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New credit scoring model cuts loan risks for financial institutions

CRC Credit Bureau Limited, in partnership with Dun & Bradstreet, has introduced CRC Delay Propensity Score to checkmate borrowers from delaying loan repayment and help…

CRC Credit Bureau Limited, in partnership with Dun & Bradstreet, has introduced CRC Delay Propensity Score to checkmate borrowers from delaying loan repayment and help financial institutions minimise risks.

The CRC Delay Propensity Score is a scoring model that predicts the likelihood of a borrower delaying their loan repayment within the next 30 to 60 days due to socio-economic factors. The model looks at borrowers who typically have never crossed the 90 days past due in their repayment. These factors may include the borrower’s credit history, number of dishonoured cheques and other financial information.

The CRC DPS model, which was developed in partnership with Dun & Bradstreet, analysing large datasets of borrower behaviour to identify the most significant predictors of delay, uses machine learning algorithms to continuously refine its predictions based on new data sources.

One of the key benefits of the CRC Delay Propensity Score, Daily Trust gathered, is that it provides lenders with a more accurate and objective assessment of a borrower’s credit worthiness. This allows lenders to enhance their credit review process, make better-informed decisions and adopt risk-based pricing in structuring loan terms.

During a briefing, Group Managing Director/CEO at CRC Credit Bureau Limited, Dr Tunde Popoola, stated that, “We’re excited to introduce the CRC Delay Propensity Score to the lending industry. By providing lenders with a more accurate picture of borrower risk, we’re helping to create a more stable lending environment that benefits everyone involved. It also supports the deployment of advanced technology in credit processing as the DPS can be integrated into existing loan origination and servicing systems, making it easy for lenders to incorporate the model into their existing workflows.”

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