Blogs
bank statement analyzer
fraud detection
underwriting
risk assessment

Why your digital lending program needs an automated bank statement analyzer

Chitwan Kaur   /    Content Specialist    /    2022-09-13

LinkedInLinkedIn

Bank statement analysis is a part of credit underwriting in lending. Bank statement analysis involves an in-depth evaluation of the borrower’s bank statement to ascertain their intent and ability to repay the loan.

The process involves parsing bank statement details such as balance, withdrawals, deposits, investments, prior EMI payments, any interests earned, etc. Bank statement analysis helps lenders gain insight into any unfavourable activity like cheque bounce or late payment fees. All these data points help the lender draw up a confidence score based on which they can decide whether or not to disburse the loan and how to price risk.

Why automated bank statement analysis is necessary

In a traditional set up, bank statement analysis would be carried out manually by scanning excel sheets. Such a process is prone to errors and can be very time consuming. 

Technology providers have automated this process. Now, bank statement analyzers can read PDFs uploaded by customers and draw insights pertaining to their creditworthiness. They come bundled with optical character recognition (OCR) and other screen scraping tools to reduce the time and resources needed for analysis and check for fraud. 

Bank statement analysis in a digital lending journey

Digital lending utilizes several data points – traditional and alternative – to underwrite a customer. Bank statement analysis helps retrieve traditional data like salary, turnover, average balance, cash flow, existing debt and obligations, investment and insurance. 

These insights form the heart of credit underwriting. Digital banks statement analysis allows for improving traditional underwriting by incorporating AI/ML capabilities and conducting a multi-factor analysis of payment histories, credit appetite and transaction habits. These insights can be paired with alternative, device-sourced data to gain deeper insights into the customer’s intent and ability to repay a loan. 

How do automated bank statement analyzers work?

There are two parts to automated bank statement analysis – a) data extraction and b) analysis. 

  • Tools of bank statement extraction

Digital lenders can use various methods for fetching bank statement data. Each tool however, comes with varying degrees of precision and ease of use for the customer.

  • Manual PDF upload

Customers can share their bank statement details by uploading a PDF of the bank statements for the required time period at the relevant point during the customer journey.

But, PDFs of bank statements can be easily tampered with. Customers can manipulate information like bank balances, instances of cheque bounce, etc in a fraudulent attempt to improve their chances of securing a loan.

  • Netbanking

Customers can share their bank statements by way of netbanking. This involves sharing their netbanking details and allowing the lender to fetch the statements.

This method is a lot less prone to manipulation. However, customers are often hesitant to share these sensitive details.

  • Account Aggregator 

The account aggregator framework is a sophisticated tool of financial data extraction that can be used to secure bank statement details of the customer. The customer need only give their consent to pull their bank statement data right from the source — their bank.

This method has proven to reduce the instance of fraud and give a boost to customer experience, thanks to its seamlessness. We have written extensively about how the account aggregator framework will revolutionize lending here, here and here

Value proposition of an advanced bank statement analyzer

Better user experience

Automated bank statement analysis can reduce drop-off rates during customer journeys. Seamlessly integrating financial data extraction tools into the user journey keeps customers engaged throughout the entire process, increasing the conversion rate.

Improved underwriting

Automated bank statement analysis assists with quality risk assessment. By using state-of-the-art data sourcing tools like account aggregation, lenders can significantly reduce the instance of fraud. Moreover, digital bank statement analysis can be aided by alternative insights as well, resulting in enriched data to be used for risk assessment.

Reduction in costs

Automating bank statement analysis for all their customers can help lenders achieve scale and reduce overall costs of underwriting.

FinBox BankConnect 

FinBox BankConnect makes the underwriting process quick and error free. It allows customers to share their bank statements, and then enriches this data to share it with the lender. 

Account Aggregator

FinBox BankConnect comes with an Account Aggregator integration, making bank statement collection smooth and hassle free. Since it fetches the bank statement data in a secure manner from the source, it diminishes the chances of fraud. 

Flexible integration

This bank statement analyzer can be integrated into the digital lending journey through APIs, SDKs and dashboards across various platforms like iOS, Android and web.

High level of data privacy

FinBox BankConnect functions with an acute focus on customers’ data privacy. Its Account Aggregator feature is entirely consent-based and secure.

How it works

Consider the following user journey:

The selection of Account Aggregator can be substituted for netbanking or manual PDF upload. When a customer chooses netbanking, they are redirected to a screen prompting them to share their netbanking details. The bank statements are fetched automatically from the customer’s bank account.

Alternatively, when the customer selects the manual PDF option, they are required to upload a PDF file of their previous months' bank statements during the user journey. FinBox BankConnect parses this data and enriches it with proprietary and/or third-party insights.

Impact of FinBox BankConnect

Conversion

FinBox BankConnect helped arrest drop-off rates during onboarding by 40%.

Fraud detection

FinBox BankConnect has improved fraud detection for customers significantly. Since its Account Aggregator integration alone, it has helped reduce fraud by 45%.

Click here for detailed press coverage of the FinBox Account Aggregator report.

Faster TAT

As many as 83% of the applications were processed in under 5 minutes. Moreover, eight in every 10 applications were processed within five minutes. 

Better customer experience

FinBox BankConnect users noted a 50% reduction in the number of queries.

Improved net promoter score 

The net promoter score of platforms using FinBox BankConnect increased by 70%. Net promoter score is a metric derived from a survey of customers to rate the likelihood of recommending the company or product.

Conclusion

Evaluation of financial information derived from bank statements is at the center of risk assessment. Digitizing and automating bank statement analysis can help cut down on turnaround time, improve fraud detection, reduce costs, and result in better conversions. FinBox BankConnect has helped lenders optimize underwriting for more precision by enriching this core data alternative insights.