Case study


Designed and developed credit application models for DLL applying Machine Learning.

In an increasingly competitive market, the decision speed and quality of credit application assessments are vital for the success of financial institutions. VIQTOR DAVIS has developed new credit application models for DLL using Machine Learning to successfully uplift the quality of automatic approvals, improving decision speed significantly while absorbing lower risk levels in the portfolios. As transparency and auditability of decision models are key in the financial industry, we have opened the black box of Machine Learning using state-of-the-art algorithms to provide detailed explanations for every decision made. The explainability models are used to provide transparency of decisions to all stakeholders, from customers to regulators.

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Data migration for the merger of ING Bank and Postbank.

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International’s customer on-boarding process is verifiably now compliant with international regulation.

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Crédit Agricole Consumer Finance

Renewing the core banking system.


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