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04/03/2025 Insurance Innovation
Most people want to resolve their debt. Creating a debt collection process that considers a debtor's personal, psychological, and behavioral factors offers an empathetic approach, addressing the challenges they face in making payments.
Innovation details
Country
Israel
Category
Product & Service Innovation
Keyword
Customer acquisition & loyalty, Customer experience, Customer service, AI & Generative AI, Insurance
Business Line
Motor insurance, Home Insurance, Liability Insurance
Distribution Channel
Online / Direct, Agents, Brokers

Innovation presentation

OVERVIEW Today’s debt collection landscape remains largely manual—relying on phone calls, letters, and prescribed and static outreach methods that often feel impersonal and aggressive. Unfortunately, this approach frequently leads to customer dissatisfaction, strained relationships, and, ultimately, lost business. In deploying a unique approach with the Wiserpay AI engine, Migdal Group is revolutionizing debt recovery by shifting the focus from simple recovery to customer retention—this new innovative debt collection project is called Migdal AI-Collect.

By leveraging advanced AI, Migdal AI-Collect creates a personalized, seamless experience that transforms the debt collection process into one that prioritizes retaining and improving the relationship between Migdal and the customer. With our customized integration of the Wiserpay AI engine, we’re analyzing a debtor’s behavior, predicting recovery rates, and offering personalized solutions to pay debt. The outcome is higher collection rates, lower recovery costs, improved customer satisfaction, and a stronger relationship between Migdal and the customer.

PROOF OF CONCEPT (POC) We kicked off this project in September 2024, focusing on a portfolio of previously written-off debts. Our goal with this POC was to focus on 1 million NIS (US$330K) with a target of 10% collection rate. Within just three months, we've achieved a 60% collection rate, significantly exceeding our initial expectations.

We discovered how individual customers respond differently to various communication channels. From varying hours of the day to different days of the week, and from preferring SMS communications to social media interaction, we realized that these communication challenges carried more weight with customer debt collection than we initially understood. Injecting an AI engine into this equation produced remarkable results. We achieved customer satisfaction of 90%, and that’s numbers representing surveys completed by the debtors themselves! And we raised our ability to recover what otherwise was lost debt by 60%, in only 3 months!

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