How AI-ML driven Bank Statement Analyser can help financial Institutions

The Banking Industry has seen tremendous changes with the advent of new technologies. Now with AI-ML driven Bank Statement Analyser, lenders can evaluate credit applications faster, reduce costs and increase the number of loans approved per month without compromising on accuracy! Let’s take a closer look at how this will benefit financial institutions in today’s digital world.

Loan Processing Document

Automating financial statement analysis. Banks are finding that by analyzing credit risk at a fundamental level—in other words, underwriting—they are able to approve loans more quickly and with fewer hiccups. By combing through financial statements looking for red flags, banks are better able to predict whether or not a customer will default on their loans, leading to quicker loan approval rates and a reduced amount of bad debt. Earlier, Financial institutions use underwriting processes that take weeks or months for each loan. This lag in time led many high-risk customers to borrow money who would never pay it back leading to them being broke or bankrupt before they could get caught out.

Advantages of using automatic bank data analysis tools:

We all agree that in order to run a successful financial institution, one needs to have an organized and streamlined business model in place, where the institution’s assets are taken care of in a meticulous manner. However, there’s also another aspect that many institutions tend to overlook that competition is rising, clients are getting harder to onboard and retention is taking more effort every day.

There’s no time for mistakes or bad deals when it comes to financial institutions. Luckily, automated financial statement analysis tools are here to help! It will analyze loans faster than any human could, allowing financial institutions to make more progress on customer onboarding with better underwriting rates.


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    AI algorithms use machine learning, statistical techniques to give financial institutions a competitive advantage over others in the banking industry by shortening loan approval rate which also results in more loan generation for your organization.

    It’s also much more cost-efficient since it doesn’t require huge teams working around the clock to quickly make decisions.

    Loan Process

    Faster Loan Approval Rate

    To get a loan from a bank, financial institutions usually request income verification from potential customers. In doing so, financial institutions usually need at least 10 days to verify income and get back to borrowers. However, with Automated Financial Statement Analyser powered by Artificial Intelligence and Machine Learning technology, within seconds institutions can analyze creditworthiness in just one click. Faster approvals lead to higher ROI which leads to increased profitability for banks and other lending institutions.

    Improved Customer Experience

    Still many financial institutions have been using tedious manual methods to provide a service that may take days or weeks to complete with no exact turn around time. With a tailored AI-ML solution, institutions will be able to serve their customers in a matter of hours, rather than days. This leads to much happier customers and much higher approval rates for loans and credit card offers, as well as a number of other products offered by the financial institutions. In short : a better customer experience leads to more revenue for financial institutions.

    Higher Credit Underwriting Accuracy

    Traditional methods of approving loans and issuing credit cards for customers is both time consuming and prone to error. The introduction of artificial intelligence and machine learning based automated underwriting tools can provide greater confidence in credit decisions with higher approval rates than ever before. Furthermore, AI powered financial statement analysers can also play a role in reducing fraud by assessing inconsistencies between claims made by individuals applying for credit and those found on their bank statements.