The area of credit scoring is one that deals with large amounts of data and mathematical modelling processes. The discussion on legal implications of credit scoring has centred, in recent times, on regulatory compliance specified by the Basel II Accord, and the legality of certain types of information found in variables used in the modelling of credit scorecards.
Business School academician Wen Li Chan (Assistant Professor of Business Law) recently presented a paper at the 12th Credit Scoring and Credit Control Conference at the University of Edinburgh, UK, that relooks at the legal concerns pertaining to the use of variables that are typically excluded from modelling due to perceived illegality pursuant to anti-discrimination laws. It argues that, in attempts to comply with anti-discrimination laws, current measures in modelling do not allow for the most effective use of credit scoring models, and at times run counter-intuitive to the intention of legislation by giving rise to indirect discrimination. The paper discussed anti-discrimination laws in the UK and US, and suggested a wider interpretation of the laws pertaining to equal access to credit that promotes equal treatment of credit applicants while retaining the integrity and effectiveness of credit scoring models.
The presentation, co-authored with Hsin-Vonn Seow (Associate Professor of Operations Research) drew much interest at the conference, particularly in light of the new Equality Act 2010 in the UK and a recent ruling of the European Court of Justice that taking the gender of an insured individual into account as a risk factor in insurance contracts constitutes discrimination. The paper, entitled "Legally Scored", was shortlisted for the Best Paper Award.
The biennial Credit Scoring and Credit Control Conference, organised by the Credit Research Centre at the University of Edinburgh, is the main conference in Europe for credit scoring, credit control and related topics, and aims to bridge the academic-practitioner divide by featuring presentations ranging from current industry issues to the latest statistical research findings.
Wen Li Chan is Assistant Professor of Business Law at Nottingham University Business School Malaysia. Her research interests currently relate to legal issues in data mining and credit scoring, including issues of data privacy and anti-discrimination laws. She has conducted research on the roles and implications of information on shareholder wealth in the areas of corporate litigation, corporate social responsibility (CSR) and corporate governance, and has published in the Journal of Business Ethics on the impact of product recalls on CSR and firm performance. Wen Li is currently a Co-Deputy Director of the Business School's MBA programme.
Hsin-Vonn Seow is Associate Professor of Operations Research and Director of the PhD programme in Nottingham University Business School at the University of Nottingham Malaysia Campus. Her current research interests include looking at applications of management science techniques in finance and banking with strong interest in credit scoring and credit control, interactive application channels (internet and telephone banking) for financial products and data mining. Hsin-Vonn is currently a member of the Operational Research Society UK. She is a referee for the European Journal of Operational Research and for the Journal of the Operational Research Society. She is also an alumni of the EURO Summer Institute (Optimization and Data Mining, Turkey 2004).
Posted on 8th March 2012