Basel regulatory capital formula revised

Credit capital requirement is a key component of Basel implementation to assess a bank’s capital adequacy. Under the Internal Rating-Based approach, some risk parameters, including Asset Correlation, are implicit assumptions that cannot be observed directly. While some heuristic formulae of Asset Correlation for different business segments are provided by Basel, they may not be fully consistent with each bank’s loss experience and thus may cause systematic underestimation of banks’ capital requirement. To address this issue, we derive an equivalent capital formula in such way that the unobservable Asset Correlation is replaced by an observable and well-understood parameter called Default Volatility, which can be calibrated based on banks’ historical loss experience. This new approach simplifies parameter estimation process without requiring additional data, as well as making risk analysis such as stress testing more credible.

Modeling Recoveries of US Leading Banks Based on Publicly Disclosed Data

The credit risk management process is a critical element that allows financial institutions to withstand economic downturns. Unlike the methods regarding the probability of default, which have been deeply addressed after the financial crisis in 2008, recovery rate models still need further development. As there are no industry standards, leading banks are modeling recovery rates using internal models developed with different assumptions. Therefore, the outcomes are often incomparable and may lead to confusion. The author presents the concept of a unified recovery rate analysis for US banks. He uses data derived from FR Y-9C reports disclosed by the Federal Reserve Bank of Chicago. Based on the historical recoveries and credit portfolio book values, the author examines the distribution function of recoveries. The research refers to a credit card portfolio and covers nine leading US banks. The author leveraged Vasicek’s one-factor model with the asset correlation parameter and implemented it for recovery rate analysis. This experiment revealed that the estimated latent correlation ranges from 0.2% to 1.5% within the examined portfolios. They are large enough to impact the recovery rate volatility and cannot be treated as negligible. It was shown that the presented method could be applied under US Comprehensive Capital Analysis and Review exercise.

What is good and bad with the regulation supporting the SME’s credit access

Purpose This analysis asks whether regulatory capital requirements capture differences in systematic risk for large firms and micro-, small- and medium-sized enterprises (MSMEs). The authors explore whether bank capital regulations intended to support SMEs’ access to borrowing are effective. The purpose of this paper is to find out whether the regulatory design (particularly the estimate of asset correlations) positively affects the lending process to small and medium enterprises, compared to large corporates. Design/methodology/approach The authors investigate the appropriateness of bank capital requirements considering default risk of loans to MSMEs and distortions in capital charges between MSMEs and large firms under the Basel III framework. The authors compiled firm-level data to capture the proportions of MSMEs and large firms in Italy during 2000–2014. The data set is drawn from financial reports of 708,041 firms over 15 years. Unlike most empirical studies that correlate assets and defaults, this study assesses a firm’s creditworthiness not by agency ratings or by sampling banks but by a specific model to estimate one-year probabilities of default. Findings The authors found that asset correlations increase with firms’ size and that large firms face considerably greater systematic risk than MSMEs. However, the empirical values are much lower than regulatory values. Moreover, when the authors focused on the MSME segment, systematic risk is rather stable and varies significantly with turnover. This analysis showed that the regulatory supporting factor represents a valuable attempt to treat MSME loans more fairly with respect to banks’ capital requirements. Basel III-internal ratings-based approach results show that when the supporting factor is applied, the Risk-Weighted-Assets (RWA) differences between MSMEs and large firms increase. Research limitations/implications The implications of this research is that banking regulators to make MSMEs support more effective should review asset correlation estimation criteria, refining the fitting with empirical evidence. Practical implications The asset correlation parameter stipulated by the Basel framework is invariant with economic cycles, decreases with borrowers’ probability of default and increases with borrowers’ assets. The authors found that those relations do not hold. This way, asset correlations fall below parameters defined by regulatory formula, and SMEs’ credit risk could be overstated, resulting in a capital crunch. Originality/value The original contribution of this paper is to demonstrate that the gap between empirical and regulatory capital charge remains high. When the authors examined the Basel III-IRBA, results showed that when the supporting factor is applied, the RWA differences between MSMEs and large firms increase. This is particularly strong for loans to small- and medium-sized companies. Correctly calibrating asset correlations associated with the supporting factor eliminates regulatory distortions, reducing the gap in capital charges between loans to large corporate and MSMEs.

A novel insurance system for associated loans: the realization of reducing bankruptcy cost

Purpose The assets of bankrupt firms are usually sold to unsuitable buyers at an extremely discounted price. Aiming to reduce the bankruptcy cost, the purpose of this paper is to propose a novel insurance system for associated loans. Design/methodology/approach In this insurance system, the joined firms are from the same industry and have a responsibility to buy the assets of potentially bankrupt firms at a relatively high price, because they could make better use of the assets than the buyers outside the industry. Further, the authors use the Shapley value to address the problem of bankruptcy cost allocation and additionally employ the method of Monte Carlo simulation to derive the numerical solution of the insurance premium of bankruptcy cost. Findings First, the relatively healthy and solvent firms in the insurance system could gain a larger proportion of benefits derived from the reduced cost of default, interestingly, the more so when the external cost of default is larger. Second, given the positive relationship between bankruptcy cost and asset correlation in practice, lenders and insurers face a trade-off to balance the cost against the benefit of asset correlation. Third, insurance premiums and bankruptcy costs decrease with the number of firms participating in this insurance system. Originality/value This paper proposes a novel insurance for associated loans, in which joined firms can pay a relatively low insurance premium due to the realization of reducing bankruptcy cost.