Credit Bureau Scores are statistically-derived measures of consumer creditworthiness, calculated dynamically and incorporating the most recent and relevant credit information available for an individual in the bureau’s databases.

Based on very large data samples taken from across the credit industry rather than that of a single lender, the scores are developed by analytics experts and predict the future payment performance of each consumer. These are typically known as ‘ generic’ Credit Bureau Scores , and generally encompass the following main characteristics:

1. Public information, such as bankruptcies and court judgments
2. Default information on previous credit agreements
3. Historical payment performance on on-going credit agreements
4. Credit limit utilisation on revolving credit agreements
5. The number and value of on-going credit agreements
6. The number and value of recent applications for credit
7. Identity confirmation information, such as an on-line Voters Roll or telephone directory check.

Credit Bureau Scores are now a fundamental part of many financial services organisations’ decision support tools for credit risk management.  Firstly, in new business decision-making, where the majority of lenders use their own credit origination scorecards in making accept and decline decisions, and setting credit limits and interest rates on new applications for credit. These models often have a Credit Bureau Score as their basis, along with scores for an applicant’s age and residential status, for example.  Secondly, in risk management of existing customers, many lenders also combine Credit Bureau Scores with existing customer and account performance in the development of their behavioural scorecards, which are widely used in setting credit limits, assigning collections actions to delinquent accounts and for excluding high risk customers from further marketing activities. Finally, Credit Bureau Scores are also used for pre-screening of new prospects, excluding high-risk individuals from the direct mail and telemarketing campaigns that can be used in some countries, to acquire new customers. 

Although the Capital Requirements Directive explicitly intends that IRB processes be based predominantly on internal ratings, national supervisors generally encourage the use of external data and/or vendor models. For many years, the financial industry has been using Credit Bureau Scores in order to optimise decision-making and credit risk management in the retail sectors. And, as long as it can be demonstrated that they add significant predictive power, retail banks can now use Credit Bureau Scores as a key component of their IRB processes, both for consumers and SMEs.

So, why are Credit Bureau Scores used?

When used in origination scorecards, the Credit Bureau Score is generally by far the best predictor of future credit risk.  This is particularly the case in markets like the UK and the US that have ‘full’ data sharing, where the overall score contribution from the application form information is typically much less than that of the Credit Bureau Score.  As well as providing an accurate measure of creditworthiness, the Credit Bureau Score has the added advantage that it can be relied on as ‘fact’, unlike the personal details supplied on an application form that can sometimes be manipulated.

The case for using Credit Bureau Scores in behavioural scorecards, although not as strong, is usually still compelling.  Because an increasing number of consumers and SMEs have credit accounts with several financial organisations at the same time, a single organisation rarely has a complete view of an individual’s overall indebtedness and creditworthiness.  To complete this picture, many lenders, particularly those providing revolving credit facilities, have taken the step of incorporating an up-to-date Credit Bureau Score into their customer or account behavioural scorecards.

Credit Bureau Scores are re-developed regularly, in order to include the very latest credit bureau data and data legislation. For this reason, there is no better source of information on which to base critical decisions, and formulate strategies for customers, new or existing.

Simon Harben - SVP, Global Analytics, Experian Decision Analytics

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