The virtual world is progressing rapidly with interactive digital communication triumphing over face-to-face interaction in almost all industrial sectors including finance. This, in turn, has boosted the growth of AI, and the technology is increasingly used in web platforms and apps we use daily. Most industries incorporate AI, and the financial lending market is no exception.
The introduction of digital solutions in the financial market brought many changes in how services were offered to customers. As a result, financial transactions, including borrowing and lending, have also moved on to digital platforms.
The entire process, from the loan application to the approval and disbursement of the fund, is now carried out through digital lending solutions. These apps make applying for loans easy and systematically collect user data to help the financial institution assess the customers.
So, with the automation of the lending process, the applicants will apply for loans with minimal paperwork, and lending establishments can get insights from the user data, making the process simple and manageable.
How is AI Improving Lending Solutions?
Here are some key cases where AI plays a significant in the lending process
Document Classification:
Regardless of the amount, the lending process involves a lot of paperwork, document submission, and review that takes a majority of the time in the whole process. The first step of the process is document submission by the borrower.
Without AI-Powered digital lending platform, an individual would have manually checked and reviewed the paperwork. However, with AI entering the playing field, the job has become easier.
The AI identifies unique markers in the documents submitted by the borrower and ensures that the system recognizes the type of document presented in the system. After that, the AI creates a digital loan file unique to the customer to store essential data taken from the submitted papers.
Initial Screening:
Lending institutions receive hundreds and thousands of loan applications every day. These applications are then screened based on the various credit model the financial establishment offers.
AI manages the entire process, minimizing clerical errors and speeding up the loan management process. With AI taking over the screening process, the company saves time, and the teams can focus on other essential aspects of the lending process that would require human intervention.
Checking Credit Scores:
Credit scores are essential as lending companies use them to gauge applicants’ repayment ability. Before AI stepped into the financial sector, a single credit score was considered before approving or rejecting loan applications.
It was not a well-rounded method, as many individuals might not have credit scores at all but have the means to pay off the loan easily. AI has developed alternative credit scoring methods that analyze consumer behavior and spending patterns to gauge the applicants’ ability and sincerity in paying off the loan.
With the help of such innovative functions, the turnaround time for processing loan applications has gone down significantly.
Detecting Fraudulent Applications and Candidates:
Loan stacking is one of the many cybercrimes where individuals take multiple loans from several lenders. It is a common practice in the lending industry, and authorities are taking continuous steps to prevent such actions.
AI has proved to be quite effective as it detects the behavior pattern of the loan applicant. If it identifies unusual or suspicious behavior on the applicant’s part, it immediately flags the applications.
On the other hand, it also helps the lending institution keep consumer and internal data safe from cyber criminals.
Reduced Due Diligence Costs:
AI can gather and analyze billions of data in seconds and update the database simultaneously. It helps the firms cut down the due diligence costs significantly. Before approving a loan, lending companies must appoint teams to manually check these records, including the applicant’s credit history, employment details, income source, assets, taxes, and more.
Moreover, this is not one-time work. The data has to be updated regularly to keep track of the installment payments if the loan gets sanctions. Forecasting borrower behavior and updating minor and important details for the loan application process is time-consuming and cumbersome, leading to human errors.
AI avoids such mishaps and provides accurate results without the help of human intervention.
In Conclusion:
An AI-powered digital lending Platform help both the borrower and the lender. AI cuts down the enormous paperwork for the borrower and makes applying for a loan simple and easy. As for the lender, it verifies application information and helps them reach a decision quickly.
