Champion-Challenger Testing for SA Banks and Credit Providers
TL;DR A collections model has been running at a South African bank for ten months. It was built on 24 months of payment data, the bulk of it pre-pandemic. It performed well in the first two quarters after deployment. Recovery rates in the 30-60 DPD bucket improved. Cost per recovery came down. In the last […]
Real-Time Collections Decisioning for India’s Digital Lending Market
TL;DR At 2:17pm on the 5th of the month, a borrower receives a salary credit notification. Her personal loan EMI was due on the 1st. She is now four days past due. At the moment her salary lands, her propensity to pay is at its highest point for the rest of the month. She has […]
Collections AI for South African Credit Providers: How the Technology Works
TL;DR A collections supervisor at a South African credit provider starts most Monday mornings the same way. She opens the delinquency report. She looks at the accounts between 30 and 90 days past due. She divides them into calling batches for the week, organised by balance with the larger balances worked first. Her team moves […]
Real-Time Credit Decisioning for US Collections Operations
TL;DR A borrower calls in on a Tuesday afternoon and makes a promise to pay by Friday. The collections agent logs the commitment. The account is flagged as PTP. Friday arrives. The payment does not post. Under a batch-processing collections system, that broken commitment sits unactioned until Monday morning when the overnight batch runs. By […]
Champion-Challenger Testing in AI Collections: A Practical Guide for US Banks
TL;DR A collections manager at a mid-size regional bank has been running the same contact strategy for three years. Recovery rates on early bucket accounts have drifted down four percentage points over that period. The strategy still looks reasonable in the monthly report. The segmentation logic has not changed. The contact sequences are the same […]
What Most Banks Still Get Wrong About AI Fairness
The most dangerous thing about biased AI in lending is that it rarely looks biased. It looks efficient, mathematical, objective, and scalable, which is exactly why institutions trust it so quickly. Over the last decade, banks have aggressively modernized credit decisioning using AI and machine learning. The promise was compelling: faster approvals, better risk assessment, […]
How Propensity Scoring Changes Debt Recovery: The AI Collections Advantage
TL;DR A collection floor on a Monday morning. The 30-day bucket report has come through. Two thousand accounts. Every one of them gets the same outbound call, queued in the same order, worked by the same team through the same script. Account 847 was going to pay on Wednesday regardless. The call interrupts her at […]
NCA Section 86 Debt Review and AI: Early Identification for SA Credit Providers
TL;DR A collections agent pulls up an account on a Monday morning. The consumer has missed two payments, the balance is overdue, and the system flags it for outbound contact. The agent makes the call. What the system did not show is that the consumer applied for debt review the previous Thursday, the debt counsellor […]
NCR Registration and AI Collections: What SA Debt Collectors Need to Know
TL;DR Picture a factory floor where every machine runs at full speed, every shift, without a supervisor watching. Output is high. Errors compound invisibly. By the time an audit catches the problem, thousands of faulty units have already shipped. That is what AI collections looks like when compliance architecture is treated as a secondary concern. […]
NCA-Compliant AI Collections: A Practical Guide for South African Credit Providers
TL;DR Consider a traffic intersection that was recently upgraded with new signals, new turning restrictions, and new pedestrian priority rules. The cars using it are newer and faster than before. Some have advanced driver assistance systems. But the updated intersection rules apply to the assisted driver with exactly the same force as to the manual […]
