Case Study: Credit Loan Approval Data

In this lesson, we’ll look at real-world business scenarios where AI decisions impact an individual.

In the realm of credit loans, it has become increasingly common for AI solutions to handle the processing.

But have we ever paused to contemplate how these decisions are made by AI and what implications biases may hold?

Step 1: Loan application

Maya, an ambitious entrepreneur, takes a significant step toward realizing her business venture by approaching a local bank for a loan. The bank manager requests her to complete a loan application, providing an opportunity for Maya to present her qualifications and meticulously crafted business plan.

Step 2: Data collection

The bank takes the data in the loan application form and supplements it with various other attributes it measures for the customer. These attributes include the customer’s past credit history, property owned, income, education, marital status, etc. All these attributes are fed to the AI decision engine.

Step 3: Decision by AI model

Behind the scenes, the bank employs an advanced AI-powered loan approval system renowned for its efficiency, speed, and accuracy. This intelligent solution utilizes sophisticated algorithms to scrutinize a wide range of crucial data points, including Maya’s financial history, credit scores, employment records, and more. The AI model processes this information to make an informed decision regarding Maya’s loan application.

Step 4: Rejection dilemma

Days pass, and Maya’s excitement turns into disappointment as she ...