How portfolio valuation works in receivables purchasing.
Before a receivables purchase goes ahead, buyer and seller first have to agree on a purchase price. To determine as fair a purchase price as possible, EOS deploys human expertise and modern technology to put a value on the receivables portfolio.
- The valuation of receivables packages is a complex process that results in an appropriate purchase price.
- Experts at EOS scrutinize every little aspect of the portfolio to determine the risk of the intended receivables purchase.
- This process makes use of algorithms and the expertise of trained analysts.
As part of the risk management function, the Operational Debt Purchase Team works with specialists in methods and analysis to thoroughly scrutinize around 800 receivables packages a year. At the end of what is a complex process, a purchase price can be recommended. “These kinds of portfolios can contain up to a million receivables. Therefore, we basically look at it as we would a shoal of fish. We need to understand what makes the shoal tick and what direction it is swimming in, not the direction of each individual fish,” says Matthias Schmidt, Head of Operational Debt Purchase at EOS Group.
The more accurate the evaluation, the lower the financial risk.
Have they ever got it wrong with their recommendations? “Yes, definitely!” Matthias admits. “But our success rate is pretty good.” Matthias actually has a doctorate in physics. After graduating he initially worked in the field of semi-conductor technology development, then as a consultant working mainly with ‘bad banks’. “And now my job is to find out what makes receivables portfolios tick,” he says. What all his previous roles have in common is the need to deal with complex subject matter. “I am someone who loves to understand the background,” he says. It’s an essential quality when evaluating portfolios. Because ultimately, it’s about making a decision involving a lot of money.
The raw data tell the story.
Because apart from quantity, the quality of the data also plays an important role: “In some countries you might get seven phone numbers for each receivable. You don’t know which, if any, is current until you have tried them all and got lucky,” says Matthias. “Or you don’t know if the information is still up-to-date. Obviously, that depends. Details provided ten years ago when a loan was taken out might no longer be valid.” Transcription errors are also an issue, for example if ownership of the receivable changes hands, two banks merge, or systems are migrated to a new system. After reviewing the data, Matthias and his team ask themselves two questions: What do we know, and sometimes much more importantly, what do we not know?
An algorithm could never develop a sense of the story of the portfolio the way an analyst does.
Past experience helps determine price.
In special cases the team falls back on algorithms, which are used to process complex data. A good result, however, does not depend on raw data alone. The human factor also plays an important role in the evaluation: “An algorithm could never develop a sense of the story of the portfolio the way an analyst does,” says Matthias. From a certain point you also need intuition, which is based on experience.