The insights from the counterfactual explanations provided by the framework can be valuable in informing decision-making processes in the credit rating domain and other real-world applications. In the credit rating domain, understanding the factors that influence credit ratings through counterfactual explanations can help financial institutions make more informed lending decisions. For example, if the framework identifies that a specific variable, such as the amount of capital stock, has a significant impact on credit ratings, financial institutions can adjust their lending criteria accordingly.
In other real-world applications, such as healthcare or predictive maintenance, the insights from counterfactual explanations can assist in understanding the factors influencing outcomes. For instance, in healthcare, identifying the key variables that impact patient outcomes can aid healthcare providers in personalized treatment plans. By leveraging the insights from counterfactual explanations, decision-makers can make more informed and data-driven decisions in various domains.