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Currently, banks, securities firms, and insurance companies conduct trading businesses that involve many of the same financial instruments and several of the same counterparties but that are subject to very different capital regulations. This chapter examines why these regulatory differences exist and what they imply for differences in minimum capital requirements for position risk. It considers differences in the definition and measurement of regulatory capital, and quantifies differences in the capital charges for position risk by reference to a model portfolio that contains a variety of financial instruments, including equity, fixed income instruments, swaps, foreign exchange positions, and options — instruments that may appear in the portfolios of securities firms, banks, or insurance companies. For most leading firms in the financial services industry, however, market forces, not minimum regulatory capital requirements, appear to play the dominant role in firms' capital decisions. The chapter concludes by considering measures to enhance market discipline.

The previous chapters in the book have concentrated on modelling decisions and uncertainties on one consumer loan. This chapter concentrates on models related to portfolios of such loans. In particular it looks at the economic capital and regulatory capital needed to cope with the credit risk in a portfolio of consumer loans. It concentrates on how the Basel Capital Accord, in place since 2007, impacts on credit scoring and is in turn dependent on credit scoring. The chapter reviews what the Accord requires and how the minimum capital requirement formula can be derived. It then looks at the impact it has on credit scoring with the increased importance in validating the prediction probabilities of the default scores, and the need to calculate long run average probability of default rates from credit scores. Models are developed to show how the Basel regulations will change the optimal cut-off scores in the application process. The various portfolio credit risk models for corporate loans and whether there are equivalent models appropriate for assessing the credit risk for portfolios of consumer loans are discussed. These are useful for stress testing as required in the Basel Accord.

This chapter employs data supplied by six large, internationally active banks to identify if the regularities in the loss data will make consistent modeling of operational losses possible. It is noted that operational risk is a material risk faced by financial institutions. The data indicate that it may be difficult to fit parametric loss-severity distributions over the entire range of loss amounts, even if separate analyses are conducted for each business line and event type. Loss-severity distributions at the six banks under consideration have tail indexes ranging between 0.50 and 0.86. Assuming a Pareto severity distribution yielded capital estimates that were broadly consistent with the Basel Committee's expectation that operational risk accounts for 12 percent of minimum regulatory capital. As banks obtain three or more years of good operational loss data, the ability to differentiate across alternative distributional assumptions should improve.