Pradip Tapadar

Economic Capital and Financial Risk Management for Financial Services Firms and Conglomerates

Preface. Introduction Risk Types, Collection and Mitigation Risk Governance Stress Testing to Measure Risk Economic Capital Types of Capital The Stochastic Model Economic Capital for Banks Economic Capital for Non Profit Life Insurance Firms and General Insurance Firms Economic Capital for Asset Management Firms Economic Capital for With Profits Life Insurance and Pension Funds Financial Services Conglomerates Capital Management and Performance Measurement in Practice Regulatory Change Summary and Conclusions References Appendices

Multifactorial Genetic Disorders and Adverse Selection: Epidemiology Meets Economics

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.

The Impact of Capital Structure on Economic Capital and Risk Adjusted Performance

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.

The Impact of Multifactorial Genetic Disorders on Critical Illness Insurance: A Simulation Study Based on UK Biobank

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.

Asset Allocation to Optimise Life Insurance Annuity Firm Economic Capital and Risk Adjusted Performance

ABSTRACT 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.

Economic capital for defined benefit pension schemes: An application to the UK Universities Superannuation Scheme

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.

Types of Capital

In this chapter we describe the role of capital and also discuss the different types of capital that are available to financial services firms to cover their regulatory capital requirements. The discussion is based on a banking model as, at least in the UK, this is the model that has recently been adopted by other types of financial services firms.

The Stochastic Model

As stated in Chapters 4 and 5, our preferred approach in this book is to determine economic capital using a stochastic, rather than a deterministic, approach wherever possible. This chapter develops a stochastic model that is effectively the engine that generates our stochastic stresses.

Role of the Pension Protection Fund in financial risk management of UK defined benefit pension sector: a multi-period economic capital study

Abstract 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.

Insurance loss coverage and social welfare

ABSTRACT 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 the economic literature on risk classification. For iso-elastic insurance demand, ranking risk classification schemes by (observable) loss coverage always give the same ordering as ranking by (unobservable) social welfare.