Automating $250k Debt Recovery in Six Months
A fintech company had recently gone through layoffs and was suffering from poorer than expected loan performance, and was looking for ways to automate and outsource collections for defaulted loans. The company had not contracted outside parties to conduct collections on this population of loans before, so it needed to create an exchange process properly accounting for all the complexities of allocating and recalling loans from these DCAs prior to starting.
Challenges
How can we create an automated process to monetize the population of unworked, defaulted loans?
How can we automatically maintain this process through loan allocation and recall processes - for example, recalling a loan that recently declared bankruptcy?
Key Results
Led development and organized team for placing 9,000+ defaulted loans with 3 different debt collection agencies (DCAs) that were previously not being actioned on
Led to recollection of ~$250,000, or 8%, of the ~$3,125,000 in principal placed with DCAs, within the 1st 6 months
Created dashboards to continuously monitor DCA performance and lay foundation for future DCA tests
Value to Business
6 months after the initial allocation, the data exchange process has continued to run smoothly and has resulted in ~$250,000 principal, or 8%, of the ~$3,125,000 principal of the allocated loans. With the information on which DCAs are performing the best, they will be able to optimize for the best DCAs and place more or all of the loans with those companies.
In cooperation with the DCAs and internal collections teams, we designed an automated process design for the data exchange that accounted for all allocation and recall situations. Following the development and testing, we turned on the process by allocating 9,000+ loans to 3 different DCAs, and monitoring the automated recall process following the initial allocation.