How AI is Transforming Loan Management

By : |May 28, 2019 0

As loan management is one of the key divisions of banking and finance companies, AI adoption has grown to do all redundant and mundane tasks, but previously it was not the case. Before we proceed to current developments and the role of AI, let’s understand – what is loan management? In simple words, managing the loan amount, repayments, recovery etc.

Before providing a loan, banks and financial instructions review lenders profile, his/her income, expenses and liabilities, etc. On the basis of that analysis, a certain amount, interest rate and tenure can be decided. Earlier, this process was manual; thus, you can imagine how much time-consuming it was.

Thanks to the recent technological developments, no need to visit a bank and provide documents, etc. for the approval of your loan. While lending is growing rapidly, we can’t depend on the legacy process and there are chances of fraud as well. Cutting-edge technology tells the bank about you on the basis of your credit history and many other factors. Moreover, AI (Artificial Intelligence) is revolutionizing loan management and helping to detect the fraud plus in making lending decisions. But how and what are the impacts of AI adoption? Mahesh Shukla, Founder, PayMe India explain the role of AI in loan management.

How AI is reducing manual efforts to make loan decisions?

                                 

___________________________________________________________________________________________________________

On one hand, it reduces the burden of lenders by automating or digitalizing credit monitoring and background checks of the applicants whereas as enables the borrowers to track their credit score, connect to a lender, and get instant loans at the time of urgency.

Nowadays, various AI-based platforms match relevant lenders’ profiles with borrowers’ requirements quite precisely, eliminating the need for submitting numerous applications at multiple lenders, who might not be suitable. This saves time and efforts simplifying credit access and accelerating the whole loan disbursal process.

Other than this, the FinTech companies use smart lending apps catering directly to the individual customers and businesses. AI helps both parties make well-informed and data-backed lending decisions and give cue about the potential risks involved.

How is machine learning applied in lending?

Machine learning evaluates the information extracted from loan applications, documents, and alternative data to learn the capability of a borrower to repay the loan as well as forecast other more likely outcomes.

As ML algorithm learns itself through data, it eliminates any possibility of bias or error, which is common and redundant in human underwriting. Many FinTech firms and banks use ML to identify the borrowers are more likely to default and the prospective ones who can be trusted and therefore, it decreases the cost of credit risk assessments. It helps the lenders make complex decisions better and faster with minimal efforts as it backs them up with relevant data and insights.

Key tech elements to keep in mind while adopting AI

We use advanced languages like Python as our backend, and we have integrated libraries like Pandas & Scikit-Learn. Scikit-Learn provides a wide selection of supervised and unsupervised learning algorithms, and it’s by far the best library for data science and AI-based programs.

How AI is going to impact lending?

The application of Artificial Intelligence (AI) in banking and finance, particularly in lending and borrowing segment, has driven gold rush in the market. Both lenders and borrowers have been switching to AI-powered instant loan apps, making strides towards the national mission of financial inclusion. Agile and faster processes now replace the antiquated ways of credit underwriting, evaluating loan eligibility, and processes of loan approval with AI.

AI-enabled software and tools verify data of the borrowers across multiple online platforms to generate reports for the lenders, helping them make smart and right decisions while boosting their productivity. For the borrowers, it’s convenient to apply for instant loans, submit their documents, undergo online verification, and get loans within two or three days. Neither they are required to request people and agencies for references nor do they need to rush from lender to lender or consultant to consultant seeking financial help and funding solutions. All of this can be done online with the ease of their comfort. These benefits driven by financial innovation are encouraging the unorganised money lenders to foray into FinTech industry.

Key impacts of AI in Loan Management

AI resolves one of the serious concerns of lenders in a bat of an eye and that is, evaluating the creditworthiness of the first-time borrowers. The lending companies and banks use AI-backed underwriting solutions to identify a reliable and trust borrower who has no credit history.

It collects data from all across social media and online channels to create a profile/portfolio of the borrower which predict the potential risks and benefits associated with the loan request. Also, predictive analytics let the industry players improve their decision-making processes in regards to timely detection of internal and external frauds and checking the authenticity of documents submitted.

Whether it is an income declaration or bank statement, AI quickly detects any discrepancy in the structured/unstructured documents, thereby shortening the underwriting process.

The future of AI-powered lending

The AI revolution in the lending industry has just started; the best is yet to come. With continual innovations in AI and Machine Learning, the lending industry will also be upgraded to lending industry 4.0 where automation and data-based decisioning will be considerable growth drivers. Where technology will do all redundant and mundane tasks, humans can invest all their time and resources in completing high-value tasks.

No Comments so fars

Jump into a conversation

No Comments Yet!

You can be the one to start a conversation.