Legally scored
| Date | 15 February 2013 |
| DOI | https://doi.org/10.1108/13581981311297812 |
| Pages | 39-50 |
| Published date | 15 February 2013 |
| Author | Wen Li Chan,Hsin‐Vonn Seow |
| Subject Matter | Accounting & finance |
Legally scored
Wen Li Chan and Hsin-Vonn Seow
Nottingham University Business School,
University of Nottingham Malaysia Campus, Semenyih, Malaysia
Abstract
Purpose – Achieving equal treatment of credit applicants has been a legitimate concern of legislators
and the credit industry. However, measures taken to date in attempting to comply with
anti-discrimination laws arguably do not allow for the most effective use of credit scoring models, and
could run counter-intuitive to the intention of legislation through indirect discrimination. The purpose
of this paper is to offer an alternative interpretation that preserves the intention of legislation and also
retains the integrity and effectiveness of credit scoring models.
Design/methodology/approach – The paper makes a legal analysis of anti-discrimination laws in
the UK, with US law as a comparison, aiming to demonstrate that concerns in using information
protected under anti-discrimination laws as variables may be misplaced, because nothing in these laws
precludes the inclusion of all relevant variables in modelling.
Findings – The inclusion of variables representing protected characteristics in credit scoring models
may not contradict current anti-discrimination laws.
Research limitations/implications – Limitations exist from the perspectives of customer
relationship and the need for further checks and balances. Conclusive validation of the findings will
need to come from the courts. The paper provides a springboard for empirical research on whether the
inclusion of variables representing protected characteristics in credit scorecards continues to produce
better decision-making models.
Practical implications – The findings benefit credit risk modelling as a whole in facilitating the
development of credit scorecards that are in compliance with anti-discrimination laws, without
sacrificing their effectiveness.
Originality/value – The paper presents a fresh perspective and alternative solution to legal
concerns regarding the use of protected characteristics in credit scoring, which will be useful to the
credit industry.
Keywords Credit, Legislation,Credit scoring models,Credit risk, Anti-discriminationlaws, Data issues
Paper type Research paper
1. Introduction
The business of credit scorecard development deals with a large amount of data,
distilled into a predictive model used in the risk adjudication process through which
credit-granting institutions hope to be able to minimise the denial of credit to
creditworthycustomers while excluding as many potentially delinquent ones as possible.
The classification models used to develop credit scorecards are derived based on
consumer information, and consumer data on credit risk invariably comes with some
strings attached – in the form of legalregulation, safeguards and restrictions. Much focus
has been given in recentyears on regulatory compliance specified by the Basel Committee
on Banking Supervision in the form of the Basel II Accord that sets out the level of capital
banks must maintain to support their lending, and encourages banks to use internal
credit scoring systems. Another area with significant implications on credit scoring,
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1358-1988.htm
The authors wish to thank members of the Credit Scoring and Credit Control XII Conference,
Edinburgh, UK, for their helpful comments and valuable insights.
Legally scored
39
Journal of Financial Regulation and
Compliance
Vol. 21 No. 1, 2013
pp. 39-50
qEmerald Group Publishing Limited
1358-1988
DOI 10.1108/13581981311297812
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