Improving regulatory capital allocation: a case for the internal ratings-based approach for retail credit risk exposures

Purpose The purpose of this study is to demonstrate that the internal ratings-based (IRB) approach provides more effective risk discrimination than the standardized approach when calculating regulatory capital for retail credit risk exposures. Design/methodology/approach The author uses four retail credit data sets to compare regulatory capital appropriation using the IRB approach and the standardized approach. The author follows the regulatory capital calculation method recommended under Basel III. For the IRB approach, the author uses a logistic regression to determine the probability of default. Findings The results suggest that the IRB approach provides more effective risk discrimination across individual exposures, which allows more regulatory capital to be held against riskier exposures and less regulatory capital to be held against less risky exposures. The author further argues that the Basel III output floor, as presently constructed, may disincentivize the use of the IRB approach and further diminish the value of secured lending under the IRB approach. To address this issue, the author offers two simple adjustments to the current design of the output floor. Originality/value While studies have argued the idea of risk-sensitive regulatory capital, the author has not observed any research that empirically compares the risk-sensitivity of regulatory capital across retail credit exposures, which makes up a significant portion of many banks’ credit exposures. This study also highlights what appears to be a major point of concern for the output floor, which is set to be phased in starting January 2022. This is of particular value because this point has not appeared to receive any attention in the literature thus far.

Irradiance Restoration Based Shadow Compensation Approach for High Resolution Multispectral Satellite Remote Sensing Images

Numerous applications are hindered by shadows in high resolution satellite remote sensing images, like image classification, target recognition and change detection. In order to improve remote sensing image utilization, significant importance appears for restoring surface feature information under shadow regions. Problems inevitably occur for current shadow compensation methods in processing high resolution multispectral satellite remote sensing images, such as color distortion of compensated shadow and interference of non-shadow. In this study, to further settle these problems, we analyzed the surface irradiance of both shadow and non-shadow areas based on a satellite sensor imaging mechanism and radiative transfer theory, and finally develop an irradiance restoration based (IRB) shadow compensation approach under the assumption that the shadow area owns the same irradiance to the nearby non-shadow area containing the same type features. To validate the performance of the proposed IRB approach for shadow compensation, we tested numerous images of WorldView-2 and WorldView-3 acquired at different sites and times. We particularly evaluated the shadow compensation performance of the proposed IRB approach by qualitative visual sense comparison and quantitative assessment with two WorldView-3 test images of Tripoli, Libya. The resulting images automatically produced by our IRB method deliver a good visual sense and relatively low relative root mean square error (rRMSE) values. Experimental results show that the proposed IRB shadow compensation approach can not only compensate information of surface features in shadow areas both effectively and automatically, but can also well preserve information of objects in non-shadow regions for high resolution multispectral satellite remote sensing images.

The conflict of interests of economic entities and to minimize its consequences by reducing the risks of corporate lending

This article is devoted to the construction of a risk-oriented model of credit risk reduction in the course of the life cycle of the loan in the provision of a commercial Bank loan to a corporate client. The work demonstrates, firstly, the need to introduce innovative solutions that reduce the risk of non-repayment of the loan by the borrower, and secondly — the mechanism of using such elements of the model as a new system of limits and risk profiles, the Institute of underwriting, IRB-approach to determine the risk category of the application and the body authorized to make.

Part II Commercial Banking, 10 The Internal Ratings-Based Approach

This chapter discusses the internal ratings-based approach (IRB). The IRB permits a bank to use its internal models to derive risk weights for particular exposures. There are two available bases for the IRB: foundation (F-IRB), which permits the bank to model Probability of Default (PD), but relies on regulatory standard figures to determine Loss Given Default (LGD) and Exposure at Default (EAD); and advanced (A-IRB), in which all three of these are modelled. The A-IRB IRB approach models PD, LGD, EAD, and M. Both IRB approaches model both expected loss (EL) and unexpected loss (UL), and IRB banks are expected to recognise the EL derived from their models in their capital calculations. Consequently, a bank using an IRB approach will generally have a different total capital level from that which it would have if it were an SA bank.

Defining the probability of bank debtors’ default using financial solvency assessment models

Due implementation of debtors’ financial solvency assessment models by Ukrainian banks with the aim of calculating the probability of their default (PD) is the next step towards the integration of Ukrainian banking system into global banking community, convergence of methodical approaches to assessing the credit risk with standards of international practice, possibility of using IRB-approach (an approach based on internal ratings) for calculating the regulatory requirements to capital adequacy.The analysis of approaches to bank credit portfolio segmentation according to types of debtors and debtors’ financial solvency assessment models, depending on the performed segmentation and accumulated bank statistical data, from the point of view of its suitability for Ukrainian banks, will enable the banks to choose the most suitable ones for implementation taking into account nature and complexity of operations performed.Such approaches will be more adapted to minimum capital requirements, simultaneously agreeing with national supervisory priorities.

A Critical Review Of The Basel Margin Of Conservatism Requirement In A Retail Credit Context

The Basel II accord (2006) includes guidelines to financial institutions for the estimation of regulatory capital (RC) for retail credit risk. Under the advanced Internal Ratings Based (IRB) approach, the formula suggested for calculating RC is based on the Asymptotic Risk Factor (ASRF) model, which assumes that a borrower will default if the value of its assets were to fall below the value of its debts. The primary inputs needed in this formula are estimates of probability of default (PD), loss given default (LGD) and exposure at default (EAD). Banks for whom usage of the advanced IRB approach have been approved usually obtain these estimates from complex models developed in-house. Basel II recognises that estimates of PDs, LGDs, and EADs are likely to involve unpredictable errors, and then states that, in order to avoid over-optimism, a bank must add to its estimates a margin of conservatism (MoC) that is related to the likely range of errors. Basel II also requires several other measures of conservatism that have to be incorporated. These conservatism requirements lead to confusion among banks and regulators as to what exactly is required as far as a margin of conservatism is concerned. In this paper, we discuss the ASRF model and its shortcomings, as well as Basel II conservatism requirements. We study the MoC concept and review possible approaches for its implementation. Our overall objective is to highlight certain issues regarding shortcomings inherent to a pervasively used model to bank practitioners and regulators and to potentially offer a less confusing interpretation of the MoC concept.