector, the other integral player in the financial markets. In this paper, we analyse the impact of applying economic capital techniques to defined benefit pension schemes in the UK. We propose two alternative economic capital quantification approaches, firstly for individual defined benefit pension schemes on a stand-alone basis and then for the pension sector as a whole by quantifying economic capital of the UK's Pension Protection Fund, which takes over eligible schemes with deficit, in the event of sponsor insolvency. We find that economic capital requirements for individual schemes are significantly high. However, we show that sharing risks through the Pension Protection Fund reduces the aggregate economic capital requirement of the entire sector.
  • Tapadar, P. (2014). An Economic Capital study of the Pension Protection Fund and UK’s Defined Benefit Pension Sector. In: Actuarial Teachers and Researchers Conference. Available at: http://www.maths.ed.ac.uk/assets/images/atrc2014/08_Pradip_Tapadar_301114.pdf.
    With the advent of formal regulatory requirements for rigorous risk-based, or economic, capital quantification for the financial risk management of banking and insurance sectors, regulators and policy-makers are turning their attention to the pension sector, the other integral player in the financial markets. In this paper, we analyse the impact of applying economic capital techniques to defined benefit pension schemes in the UK. We propose two alternative economic capital quantification approaches, firstly for individual defined benefit pension schemes on a stand-alone basis and then for the pension sector as a whole by quantifying economic capital of the UK’s Pension Protection Fund, which takes over eligible schemes with deficit, in the event of sponsor insolvency. We find that economic capital requirements for individual schemes are significantly high. However, we show that sharing risks through the Pension Protection Fund, reduces the aggregate economic capital requirement of the entire sector.
  • Tapadar, P. (2012). Actuarial Education and Examinations. In: 14th Global Conference of Actuaries.
  • Tapadar, P. (2012). Genetic Testing, Insurance Underwriting and Adverse Selection. In: 14th Global Conference of Actuaries.
  • Tapadar, P. (2011). Financial Risk Management of Pension Schemes - An Economic Capital Approach. In: Queen’s University Management School Seminar Series.
  • Tapadar, P. (2011). Economic Capital and Financial Risk Management. In: 13th Global Conference of Actuaries. Available at: http://www.actuariesindia.org/events/global-conference-of-actuaries/details/8-13th-gca.html.
    The latest global financial crisis has highlighted the need for financial services firms to adopt comprehensive risk management techniques to identify, manage and mitigate risks promptly and efficiently. To this end, a key risk management tool is to hold sufficient capital to back the risks a business is running. In recent times, financial services regulators have also initiated a move towards risk-based economic capital approach with different regulations for banks (Basel 2 and 3) and insurance firms (Solvency 2). In this paper, a generic definition of economic capital is proposed using a stochastic approach, which is then used to quantify economic capital for a capital repayment mortgage, a lifetime mortgage, a life insurance annuity and a conglomerate operating a range of financial services. The paper highlights economic capital as a risk management tool that unifies capital calculation techniques across all financial services firms and conglomerates, irrespective of their line of operation.
  • Tapadar, P. (2010). Multifactoral Genetic Disorders and Adverse Selection: Epidemiology Meets Economics. In: Royal Statistical Society Conference.
    Insurance underwriting aims to identify risk factors that stratify customers into homogeneous groups, so that appropriate premiums can be charged for each group. However, use of genetic risk factors, over which individuals have no control, is controversial. But progress in genetic research is enabling better understanding of gene-environment interactions and associated multifactorial disorders. So, private and undisclosed genetic information may allow adverse selection, as insurers can only charge an average price. Adverse selection will occur if the lowest risk group decides against purchasing insurance when their expected utility of insurance falls below a certain threshold. We explore this boundary.
  • Tapadar, P. (2010). Economic Capital - A Unifying Approach. In: International Congress of Actuaries. Available at: http://www.ica2010.com.
    With the advent of new risk-based regulations for financial services firms, specifically Basel 2 for banks and Solvency 2 for insurers, there is now a heightened focus on the practical implementation of quantitative risk management techniques for firms operating within the financial services industry. In particular, financial services firms are now expected to self assess and quantify the amount of capital that they need, to cover the risks they are running. This self-assessed quantum of capital is commonly termed risk, or economic, capital. Economic capital has the potential to make financial services firms more risk-aware in their capital management, enabling investors and regulators to easily compare financial strength and profitability across business lines and sectors.

    The first part of the presentation is based on Srinivasan and Tapadar (2008) and Porteous and Tapadar (2005). It focuses on the implementation of economic capital techniques to show how economic capital can be calculated for companies offering different financial products with varying risk profiles. A stochastic approach, using graphical models, is used in conjunction with examples of a capital repayment mortgage, a lifetime mortgage and a life insurance annuity product. This will demonstrate economic capital as a tool that not only meets the needs of all interested parties, but also unifies capital calculation techniques across all financial services firms, irrespective of their line of operation.

