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1st Credit becomes the 1st Choice

Turning bad debt into successful business

With 1.5 million accounts worth over £3 billion under management, 1st Credit is one of the United Kingdom's leaders in debt purchase and outsourced debt collection services. The company works primarily with banks, credit card providers, utilities, telecoms and retail companies, buying their bad debts and then working with the debtors in a supportive and constructive way to help them pay off the money owed.

People get into debt for a variety of reasons: they lose their jobs, they suffer an unexpected change in their family situation, or they take on more debt than they can handle. Some even take out loans with no intention to pay. Each situation has to be treated on its merits. 1st Credit's task is to locate the debtors and then come up with a realistic strategy to help.

Banks and other credit institutions have usually gone through their own debt administration and collection process, with the aim of rehabilitating the customer: the aim is to make the customer profitable again. They typically sell the debt only when they have given up and are cutting their losses.

The science of debt collection
Until relatively recently debt collection companies ran on "gut instinct" about how to handle individual cases. 1st Credit is one of the pioneers of a more scientific approach, both in terms of acquiring debts from clients at the right price, and managing the relationship with the debtor. Dr Simon Young, as Chief Risk Officer, is responsible for developing this "science" and uses SAS software to enable 1st Credit to model and analyse debt.

"There are only one or two other debt collection companies operating with our level of sophistication," says Young. "Analytics is one of our most important competitive differentiators, especially the ability to calculate the likely value of each individual debt we take on.

"Before we had SAS we could monitor our performance. We could see how fast funds were coming into the organisation. But it is only since we have been using SAS that we can manage debt proactively, putting us ahead of the game," adds Young.

"In the early days, when we were only managing a handful of debt portfolios, we could get by. But now we have more than 300 portfolios and no human being can stay on top of that without a scalable analytical software," says Young.

Each portfolio is a batch of debts. Based on the historic data that 1st Credit has built up over the years, and experience of the characteristics of individual debtors (based on variables such as age, location, profession, marital status and so on) the company has been able to build models in SAS that enable it to predict the future performance of a debt.

"The model is redeveloped every six months based on the most recent experiences, trends in the marketplace and the latest information from credit reference agencies, so we are constantly improving our predictive capabilities," says Young.

Fast decisions
1st Credit's annual growth rate has been about 50 percent throughout its history, and 60% in the three years it has been using SAS, far faster than any other operator in the UK market, in large measure because it can react to opportunities more quickly and effectively than its competitors. "If a bank wants to offload some debt quickly, we can run it through our model and take the decision on a bid faster than our competitors. If necessary, we can turn a decision around in 24 hours." says Young. "Using SAS, we can examine batches of debt down to the individual debtor level, and then aggregate it or subdivide it based on a range of variables to probe the potential profitability. Ability to break down the debt and then aggregate it across different dimensions is absolutely key to optimising purchase decisions," says Young.

"Getting this right is business-critical," he adds. "If our bids are too high, we will be unprofitable, and if our bids are too low, we won't get the business in the first place."

Once 1st Credit has acquired the debt, the next challenge is to identify the best strategies for debt management and recovery. "We run the debt portfolio through our model and split it into different segments based on historic performance," says Young. "A different strategy is appropriate for each segment; we need to monitor them over a period of a few months to see how well they are working, and which factors in the strategies are most important in getting the desired results." These strategies typically cover how to make the initial contact, and what sort of offer 1st Credit should make to the debtor.

"If we are convinced that the debtor is likely to pay, it is worth investing time and effort, for example with visits and telephone calls, to help. If it is less likely that the debtor will pay, it may not be worth making as much effort." says Young.

That is just the start, and it is an over-simplification, of course. "We are developing a more behavioural based approach with SAS that gives us insights over the entire lifecycle: not just deciding up front how much time we will invest in a debtor, but also how to respond if things go better, or worse, than expected," says Young.

Continuous improvement
Dr Young and a team of three analysts developed the solution further in-house. "SAS offers us an exceptional ability to combine and manipulate data to develop analytical models, and to export outputs into other formats for further analysis by 1st Credit's management," says Young. His team passes regular reports to the Board and senior directors to monitor company activity, enabling them to fine-tune growth plans.

They also supply reports to operational managers, including debt collectors, so they can see how well they are performing and identify priorities that they can act on, for example by attempting to adjust a debtor's payment terms.

1st Credit is now looking at SAS text mining technology as a possible next step forward. "Ours is above all a people-oriented business and a lot of information is captured in conversations between collectors and debtors. Analysing this information could provide vital clues that help us to improve our performance even further," concludes Young.

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1st Credit

Business Issue:
1st Credit's business model depends on its ability to price batches of debt more accurately and swiftly than the competition.
Solution:
The company feeds historic data into its SAS® software-based models to determine the right price to bid for business, and then to develop effective debt collection strategies.
Benefits:
The ability to get good business fast, and then manage debt collection effectively, has enabled 1st Credit to grow at a rate of 50% per annum.

SAS is business-critical. If our bids are too high, we will be unprofitable, and if our bids are too low, we won't get the business in the first place.

Dr Simon Young

Chief Risk Officer

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