Credit risk is a major concern for financial services institutions, as it can lead to significant financial losses and reputational damage. Traditional methods of credit risk assessment, such as manual review of credit reports or rule-based systems, can be time-consuming and may not provide accurate risk assessments.

AI and machine learning (ML) can play a key role in mitigating credit risk and improving credit decisions in financial services institutions. By training an ML model on data from various sources, such as credit reports, financial statements, and customer behavior, our solution can assess credit risk and provide recommendations for credit decisions. In addition, ML models can be used to adjust credit risk assessment algorithms in real-time based on new data and emerging trends, ensuring that financial services institutions are always making informed credit decisions.