    The second half of the presentation is based on Porteous and Tapadar (2008) which advances the techniques further to quantify the impact of capital structure and capital asset allocation on a firm's economic capital and risk adjusted performance. It is demonstrated that under certain circumstances, gearing up Tier 1 capital with Tier 2 capital can be in the interests of the firms' Tier 1 capital providers. The technique is again generic and can be applied to any financial services firm.
  • Tapadar, P. (2009). Asset Allocation to Optimise Life Insurance Annuity Firm Economic Capital and Risk Adjusted Performance. In: Royal Statistical Society Conference. Available at: http://www.rss.org.uk.
    With the advent of new risk-based regulations for financial services firms, specifically Basel 2 for banks
    and Solvency 2 for insurers, there is now a heightened focus on the practical implementation of
    quantitative risk management techniques for firms operating within the financial services industry.
    In particular, financial services firms are now expected to self assess and quantify the amount of capital
    that they need, to cover the risks they are running. This self assessed quantum of capital is commonly
    termed risk, or economic, capital.
    This talk is concerned with two important questions:
    Question 1: How should a capital constrained firm allocate its assets to minimise its economic capital
    requirement?
    Question 2: How should a firm allocate its assets to optimise its risk adjusted performance?
    The talk will focus on the impact that asset allocation has on the economic capital and the risk adjusted
    performance of financial services firms. A stochastic approach, using graphical models, is used in
    conjunction with a life insurance annuity firm as an illustrative example. It is shown that traditional
    solvency-driven deterministic approaches to financial services firm asset allocation can yield suboptimal
    results in terms of minimising economic capital or maximising risk adjusted performance.
    Our results challenge the conventional wisdom that the assets backing life insurance annuities and
    financial services firm capital should be invested in low risk, bond type, assets. Implications for firms,
    customers, capital providers and regulators are also considered.
  • Tapadar, P. (2009). The Impact of Capital Structure on Economic Capital and Risk Adjusted Performance. In: Actuarial Teachers and Researchers Conference. Available at: http://www.qub.ac.uk/schools/QueensUniversityManagementSchool/ATRC2009/.
  • Tapadar, P. (2008). The Impact of Asset Allocation on Financial Services Firm Economic Capital and Risk Adjusted Performance. In: Actuarial Teachers and Researchers Conference.
  • Tapadar, P. and Srinivasan, V. (2007). Economic Capital - A Unifying Approach. In: Action Group for Banking Networking Evening. Available at: http://www.actuaries.org.uk/members/pages/networking-evening-20071024.
  • Tapadar, P. and Porteous, B. (2007). Identify, Measure and Manage Multiple, Dependent Risks and Diversification Benefits. In: Risk Management Techniques and Capital Allocation Processes for Insurers.
  • Tapadar, P. (2007). An Introduction to Economic Capital for Financial Services Firms. In: Risk Management & Solvency 2 Conference.
  • Tapadar, P. and Porteous, B. (2006). Economic Capital for Financial Services Conglomerates. In: Oxford Workshop on Financial Risk.
  • Tapadar, P. (2006). The Impact of Multifactorial Genetic Disorders on Critical Illness Insurance: A Simulation Study Based on UK Biobank. In: Young Statisticians Meeting.
  • Tapadar, P. and Porteous, B. (2006). Economic Capital for Financial Services Conglomerates. In: Capital and Liability Solutions for Life Insurers.

Confidential report

  • Oberoi, J. and Tapadar, P. (2016). International Personal Wealth Flows: A Report on Selected Countries. Not for publication.
  • Alai, D., Oberoi, J. and Tapadar, P. (2016). Review of a Mortality Projection Model. Not for publication.

Monograph

  • Tapadar, P. and Thomas, R. (2017). Why Insurance Works Better With Some Adverse Selection. The Institute of Actuaries of India. Available at: http://www.actuariesindia.org/downloads/souvenir/2017/ActuaryIndiaJuly2017.pdf.
  • Tapadar, P. and Thomas, R. (2017). Appetite for Selection. The Institute and Faculty of Actuaries. Available at: http://www.theactuary.com/features/2017/05/appetite-for-adverse-selection/.
  • Srinivasan, V. and Tapadar, P. (2008). Economic Capital - A Unifying Approach. Incisive Financial Publishing Limited.
  • Tapadar, P. and Porteous, B. (2006). Economic Capital and Financial Risk Management for Financial Services Firms and Conglomerates. The Institute of Actuaries of India.

