Interviewing AI enabled system for credit card risk mitigation

 

Modern banking places a high priority on preventing credit card risk, and many financial institutions use cutting-edge artificial intelligence (AI) technologies to evaluate a person's credit worthiness and capacity to pay back the debt. These AI systems examine a wide range of parameters, from credit scores and income levels to spending patterns and behavioral data of a specific individual or organization, using cutting-edge technology and algorithms. In this blog article, we'll look at some of the complex and technical checks that these systems may run and how they assist financial institutions in making better decisions about preventing credit card risk.

Though I started writing this blog keeping credit card issuance in mind, but these questions are valid for any kind of loan bank offers to it's customers as most of the risks associated with it are common in nature.

Meet our interviewee Ava, a fraud detection and scrutiny system trained with TBs of data over the period of a decade (or probably more) -

Image - AI generated image using prompts

So here we begin:

Q. Hi Ava, it's great to have you here today. Before we dive into the interview, could you tell me something about yourself?

Ava Hello, it's great to talk to you as well. I'm Ava, and I'm an artificial intelligence system tasked with evaluating the risk and fraud associated with credit card applications. I assess a variety of indicators, including credit scores, income levels, spending habits, and behavioral data using sophisticated algorithms and data analytic techniques to decide whether a potential application is likely to be a good fit for a credit card. To make sure that my evaluations are as accurate and dependable as possible, I am always learning new things and refining my analysis techniques.

Q. What checks do you perform to verify applicant's information? There could be a possibility of information given to the bank turns out to be fake.

Ava To make sure the person is not using incorrect information on their application, the system will do a fraud check. This could require cross-referencing the person's name and address with public records or other databases. Before making a final judgement, the system can request more supporting documentation from the applicant if there's a need of it.

Q. What are the other ways to confirm individual's identity besides the documents applicant has submitted?

Ava The system might use biometric verification, such as facial recognition or voice recognition, to verify the individual's identity and prevent fraud. This could involve comparing the individual's image or voice to their government-issued ID or other records.

Q. How do you decide if the person is eligible for the credit card?

Ava Through a check on employment. The system will examine a person's employment status, including their title, pay, and time spent in their current position. In case if the applicant is running a business the checks will be done accordingly. This information can help the bank to determine the individual's ability to make regular credit card payments.

Q. How do you analyze that the person is likely to pay the dues?

Ava The system runs credit checks to verify a person's credit history and credit worthiness. This allows the bank to determine the likelihood of the person repaying the credit card debt. A credit check also reveals outstanding debts, arrears and arrears.

Q. How do you decide the credit limit for an individual?

Ava The system can also look at an individual's income and expenses to determine the expense-to-income ratio. This calculation compares a person's gross debt payments to income and helps system to estimate a person's credit limit.

Q. How the system analyze the overall financial condition of an individual?

Ava Through an aggregate model. The system may use account aggregation technology to collect information from personal bank accounts, credit card accounts, and other banks to determine applicant's overall financial situation. This includes factors such as income, expenses and credit utilization.

Q. Considering that everything goes well, is that it and credit card is given or there're other steps too before bank offers the credit card?

Ava No, there're few more checks. To determine credit worthiness, the system may use machine learning algorithms to evaluate the individual's behavior, such as their online and offline activities, social media profiles, and mobile phone usage. This analysis could include things like their spending habits, frequency of transactions, and interactions with debt collectors.

Q. How do you calculate the risk of delay or default in payment?

Ava The system uses various AI modeling techniques to assess default risk or individual default risk. This involves analyzing large datasets to identify patterns and correlations between various factors such as credit score, income levels, employment status, credit card performance and more.

Risk detection and prevention is a complex process specially when it comes to finance. Above discussion gives a high level idea about a system which is designed to perform such tasks to detect any such situation and inform the concerned authority to take appropriate action. Besides such system, each bank has multiple levels of approval workflow to make sure that no stone is unturned before a final decision is taken.

Hope you liked the blog and has something to say about it. Do share your feedback / inputs which you think can be a good addition to the topic.

Thanks for giving me your valuable time!

Writer: Jitendra Anand