Founded in the late 2010s, this fast-growing buy now, pay later (BNPL) lender provides point-of-sale financing across the United States. It partners with tens of thousands of healthcare providers, including dental, veterinary, plastic surgery and aesthetics practices, to help them treat more patients with flexible payment plans. It has funded around $2 billion across roughly 1 million transactions.
As the company scaled, so did customer expectations. Consumers expected financing to be personalized and supportive through repayment, not just available at checkout.
The lender's leaders wanted a collections experience as advanced as its origination process. In a fast-moving BNPL market, building that in-house would have taken years. They would have had to:
Every month of delay meant higher roll rates, mounting losses and the risk of falling behind competitors already raising the bar.
The lender deployed proCollect, powered by the Prodigal Intelligence Engine (PIE), the intelligence layer that drives next best actions for both AI agents and human teams. proCollect produced a daily strategy for each consumer across four dimensions:
Machine learning models then predicted each consumer's intent to pay within seven days and their recovery potential. Combining the two, proCollect routed high-value accounts to resource-intensive channels like voice and directed others to low-cost digital outreach.
The lender ran a champion-challenger test, with 45% of past-due accounts managed by proCollect and 55% left on its existing process. Reaching consumers at the right time, on the right channel, with the right message drove a 57% lift in digital engagement. Agents became more productive too, with 45% higher promise-to-pay in calling campaigns.
On the strength of these results, the lender is expanding proCollect to 100% of its past-due portfolio.
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