The credit risk assessment process in banks has historically been a labor-intensive task, requiring significant manual effort. However, a new approach to credit assessment that combines expert knowledge with artificial intelligence (AI) is revolutionizing the industry.
Traditionally, financial institutions have used ‘rule-based’ decision trees to process credit checks more efficiently. While these automated systems have provided some relief, they have also presented challenges. The complexity of defining detailed rules and maintaining the system has made it difficult to adapt to changing circumstances, ultimately reducing accuracy.
To address these limitations, a new model has emerged that combines AI with expert input. By capturing the knowledge of multiple experts in an AI model, credit decisioning becomes more efficient and consistent. This model works objectively, reducing the likelihood of human error and bias, while also being flexible enough to adapt to changing market conditions.
The experts play a crucial role in this process. They identify the relevant variables, create a training set, and provide representative examples with an objective risk scoring. This reduces dependence on…
