Underwriting refers to the process commercial banks undertake to evaluate and assess the creditworthiness of borrowers. Only then can these lenders determine the potential risk they are likely to incur when sanctioning loans to them. The risk involves the probability of the borrowers defaulting on their timely loan repayments. The financiers have no option but to write off the unpaid portion of their loans as bad debts. Accordingly, the financiers take the decision whether or not to approve the issue of these loans to borrowers. This procedure plays a critical role in determining the interest rates chargeable once the banks sanction the borrowers’ loans.
What exactly is AI underwriting?
Every company, small entrepreneurs, or individuals applying for a loan needs to go through the underwriting process. This is necessary to accurately assess the creditworthiness of these potential borrowers and determine the interest rate chargeable. It is an elaborate procedure involving the scrutiny and analysis of a wide range of vital information. These include financial statements, credit history, salary details, current debts, place of residence, present employment, and other relevant paperwork. Only then can commercial banks decide whether it is worthwhile to approve their loan applications. However, manual underwriting of loans has the following shortcomings:
- It is a time-consuming and labor-intensive process, and
- It is not possible to eliminate all forms of clerical errors and unintentional bias during the evaluation.
Artificial intelligence is a branch of computer science involving the building machines’ capability of performing tasks that require human intelligence. In the finance sector, this latest technology is making significant inroads in the area of the underwriting of bank loans. The use of artificial intelligence technology to analyze the underwriting data for determining the creditworthiness of borrowers is known as AI underwriting.
How does it work?
The underwriting software solutions banks operate use its artificial intelligence features to gather big data on borrowers from multiple sources. It can be in the form of social media, e-commerce, business, banking, or governmental agencies’ websites on the Internet. This data can be in both structured or unstructured form. The software solution then stores, categorizes, and scrutinizes this information using its in-build machine learning metrics. Then, the system transfers the data to its pre-set predictive models for in-depth analysis. These models have optical character recognition and natural language processing analytics to extract the relevant details necessary for the underwriting process. Then, the solution examines the information to produce an accurate creditworthiness and risk profile of the borrowers.
The benefits of using artificial intelligence to automate the underwriting process commercial banks use to evaluate borrowers’ creditworthiness are as follows:
- Expedites workloads which commercial banks would take hours to process,
- Significantly minimizes clerical errors by streamlining the underwriting workflow, and
- Eliminates human bias in evaluating the borrowers’ creditworthiness.
Software solutions incorporating Al underwriting technology help commercial banks to get an impartial evaluation of their borrowers’ creditworthiness. On the basis of the results and the solution, these financial institutions can then make a decision on whether to approve their loans. However, the software solution the lender selects should be compatible enough to integrate into their IT infrastructure. Above all, it should be cost-effective to operate seamlessly for the entity as well.