Experian has combined the Experian-Scorex credit risk and analytics business with its fraud and identity solutions business to create a new global business line – Experian Decision Analytics.

Experian Decision Analytics will provide better and more integrated services for its clients across the globe, delivering a complete set of proven solutions to tackle credit risk management and fraud challenges throughout the customer life cycle.

Decision analytics is the process of managing and enriching customer data to enable organisations to make the right decisions for each customer, tailored to their individual circumstances, in order to maximise profitability and performance of each relationship. Spanning every aspect of the customer relationship, this includes targeting the right prospective customers and making fast, accurate and consistent decisions about applicants, through to appropriate customer management and reducing losses by quickly identifying higher risk customers for effective collections activity.

Experian's fraud and identity solutions include the market-leading Hunter and Detect credit application fraud services, Authenticate, for the authentication of identities of individuals transacting over the Internet, and anti-money laundering solutions. Experian provides fraud and identity solutions throughout the United Kingdom, Australia, South Africa, Europe and the Asia-Pacific region. Integration of these solutions into Experian Decision Analytics will enable the global business line to expand their availability further into new markets as consumer credit grows in global markets, and to address the strategic risk and fraud challenges faced by lenders in these markets.

Elio Vitucci, Managing Director of Experian Decision Analytics, commented: “Our clients will benefit from the synergies between our fraud and credit risk expertise by having all the tools to manage their customers with just one proven provider of decisioning technology. At the same time, we will be better placed to develop new solutions for the effective management of the complete customer cycle.”

Gary Woods, Managing Director, Fraud and Identity Solutions, Experian Decision Analytics, added: “With fraud a major problem for our clients, Experian Decision Analytics is able to provide the right tools to tackle it and to minimise its impact whilst ensuring that our clients meet their business objectives and make the right decisions for the right customers.”

Experian South Africa's 15th Annual Conference is to be held at Zimbali Lodge, KwaZulu Natal on 19 - 21 September 2007.

Save the date for this year's conference which promises to be an excellent event. We look forward to seeing you there!

The growing opportunity and need for lenders to provide credit products to consumers who ordinarily wouldn't qualify based on traditional scoring methods and cut-offs has lead to the introduction of Delphi for New Markets.

This customer acquisition scorecard has been developed to enable lenders to score the characteristics of this segment differently from the traditional market. Experian will offer this score, to be launched in June 2007, as an alternative to the traditional Delphi score, which has been the flagship of the Delphi product range for over 20 years.

Delphi for New Markets (DNM) is a suite of highly predictive generic bureau scorecards that can be used in any consumer credit application processing environment to assess the credit risk of new market entrants, new portfolios and emerging markets were such segments.

The DNM scoring models are designed to predict the likelihood that a new applicant for credit will become a ‘good' payer, within a higher risk portfolio, if accepted.

The key to their predictive power lies in Experian's:

DNM key features

Key benefits of DNM

Enhanced predictive power

DNM features proven enhanced predictive strength to maximize profitable lending within new markets.

Better decisions

Access to Experian's vast array of data assets and analytics enable you to make the right acquisition decisions to grow your business but at the same time control bad debt, business risk and exposure.

Compliant

DNM has been built taking South African regulatory requirements into account. This means that DNM is fully aligned with the National Credit Act (NCA) and other national regulatory frameworks

Cost effective

As a bureau based service it frees up time and cost associated with the development, implementation and monitoring of custom scorecards.

No degradation over time

Because DNM is regularly updated, your scorecards and quality of decision-making will not deteriorate over time as they would with a custom scorecard development.

Tailored to business requirements

Where needed, additional characteristics can be added for specific organizations or market sectors to ensure the overall scoring solution meets every business requirement.
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It is a challenging time for the South African credit industry - credit providers and bureaux have been working flat out to ensure compliance to the National Credit Act (NCA) by 1 June 2007. The greater challenge, however, is that work is not likely to end there. It is anticipated that the Act will lead to additional and far reaching effects on consumer behaviour, which may, in turn result in further data shifts that will impact the stability of decision processing systems:

1. Section 73 – Data Amnesty

Section 73 of the National Credit Act prescribes that the following data items must be deleted by all registered credit bureaux prior to 1 June 2007:

•  Adverse consumer credit information in respect of debts of less than R500;

•  All consumer credit information relating to dormant accounts (no activity for 24 months)

•  Judgments of value up to R500, except if the consumer has more than 2 judgments on his/her credit record.

