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Ahmed Mounir, Head of the Regulatory Sandbox at the Central Bank of Egypt (CBE), stated that relying on alternative data and behavioral analysis represents a strategic path for updating credit scoring systems. He explained that this approach aligns with the CBE’s vision to adopt modern financial technologies—led by artificial intelligence—to expand financial inclusion and modernize banking services, supporting innovation and meeting customer needs efficiently.

Supporting Innovation and Expanding the Beneficiary Base

Mounir emphasized that behavioral scoring based on alternative data empowers financial institutions to enhance their services and offer innovative products. The significance of these technologies lies in their ability to integrate groups that lack a traditional credit history or face financing obstacles due to insufficient historical transaction data.

The Role of the Regulatory Sandbox and Regulatory Framework

The Head of the Regulatory Sandbox noted that the sandbox's role is not limited to providing an experimental environment for testing smart financial solutions. It extends to establishing a comprehensive regulatory framework to evaluate these applications, analyze associated risks, and measure their readiness for actual deployment in the banking market.

Mechanics of Behavioral Scoring and Distinguishing Capability from Willingness

Mounir pointed out that alternative data provides a comprehensive and accurate picture of a customer's financial behavior by tracking recurring payment patterns, such as utility bill payments. He highlighted the importance of separating two fundamental concepts: "financial capability to pay" and "willingness and commitment to pay," as behavioral analysis helps measure a customer's eagerness to honor commitments even without a prior bank history.

Gradual Testing and Ensuring Financial Stability

He stressed the necessity of not generalizing credit scoring model results without conducting field tests on diverse customer segments to monitor repayment and default rates and measure prediction accuracy. Mounir concluded by affirming that the true success of these technologies depends on striking a delicate balance between expanding financial inclusion and maintaining credit portfolio quality and risk management.