عنوان انگلیسی مقاله:
An explainable AI decision-support-system to automate loan underwriting
ترجمه فارسی عنوان مقاله:
یک سیستم پشتیبانی تصمیم گیری هوش مصنوعی قابل توضیح برای اتوماسیون پذیره نویسی وام
Sciencedirect - Elsevier - Expert Systems With Applications, 144 (2020) 113100. doi:10.1016/j.eswa.2019.113100
Swati Sachan ∗, Jian-Bo Yang , Dong-Ling Xu , David Eraso Benavides , Yang Li
Widespread adoption of automated decision making by artificial intelligence (AI) is witnessed due to specular advances in computation power and improvements in optimization algorithms especially in ma- chine learning (ML). Complex ML models provide good prediction accuracy; however, the opacity of ML models does not provide sufficient assurance for their adoption in the automation of lending decisions. This paper presents an explainable AI decision-support-system to automate the loan underwriting pro- cess by belief-rule-base (BRB). This system can accommodate human knowledge and can also learn from historical data by supervised learning. The hierarchical structure of BRB can accommodates factual and heuristic rules. The system can explain the chain of events leading to a decision for a loan application by the importance of an activated rule and the contribution of antecedent attributes in the rule. A business case study on automation of mortgage underwriting is demonstrated to show that the BRB system can provide a good trade-offbetween accuracy and explainability. The textual explanation produced by the activation of rules could be used as a reason for denial of a loan. The decision-making process for an application can be comprehended by the significance of rules in providing the decision and contribution of its antecedent attributes.
Keywords: Explainable artificial intelligence | Interpretable machine learning | Loan underwriting | Evidential reasoning | Belief-rule-base | Automated decision making