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Track record · Debt collection

More precise debtor profiles, more effective debt collection

For an internationally leading debt-collection company, an AI-supported profiling system for debtors in managed and acquired portfolios was built: internal and external data is collected, cleaned and enriched to profile each debtor individually and steer outreach accordingly.

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The challenge

The problem

Debtor profiles in managed and acquired portfolios were imprecise, and important signals from internal and external data sources went unused.

The potential of a dynamic, individually profiled approach to debt collection, with outreach tailored to each debtor, remained untapped.

Analytics

The solution

How it was solved

Data aggregation Targeted collection, aggregation and cleansing of internal and external data in a central data warehouse.
Individual profiling Each debtor is profiled individually, with results passed to downstream services for steering.
Tailored outreach The channel, tone and timing of outreach (mail, call) follow the individual profile.

The results

14 % increase in debt recovery
4 % reduction in write-offs
60 % reduced staffing (FTE) in administration

Technology

Methods used

Stack

  • Machine Learning
  • Data warehouse
  • Profiling
  • Data enrichment

Per the project report: around 76 million euros in combined savings and revenue effect.

Led by Beyonetix founders and senior engineers. Figures per the respective project report.

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