RISIKO MANAGER 10.2019

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6 RISIKO MANAGER 10|2019 ECB requirements for credit risk models Inspection techniques for data quality The European Central Bank (ECB) will perform a Targeted Review of Internal Models (TRIM) with the objective of reducing the variability in Risk-Weighted Assets (RWA). This will be accomplished by harmonizing practices and checking the compliance of Pillar 1 internal models of credit risk (CR), market risk (MR) and counterparty credit risk (CCR) with regular requirements. The objective is to reduce the variability in risk-weighted assets RWAs by harmonizing practices and checking the compliance of Pillar 1 internal models for credit risk (CR), market risk (MR) and counterparty credit risk (CCR) with regulatory requirements. The article will critically assess the collection and storage stages of data used for probability of default PD and loss given default LGD estimation, covering a selection of mandatory key variables and also allowing for additional tests to be performed. Specific attention will be paid to the different core banking systems and data sources that are used through to the (historical) risk database identified in the inspection. Even though the fact that the IT architecture and infrastructure for the credit rating systems are mode-specific, a simplified process will be outlined throughout the article to illustrate the main process steps, systems, and datasets. The focal point of the article revolves around retail and corporate small medium enterprises SME portfolios, including information based on personal experiences of the author. Introduction TRIM addresses two specific aspects appertaining to the compliance of internal models with regulatory requirements. An assessment is required based on the Capital Requirements Regulation (CRR) [see EBA 2013a], the Capital Requirements Directive (CRD IV) [see EBA 2013b], relevant Commission Delegated and Implementing Regulations, regulatory technical standards (RTS), European Banking Authority (EBA) guidelines and the approved European Central Bank (ECB) Banking Supervision guidelines. The assessment hopes to fulfil the obligations of the ECB banking supervision to ensure equal treatment of credit banks and the supervisory assessment and approval of internal models ([see ECB (2017)]: SSM supervisory priorities). It aims to reduce the unwarranted variability in RWA as it relates to internal models outcomes considering the results of benchmarking, delivering interpretations of the CRR and addressing gaps in the interpretation of regulations relating to internal models. In this article, I will focus on experiences and critical analysis drawn from closer inspection of credit risk models and the parameters’ probability of default PD and LGD. The article draws a map of the databases. All relevant sources of data, relevant processes of data extraction and transformation, relevant functional and technical specification of databases, data models, relevant work-flows and procedures relating to data collection and data storage will be analysed and the items will be fully documented. Literature overview According to Montgomery (2009) the modem definition of quality, „Quality is inversely proportional to variability“, implies that product quality increases as variability in important product characteristics decrease. Quality improvement can then be defined as the reduction of variability in processes and products. In his Introduction

Kreditrisiko 7 Tab. 01 The different ECB guidelines* Regulation (EU) 2013 of the European Parliament and of the Council of 26 June 2013 on prudential requirements for credit institutions and investment firms and amending Regulation (EU) No 648/2012 Directive 2013/36/EU of the European Parliament and of the Council of 26 June 2013 on access to the activity of credit institutions and the prudential supervision of credit institutions and investment firms Document “Minimum capital requirements for market risk” issued by the Basel Committee on Banking Supervision (BCBS) http//www.bis.org/bcbs/ publ/d352 pdf Quelle: * see ECB (2016a), (2016b), (2017a), (2017b). (OJ L 176, 27.6.2013, p. 1) (OJ L 176, 27.6.2013 , p. 338) January 2016 EBA Consultation paper on Guidelines on PD estimation, LGD estimation and the treatment of defaulted exposures 14 November 2016 CRO 3(1) 7, 9, 11 26/06/2013 CRR 175, 185, 189, 190, 191,288 30/11/2013 Final Draft RTS on assessment methodology for IRB 21/07/2016 Final Draft RTS on assessment methodology for IMA and significant shares 22/11/2016 Guidelines on common procedures and methodologies for the supervisory review and evaluation process (SREP) (EBA/GU2014/13) to Statistical Quality Control [see Montgomery (2009)] Montgomery presents methods applicable in the key areas of process control, design of experiments, and acceptance sampling. To understand the potential for application of statistical methods, a credit risk model is assumed to be a „black box“. The output of this black box is a product whose quality is defined by one or more quality characteristics that represent dimensions such as conformance to standards, performance, or reliability. Product quality can be evaluated with acceptance sampling plans. These plans are typically applied to the output of a process or the input data. Application of process control techniques (such as control charts) or statistically designed experiments can achieve a significant reduction in variability. Whether or not controllable and uncontrollable inputs are significant can be determined through process characterization. Statistically designed experiments are extremely helpful in characterizing processes and optimizing the relationship between incoming data and process variables. The statistical methods presented in this text are well established in scientific the literature and were applied to financial transactions and services. An overview of statistical tests can be found in [Morgan and Lock (2013)] Statistics unlocking the power of data and [Quatmember (2015)] Datenqualität in Stichprobenerhebungen: Eine verstandnisorientierte Einführung in Stichprobenverfahren Fig. 01 Compliance with Regulatory standards Definition of a guide for TRIM Improvement of internal models‘ supervision Adequate capital requirements Stages of the inspection und verwandte Themen. In the marketing field, there exist substantial literature on quality control, e.g. [Berry (2004)] Data mining techniques for marketing sales and customer support. Especially on data mining, the literature has grown rapidly in recent years. Principles of Data Mining [see Hand et al (2001)] provides an introduction to the wide range of algorithms and methodologies in this area. [Hammergren and Simon (2009)] in Data Warehousing for Dummies analyse top-down and bottom-up data warehouse design. [Han and Kamber (2005)] in Data mining: Concepts and techniques describe applications and trends in data mining. [Ott and Objective: To enhance the credibility and confirm adequacy and appropriateness of approved Pillar I internal models. TRIM will ... assess the reliability and comparability of internal rating systems and models permitted for capital requiremnents with a view to ensure compliance with regulatory requirements and harmonise supervisory practices. communicate a guide with harmonised principles and make recommendations to institutions contribute to improve the future supervisory work on internal models enhancing the internal models expertise verify whether risks are modelled correctly and hence capital requirements are calculated adequately.