Non-Performing Consumer Claims Valuation remains one of the biggest challenges for institutional investors. The European market for non-performing consumer loans is a well-defined institutional asset class, but pricing remains an exercise in inference under uncertainty. This paper sets out a practical, statistically grounded framework for using external credit-collection data and reference recovery curves to value consumer NPLs when internal data is sparse, unrepresentative or absent, drawing on the Global Credit Data representativeness guidelines, Bayesian credibility blending theory and censored recovery-curve estimation.

The framework delivers a three-pillar methodology comprising representativeness assessment, censoring-aware recovery curves based on EBA Template 5 cashflows, and Bayesian credibility blending. Worked examples demonstrate how credibility weights evolve as post-acquisition data accumulates, providing institutional investors with a repeatable and auditable pricing discipline across cycles, sellers and product innovations.

Read the full article to discover how external reference data and recovery curves support non-performing consumer claims valuation: Valuation of Consumer NPL with External Data