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How to Eliminate Data Entry From Loan Underwriting

Mary Ellen Biery
March 28, 2018
Read Time: 0 min

Processing, underwriting, and approving smaller loans for businesses can be as costly for banks and credit unions as handling larger loans, in large part, because extensive data entry is involved in each stage of the process. Financial institutions rightly concerned about being able to capture this business efficiently should look to reduce or eliminate data entry as much as possible.

This issue of eliminating data entry is especially relevant as community banks and credit unions look to grow revenue and earnings by recapturing some of the small business lending that smaller institutions have ceded to large banks and financial technology firms over the last decade. Indeed, a recent survey of banks and credit unions identified loan growth as the institutions’ top marketing priority in 2018.

In addition, the $700 billion small business lending market in the U.S. is undergoing demographic changes that provide opportunities for efficient and forward-thinking institutions to capture profitable small business loan volume. Baby boomers are retiring and passing on or selling their businesses to younger entrepreneurs, and many of these younger owners expect the ease of Amazon or Uber with the services they use – including banking and borrowing. Banks and credit unions don’t have to be financial technology companies in order to be attractive to these business customers and to boost institutional efficiency and loan profitability.

Instead, by incorporating technology advancements into their lending processes, financial institutions can reduce or eliminate data entry. Data entry in these areas ties up the time of higher-paid commercial lenders – time they could instead spend on developing new business. Manual data entry also lengthens turnaround times for business loan requests and annual renewals, and it introduces erroneous data that creates additional costs and risks for the bank or credit union.

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Here are four ways to eradicate data entry:

Use digital applications. Eliminating data entry from the underwriting process starts as early as the application stage. An online loan application removes the need for a paper application that must be keyed into the system. This begins an efficient loan-review process and also allows business owners to apply after banking hours and without having to make a separate trip to the branch. Furthermore, because the application cannot be submitted until the requested information is provided, an online loan application reduces the amount of back and forth between the applicant and the lender. Each improvement in efficiency during the process can translate into a faster decision for the borrower and less time tracking and keying in data on the part of the lender.

Automate the uploading of financial data. As part of the application process, banks, and credit unions can import information directly from a business borrower’s digital tax returns. The Electronic Tax Return Reader reads the tax return and all of its schedules and then automatically spreads the information with 100 percent accuracy and no human intervention. This saves an average of 20 minutes per tax return for new loans and reviews and reduces data errors associated with manual entry. Other technology allows borrowers to authorize their CPA to securely send tax returns directly to the bank or to authorize credit pulls and the sharing of asset information from more than 9,000 other financial institutions. This prevents the borrower and lender from having to track down and key in all of the information separately. As this financial data is transformed into personal financial statements for the borrowers, loan officers can quickly move on to analyzing the loan application.

Automate decisions on some loans. Technology can also help financial institutions streamline the consideration of and decisions on certain business loans without increasing risk. The bank or credit union determines at a high level what data is required for different loan types and customizes which calculations and rules are applied in the analysis and decisioning process, customizing it to the institution’s loan policy. Credit analysts then receive automated or manual loan-decision recommendations that already have the required documentation generated, further eliminating repeated data entry.

Automate complex loan analysis. For higher-value or more complex borrower applications, banks and credit unions can nevertheless eliminate repeated keying of data during the spreading, analysis and credit memorandum processes. Technology solutions that provide automated financial spreads and ratio calculations, global cash flow analysis, and dynamic narrative analysis ensure decision-makers have the best information to make the right decision efficiently.
By tapping into technology advancements, community banks, and credit unions can eliminate data entry and rely less on staff- and paper-intensive processes. These changes pave the way to place the loan officer back in the role of developing new business loan opportunities and building community relationships, and the credit analyst back in the role of underwriting loans. Business loans that once took weeks can now be decided in days or hours, with fewer data-entry errors and improved staff coordination along the way.

About the Author

Mary Ellen Biery

Senior Strategist & Content Manager
Mary Ellen Biery is Senior Strategist & Content Manager at Abrigo, where she works with advisors and other experts to develop whitepapers, original research, and other resources that help financial institutions drive growth and manage risk. A former equities reporter for Dow Jones Newswires whose work has been published in

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About Abrigo

Abrigo enables U.S. financial institutions to support their communities through technology that fights financial crime, grows loans and deposits, and optimizes risk. Abrigo's platform centralizes the institution's data, creates a digital user experience, ensures compliance, and delivers efficiency for scale and profitable growth.

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