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Leaning into innovation to bring newfound speed and accuracy to credit risk modelling

Bharath Vellore
Bharath Vellore5/27/2022 12:00 PM GMT+08  • 4 min read
Leaning into innovation to bring newfound speed and accuracy to credit risk modelling
The era of AI is here – just in time for organisations to come to terms with and move forward with better credit risk decisioning. Photo: Scott Graham/Unsplash
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With all the disruption stemming from COVID-19 over the past two years, how sound are credit risk models? According to our recent survey, only 16% of fintech and financial services organisations believe their credit risk models are accurate at least 76% of the time.

This state of great uncertainty in credit risk modelling exposes the shortcomings of legacy approaches for credit risk decisioning that leverage limited data, workflow and automation – often in separate systems.

To level up decisioning, organisations need more data, automation, sophisticated processes, forward-looking predictions and greater speed-to-decisioning. And to this end, they need artificial intelligence (AI), machine learning, and alternative data.

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