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How AI improved debt collection decision-making

How AI improved debt collection decision-making
The Challenge: Uncertainty in Debtor Behavior

A leading debt collection agency managed dozens of small, diverse debt portfolios, each with varying structures and risk levels. Without standardized data or predictive models, bidding on portfolios was based on guesswork, leading to unreliable returns and inefficiencies.

The Solution: AI-Powered Prediction of Debtor Cooperation

Digiwit introduced a data-driven AI solution to cut through uncertainty:
✅ Historical Data Analysis – Identified patterns in debtor behavior.
✅ CRISP-DM Methodology – Tested 20+ predictive models, selecting the top 6 with the highest accuracy.
✅ Automated Predictions – Provided decision-makers with on-demand insights via a custom-built interface.

💡 Key Benefit: AI turned subjective decisions into clear, data-driven insights—eliminating uncertainty.

The Impact: Smarter Investments & Increased Efficiency

🚀 32% Increase in Operational Effectiveness – AI-driven predictions enabled better bidding decisions.
📊 160 Hours Saved Annually – Eliminated manual analysis, freeing up time for strategic work.
💰 Improved Profitability – AI insights helped target high-yield portfolios while avoiding lower-return investments.

Conclusion: Smarter Debt Collection with AI

Digiwit’s AI-powered decision engine has redefined debt collection strategies—transforming inconsistent data into actionable insights for better financial outcomes.

🔹 Want to revolutionize your debt collection strategy? Schedule a demo with Digiwit today!

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BRAINHINT B.V.
Zeestraat 70, 2518AC
Den Haag, The Netherlands

Industries
Banking & finance
Professional services
Retail & trade
Expertise
AI-first applications
AI-ready infrastructure
AI-powered automation