Collections and servicing teams are turning to digital channels like email to boost payments and lower the cost to collect. But early digital outreach doesn't always meet expectations. When a large buy now, pay later (BNPL) lender asked us to help raise revenue from email, we set out to show how AI changes the game.

• 43% increase in number of payments
• 14% increase in email open rates
• 27% increase in email click-through rates

The challenge

Digital collections is new enough that there are few proven standards to rely on. To improve email and SMS outcomes, teams need to find the ingredients of a successful connection: the day, the time, the message and the frequency. AI trained on consumer finance can analyze enough data to tailor each of these.

The data

The lender's goal was simple: more revenue. Prodigal built a proprietary AI model to improve on its standard email practice. The model weighed almost 200 variables, including how those factors interact. By analyzing the behaviors that led to opens, clicks and payments, it showed how to maximize revenue by optimizing the day, time, message and frequency of each email.

The results

Following Prodigal's recommendations, the lender saw:

• 14% lift in open rate
• 27% greater click-through rate
• 43% increase in payments

Results also improved for accounts usually assumed to be harder to collect, including older and higher-balance accounts. Extrapolating from these early results, the lender can expect about $40K in additional revenue per day, or $800K per month.

Download the original case study (PDF)