Other

  • Tapadar, P., Alai, D., Sweeting, P., Oberoi, J. and Wood, N. (2017). Actuarial Teachers and Researchers Conference 2017. [N/A]. Available at: https://blogs.kent.ac.uk/atrc/.
    The annual academic conference affiliated to the Institute and Faculty of Actuaries. The special theme of the conference was Ageing Populations and Actuarial Implications.
  • Andrews, D., Oberoi, J., Rybczynski, K., Tapadar, P. and Wirijanto, T. (2014). Does Population Age Structure Affect Asset Values? Can it be Deflationary?. [N/A]. Available at: https://uwaterloo.ca/statistics-and-actuarial-science/events/university-waterloo-and-university-kent-invite-you-one-day.
    A workshop on age structure and its links to asset prices and inflation was co-organised with the University of Waterloo, with funding from the Society of Actuaries (USA), the University of Waterloo and travel support from the University of Kent. Four distinguished speakers and a panel of three distinguished experts were invited to participate in this event, open to researchers and the public.

Research report (external)

  • Andrews, D., Oberoi, J., Rybczynski, K. and Tapadar, P. (2015). Future Equity Patterns and Baby Boomer Retirements. [Online]. Society of Actuaries. Available at: https://www.soa.org/Research/Research-Projects/Finance-Investment/Future-Equity-Patterns-and-Baby-Boomer-Retirements.aspx#sthash.X9H1Zvuv.dpbs.

Thesis

  • Hao, M. (2017). Insurance Loss Coverage under Restricted Risk Classification.
    Insurers hope to make profit through pooling policies from a large number of individuals. Unless the risk in question is similar for all potential customers, an insurer is exposed to the possibility of adverse selection by attracting only high-risk individuals. To counter this, insurers have traditionally employed underwriting principles, identifying suitable risk factors to subdivide their potential customers into homogeneous risk groups, based on which risk-related premiums can be charged.

    In reality, however, insurers may not have all the information reflecting individuals' risks due to information asymmetry or restrictions on using certain risk factors by regulators. In either case, conventional wisdom suggests that the absence of risk classification in an insurance market is likely to lead to a vicious circle: increasing premium with the prime aim to recover losses from over-subscription by high risks would lead to more low risks dropping out of the market; and eventually leading to a collapse of the whole insurance system, i.e. an adverse selection spiral. However, this concept is difficult to reconcile with the successful operation of many insurance markets, even in the presence of some restrictions on risk classification by regulators.

    Theoretical analysis of polices under asymmetric information began in the 1960s and 1970s (Arrow (1963), Pauly (1974), Rothschild & Stiglitz (1976)), by which time the adverse consequences of information asymmetry had already been widely accepted. However, empirical test results of its presence are mixed and varied by markets.

    Arguably from society's viewpoint, the high risks are those who most need insurance. That is, if the social purpose of insurance is to compensate the population's losses, then insuring high risks contributes more to this purpose than insuring low risks. In this case, restriction on risk classification may be reasonable, otherwise premium for high risks would be too high to be affordable. Thus, the traditional insurers' risk classification practices might be considered as contrary to this social purpose.

    To highlight this issue, ''loss coverage'' was introduced in Thomas (2008) as the expected population losses compensated by insurance. A higher loss coverage indicates that a higher proportion of the population's expected losses can be compensated by insurance. This might be a good result for the population as a whole. A corollary of this concept is that, from a public policy perspective, adverse selection might not always be a bad thing. The author argued that a moderate degree of adverse selection could be negated by the positive influence of loss coverage. Therefore, when analysing the impact of restricting insurance risk classification, loss coverage might be a better measure than adverse selection.

    In this thesis, we model the outcome in an insurance market where a pooled premium is charged as a result of an absence of risk-classification. The outcome is characterised by four quantities: equilibrium premium, adverse selection, loss coverage and social welfare. Social welfare is defined as the total expected utility of individuals (including those who buy insurance and those who do not buy insurance) at a given premium. Using a general family of demand functions (of which iso-elastic demand and negative-exponential demand are examples) with a non-decreasing demand elasticity function with respect to premium, we first analyse the case when low and high risk-groups have the same constant demand elasticity. Then we generalise the results to the case where demand elasticities could be different.

    In general, equilibrium premium and adverse selection increase monotonically with demand elasticity, but loss coverage first increases and then decreases. The results are consistent with the ideas proposed by Thomas (2008, 2009) that loss coverage will be increased if a moderate degree of adverse selection is tolerated. Furthermore, we are able to show that, for iso-elastic demand with equal demand elasticities for high and low risks, social welfare moves in the same direction as loss coverage, i.e. social welfare at pooled premium is higher than at risk-differentiated premiums, when demand elasticity is less than 1. Therefore, we argue that loss coverage may be a better measure than adverse selection to quantify the impact of risk classification scheme being restricted. Moreover, (observable) loss coverage could also be a useful proxy for social welfare, which depends on unobservable utility functions. Therefore, adverse election is not always a bad thing, if demand elasticity is sufficiently low.

    The research findings should add to the wider public policy debate on these issues and provide necessary research insights for informed decision making by actuaries, regulators, policyholders, insurers, policy-makers, capital providers and other stakeholders.
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