•  Judgments of value up to R5 000, older than 18 months except if the consumer has more than 2 judgments on his/her credit record.

•  Judgments of value up to R50 000 if balance has been paid up

These deletions are expected to result in an immediate positive score shift, as shown below in Figure 1.

However, the deletions are intended as a ‘once off' amnesty, which we do not expect will be repeated. This essentially means that the future is not going to be exactly like the past. Since scorecard modeling is developed around the assumption that the future will be like the past it is clear that this will impact scorecard stability, and possibly performance.

We cannot predict exactly what will occur in the months following the amnesty, but we do expect that the volume of adverse and judgment information stored by the bureaux will gradually increase, perhaps to even greater volumes than immediately prior to the amnesty given that South Africa is entering a high base rate cycle. If this does happen, the result will be a gradual negative score shift.

2. Micro Finance Data

The Usury Act, which divided credit agreements into those exempt from Usury (Microloans) and those within Usury (Other agreements) has fallen away, with pricing governed within the NCA regulations. This means that Microloans may become more difficult to identify – which could have far reaching consequences since behaviour on a microloan is generally distinctly different to behaviour on other credit agreements. Lenders will need to monitor the stability and predictive strength of bureau payment profile variables – and make the required adjustments to their scorecards.

3. Consumer Awareness

One of the aims of the act is to increase credit awareness amongst consumers. Lenders will be expected to fully disclose the cost of credit, allowing consumers more of an opportunity to compare prices, and shop for the best deal available to them. For the lender this means that the deal offered to a consumer needs to be competitive, and also may result in a shift in the profile of the population who ultimately accept a credit product. The impact of this would be a scorecard shift (either positive or negative), which could affect the ability of the scorecard to differentiate between good and bad payers.

Although we cannot fully predict the nature and extent of data shifts following the implementation of the NCA on 1 June, we do expect that there will be data instability over time. Scorecard and decision monitoring is therefore going to become essential in order for the lender to ensure that the models in place are operating as expected.

Did you know that 5-20% of your bad debt book could be attributable to first party fraud? This could run into millions of euros and, therefore, even a small reduction in losses could have a major impact on the bottom line. First party fraud is fast becoming the ‘hot topic' of many fraud and credit risk management teams.

‘First party fraud', for the purposes of this article, is customers committing the fraud using either their own or completely false details. Ideally, an organisation could recognise first party fraud by identifying those customers intending not to repay when they take the credit facility. However, intent cannot easily be proved and it is for this reason that many organisations struggle to:

There are several different types of first party fraud, ranging from transactional fraud, such as under-floor limit debit/credit card spending at merchants, through to application fraud when the customer makes an application using false or incorrect details, to sleeper fraud (or bust-out fraud) where a customer sleeps within the customer database, manipulating their account behaviour in order to obtain higher credit facilities and then not repaying.

First party fraud is highly organised crime and detection is difficult due to the fact that there is no third party victim (apart from the financial organisation) to tell you that a fraud has occurred. This also affects an organisation's ability to clearly define and spilt bad debt losses into can't pay versus won't pay and thus easily be able to build detection tools.

Commercial challenges resulting from first party fraud present some tough decisions for organisations, of which the two most important are:

There are many considerations that a financial organisation will need to address if it is going to successfully reduce first party fraud losses. Organisations in the UK and the US have started to recognise and address this emerging trend in the last few years. However, there is no doubt that this is becoming a global problem, which continues to grow. Whilst there are different mitigating strategies and processes that institutions can implement, the key step has to be for organisations to collaborate across the industry to align their first party fraud definition and share data.

Exciting opportunities currently available at Experian: Infrastructure Manager - This person will report to the IT Manager and is responsible for managing the day to day operations of the Experian Bureau processing environment including (but not limited to) infrastructure (both logical and physical), network connectivity, client expectations and service level agreements. Click here for more information.

Account Manager - The Account Manager is responsible for managing mid to high value clients as part of the Experian Account Management Team. The Account Manager is responsible for building and maintaining deep relationships with Experian's clients. This role is responsible for ongoing account management, revenue generation and client satisfaction including understanding the client's needs to identify opportunities for strategic services. Click here for more information.

Project Manager - Planning, initiation, monitoring and control of projects to deliver quality products/services within budget and on time. Management of delivery procedures, software version control and release procedures. Management of third parties involved in the technical delivery of software solutions. Click here for more information.

To view all Experian's job vacancies please click here