Credit Kudos has launched a new open banking credit scoring system to accurately predict repayments and help lenders serve more customers and reduce defaults.
Named ‘Signal’, the system will allow the credit reference agency to use a combination of machine learning and open banking gathered transaction data to accurately predict an individual’s likelihood of repayment.
Credit Kudos said Signal allows lenders to increase acceptances, helping lenders reach underserved customers by accessing an accurate understanding of anyone’s financial situation.
The credit reference agency said that Signal uses open banking data and insights to accurately predict someone’s creditworthiness so it can reduce lender defaults.
The firm said the credit score gives evidence for its risk decisions so lenders can understand it, be transparent and fulfil regulatory requirements.
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“Credit scores based on traditional credit data are not only limited but can lead to lenders wrongly declining those who are creditworthy,” said Freddy Kelly, chief executive of Credit Kudos.
“Our new open banking-powered credit score, Signal, allows lenders to accurately assess all applicants – including those with thin files – meaning they can safely increase acceptances without increasing risk or defaults.
“It is highly accurate, fast, and wholly explainable, all of which are integral features to helping lenders make better, more informed and responsible decisions.”
In June, Credit Kudos launched a new decision engine called Assembly which aims to save lenders thousands of hours in manual underwriting.