| Sharing credit data – the benefits 1 |
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| Monday, 08 November 2010 00:00 |
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This article discusses the benefits to credit grantors who begin sharing data. The article follows on from the previous article, ‘Sharing Credit Data – The Concepts’ which explained the general history and practice of credit data sharing, illustrated with examples specific to South Africa. Credit Data Sharing – An Overview For credit grantors, effective management of customer information is a critical business task. This ranges from the gathering of data found on account application forms, to utilising the ongoing performance information available on existing client portfolios. The correct handling of these data rich environments often determines whether the business remains competitive and successful. In recent years, credit granting organisations have also realised that internal information sources can be supplemented with the value that comes from exchanging data with other businesses. In a South African context, a good example of this was the recognition by several leading retailers some years back that they jointly had at their disposal a pool of untapped consumer information. By grouping this centrally, using credit bureaux to hold the data, a large database of shared information became available. In particular, the data contributors focused on submitting monthly information as to how customers conducted accounts held with each organisation. This data, commonly known as the payment profile history, includes the following: •Date the account was opened •Organisation where the account is held •Type of account i.e. revolving, instalment •Account opening balance •Account current balance •The total value of all outstanding amounts – the ‘balance versus burden’ •Calendar month the account was last updated at the credit bureaux •24 monthly entries from the most recent to the least recent month – a series of alpha and numeric characters indicating the account status for a given month The benefits of sharing this type of information are quickly identifiable. For example, when reviewing account applications the credit grantor can reference the payment profile history, ask specific questions, and apply policy rules. This is helpful when reviewing or processing ‘marginal’ account applications. Questions might include: •Has this person disclosed all relevant account information on their application form? Are there other accounts not mentioned? If so, why? •Are the outstanding amounts on other accounts accurately disclosed? Answering this enables the credit grantor to better determine the applicant’s current debt burden and provide guidelines in the accept/ decline decision, as well as the appropriate limit assignment. •Is the applicant only providing information on those accounts that are conducted well, i.e. the ‘best three’ scenario? Trends ascertained provide insight on all historical account behaviour and performance. Applicant Verification There are substantial benefits when looking at a shared ‘bigger picture’ for each applicant. Combined databases assist when it comes to applicant verification and confirmation from an independent, co-managed data source. Verification differs from organisation to organisation, although the more common aspects of confirmation include the applicant’s identity number, address and contact information, personal references, and employment or bank account details. With high-risk applications, verification becomes more intensive and laboured, making processing of these accounts slower - not ideal in the time sensitive credit granting environment. Increased response times impact customer service response levels; any reduction in the confirmation process directly affects the level of service customer representatives can offer. An example of a recent verification initiative in South Africa is the idea of sharing employment details within a closed user group. This can be either information on the company’s own employees, or consumer employment information already verified by that company. Making this data available to other contributors in a controlled and properly audited manner theoretically reduces the time and effort required with subsequent verifications. Details stored could include employee number, a human resource department reference, position held, or date of last verification. Larger contributors, by their very nature, will tend to provide more information than smaller organisations in the user group. By charging a ‘fee per view,’ the data contributor receives some degree of financial return without subsidizing smaller users. The general benefits of reducing verification procedures include: •A faster turnaround time on application review, which is critical in time sensitive credit processing environments. •Improved utilisation of staff and better business resource allocation. For example, minimising the confi rmation steps reduces operating costs and allows staff to prioritise good quality prospects, whilst also managing higher risk applicants. •Reduce the false-positive rate. This is the phenomenon where underwriters investigate suspected fraudulent applications, only to have these subsequently turn out to be genuine consumers. Naturally, this affects the level of customer service given to the individual, and ties up staff resources unnecessarily. Fraud – A Common Problem The danger of fraud is a universal challenge for practically all credit grantors. Sharing credit data is one way of offsetting the potential for fraud, but usually this only takes place effectively once the industry sector jointly acknowledges the problem. Data sharing examples here include monitoring the number of credit applications made by an individual at different credit grantors over