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Account Aggregation


Driven by its mission of financial inclusion for all, Lokyata created an AI-driven credit risk platform that enables lenders to provide underbanked borrowers with better access to credit, at a lower cost. Lokyata uses AI-driven predictive analytics and workflows to provision fully automated loan underwriting in an easy-to-acquire, cost-effective solution.

The Challenge

Lenders rely on credit scores to make loan underwriting decisions. As a result, underbanked borrowers with poor credit scores often cannot qualify for a personal, consumer, or auto loan. When these borrowers qualify, lenders hedge against high default rates by using a “one-size-fits-all” approach and charge extremely high interest rates. Lokyata wanted to enable lenders to provide underbanked borrowers with better access to credit at a lower cost and needed access to transaction data to help inform its AI-driven credit risk platform.

The Solution

By integrating MX aggregation and incorporating real-time borrower transaction data in its Bank Transaction Analyzer, Lokyata provides lenders with a more scientific and objective assessment of a borrower’s financial health. As a result, borrowers with poor or non-existent credit scores can gain access to credit, and lenders can provide loans to underserved borrowers at a significantly lower cost.

The reliability and number of MX’s connections to banks was very important to Lokyata when selecting a partner. Many underbanked borrowers use smaller community banks and credit unions, and bad connections result in a poor customer experience—potentially lost business for our clients.

Steve Bireley


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