In our first piece on the changing landscape of collecting through litigation, we pointed out that the soft financial market and corresponding uneven regulatory landscape have added up to a great deal of waste and loss of profitability in collecting unpaid debt. In this article, we describe new systems coming into play that will employ technology to optimize litigation processes and return them to profitability. 

There are many ways collection professionals decide whether or not to pursue legal action on collection accounts. We’ve identified at least ten so far - from taking action on all or none of the accounts to only acting on collector referrals or accounts going out of statute to the use of cutting edge, analytics-based models. 

We’d like to explain how this last approach, used proactively, may ease risk and boost profitability, thus leading to three benefits for debt collectors: 1) suing the right accounts; 2) lowering the cost of mistakes; and 3) improving the return on total costs. Can this be done?

Suit decisioning that leads to profitability for creditor and collection professionals involves several factors. Foremost is figuring out where to target collections - ideally meaning going after people who could pay back a large portion of the outstanding debt. 

It’s critical, of course, to identify these consumers by looking at asset information. Approaches to identifying and verifying assets vary greatly among creditors and collection specialists. Some use verified data from secondary sources; some use unverified data; and some conduct internal identification and verification processes. In the worst of cases, no verification takes place at all. 

Lawsuits, as well as data acquisition and verification, all have quantifiable expenses and timelines. Often outstanding debt is satisfied only partially, if at all. Putting these pieces of the collection puzzle together, a proactive process seeks to answer two questions: What’s the likely profitability of the suit decision? How can I most quickly, easily and compliantly satisfy the judgment?

The Profitability Index

Given that the ultimate goal is to prioritize consumer debt for collection based on ability to pay, that identity data is now verifiable and widely available and that we have a few quantifiable factors such as legal and data acquisition costs, an actual equation or algorithm can be used in the decision-making process. 

We’ve dubbed this method of inquiry the Profitability Index. In short, profitability can be determined as a result of dividing a Probability Adjusted NPV (net present value) by the sum of the court cost and information cost. The Probability Adjusted NPV is an evaluation of 76 different variables for each individual account. 

It answers two questions: What is the probability of payment? How much money will be paid? In other words, what is the likelihood of receiving what percentage of the total amount that is owed? 

Court costs vary for instituting and conducting a lawsuit and information costs vary for identifying and verifying assets. 

That may sound a bit baffling, but with the power of technology and responsible data use and analytics, figuring out how to make collections the most profitable and least risky becomes a number-crunching exercise. 

A few of the benefits that state-of-the-art information science can offer include identifying a consumer’s ability and means to pay, locating assets, ensuring data quality and accuracy through multi-step verification processes and identifying previously undiscovered assets. All of these lead to a greater likelihood of successful, compliant collections because of the accuracy of available information.

This approach to collections management first allows professionals to evaluate debt portfolios in a consistent, quantifiable way. Second, it enables them to evaluate consumers for the most advantageous collections channel and/or treatment strategy. 

It can also mitigate wasteful spending by eliminating costs, using a more holistic and rational approach than in the past. Maybe it's time to consider a data-driven analytical approach for your collections practice.

Jason L. Horsley is director of Market Planning, Receivables Management at LexisNexis Risk Solutions, a provider of essential information that helps customers across industries and government predict, assess and manage risk. He can be reached at


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