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Impact Data

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Collection Agency


Our client was competing for market share of a high average balance credit card portfolio, using a strategy of intensive contact based on credit bureau scores. The results left it lagging behind the competition. The client’s statistics showed they were liquidating only 4.72 percent, while their five competitors were averaging between 5 and 5.5 percent. None, though, were anywhere near the issuer’s goal of 6.5 percent. Christmas season was approaching, bringing with it a natural payment slowdown, meaning no one was likely to meet the issuer’s target. By the time the client engaged Impact Data’s services, time was short: a market alignment meeting was in 90 days and our client stood to lose a significant share.

Using our proprietary geo-economic segmentation model, Impact Data created a 30-segment matrix identifying clients with a high propensity to pay from a pool of 9,788 accounts. The client had been aggressively working accounts with a score of 621 or greater.

Figure 1: Total Accountstotal-accounts

As the chart above (Figure 1) details, that strategy had the clients forcefully working slightly less than one-third of the accounts, with 36 percent of potential revenue (Figure 2).

Figure 2: Total Balancetotal-balance

Impact Data’s model suggested that accounts listed in the 1 total category should be worked five times more frequently than those in the 3 total spot. Accounts in the 2 total segments should be worked three times more frequently than those in 3.


Figure 3: Impact Data effect on accounts with new payments


Focusing on the accounts in the 1 total category, as Impact Data recommended, brought more than three-fourths of the new payments (Figure 3), accounting for 71 percent of the revenue (Figure 4). By the next market alignment meeting, our client had an incremental increase of more than $1.9 million from 1,058 new payments. During the three-month period, our client achieved a cumulative liquidation rate of 6.69 percent, exceeding the issuer’s goal and outperforming all five other agencies to gain the top position.

Figure 4: Impact Data effect on payments by segment



Client Benefit

In addition to the top spot among competing agencies, Impact Data’s client realized an incremental bottom line gain of $637,000 and an additional $31,000 in operational expense savings, contributing $668,000 to profit for the first quarter of 2014. It also was able to gain 30 percent more market share at the next market alignment meeting.

What can Impact Data do for your collection agency? We’ll prove our performance before we start with a sample of your data. Contact us to get started improving your market share, reducing operational expenses and adding to your bottom line. Or, register to receive our free eBook and learn more about the ways Impact Data can transform profitability through data intelligence.


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