a specified time period. Alternatively, velocity analysis of address or personal reference information. An applicant with frequent address changes on application forms warrants closer scrutiny. Through data sharing arrangements, contributors can alert one another to the existence of fraud syndicates, front companies, fake personal references and a host of other fraudulent activities. Deeper analysis of the data may also reveal fraud patterns, helping the database administrator or fraud investigator to uncover hidden meaning in the data and better pinpoint possible warning signs. Other options would be to build up an events sequence or analyse transaction patterns, in so doing creating a proactive monitoring tool or response system. When it comes to the issue of fraud, the benefits of data sharing are not limited to credit grantors only. South Africa recently saw the introduction of a shared database for the insurance industry. The database, known as the Insurance Data System (IDS), is a repository of information relating to short term insurance claims. The database includes individual claim histories, a log of transactions from service providers and product suppliers to the insurance industry, and compiled reports from damage and loss assessors. The IDS came about after the industry as a whole acknowledged that insurance fraud was spiralling out of control with an estimated 30% of all short term insurance claims being false.* The main aim of the database is therefore to prevent collusion between suppliers and claimants, and make it harder for consumers to file bogus claims or switch frequently between insurers. Clearly, this industry sector has accepted that despite their individual competitiveness and business concerns, there is greater benefit to be generated from sharing claims information as opposed to not doing so. Shared Data – Dynamic and Expanding Where a number of organisations are contributing data, the shared database expands in a dynamic and fluid manner. This constant growth leads to a deepening of the data available for reference and analysis. A ‘bigger picture’ resource is invaluable for a number of reasons: •Data can be used to develop continually improved modelling, analysis and general risk tools. As the database widens to include other contributors in the industry, or totally new industry sectors, so each consumer profile takes on deeper meaning. In sophisticated economies, contributed data may include information on a wide range of activities from information on personal banking habits and retail account behaviour, to loan obligations, and instalment arrangements. •Apart from better managing the risk associated with each customer, organisations that have access to wider information are also in a position to refine and tailor product and service offerings most suited to each individual. •If ‘bigger picture’ information is available, the organisation can proactively manage each account in the portfolio. For example, limiting credit exposure when it becomes evident that an account under review has started going delinquent at other organisations reporting into the shared database. Ultimately, this should encourage more informed and responsible lending practices. *Cape Argus, 2001-05-04 Benchmarking For Better Credit Management Where there is access to a centrally shared database, individual contributors can compare their own data to the industry or region, providing insight for better management. For example, comparing the company match rate against the shared database, where a low match rate indicates poor data quality on the portfolio. Alternatively, companies can agree to use a central database to periodically refresh their own customer information files, perhaps replacing outdated postal addresses. Companies can benchmark their portfolios or credit practices against the industry or other participating businesses. Typically, an independent vendor or third party manages this process, with company identities remaining confidential to safeguard any competitive advantage. Comparison is helpful in assisting management to understand how the business is performing, relative to the rest of the industry. A selection of key assessment measures might include: level of portfolio delinquency versus the industry, customer account utilisation relative to the industry average, comparative percentage of accounts with overlimit balances. In all, these measures create a comparative ‘snapshot’ to guide management in their decisions and actions. Summary This article details a few of the benefits that come about through data sharing. Due to space considerations, the less obvious advantages have not been included in the article. Slightly more obvious benefits include tackling the problem of fraud, reducing account processing times, and benchmarking companies against their industry sector. Increasingly, data sharing is nowadays undertaken by a number of business sectors, from banking and insurance, to retail and telecommunications. The growth in shared data initiatives is largely due to the logical realisation that, despite competitive and other confidentiality issues, there are many significant advantages to be had through the responsible and intelligent sharing of data. As such, data sharing practices should be seen as an inevitable and welcome evolution associated with more sophisticated economies. About the Contributor PIC Solutions is the leading specialist credit risk solutions company in the EMEA region. With offices in Cape Town, Dubai, Johannesburg, Manama and Nairobi, we deliver integrated analytics, consulting and software solutions to over 150 companies in 30+ countries. We work worldwide with organizations to improve performance, drive strategies and enhance profitability. Analytics | Consulting | Software |
| Last Updated on Monday, 08 November 2010 09:53 |