From Years to Weeks: Data Automation

A national non-bank SMB commercial lender was facing a massive compliance hurdle: rename and categorize nearly 400,000 loan application files according to strict naming conventions. Manually, the process was projected to take over two years of full-time work.

Acclarity stepped in with a custom-built automation solution, completing the task with speed and precision—maintaining data integrity, reducing human error, and freeing up the client’s team to focus on what matters most: driving business forward.

KEY TAKEAWAYS

390 K

Renamed and categorized 390,000 loan application files

26 x

Completed project 26x faster than the estimated 2 years it would have taken one full-time employee

96 %

Yielded 96.15% reduction in time, minimizing expected 2+ years to 4 weeks.

100 %

Accurately renamed and categorized 100% of 2,300 random samples

Acclarity delivers data automation solutions that eliminate time-consuming, manual processes—freeing up your team to focus on what drives growth. With precision and speed, we turn workloads into efficient, reliable outcomes in weeks—not years.

THE CHALLENGE

Our national, non-bank SMB commercial lender client was required by law/regulations to rename and categorize their loan application files. Each file needed to be opened and renamed with information, such as applicant name and TIN, within the file name itself. It was estimated the file renaming process would take one full-time employee 2+ years to complete.

ACCLARITY APPROACH

Our Acclarity team categorized and stored files in the client’s server: 283,186 files included note files, and 113,528 files did not include note files. Our team renamed 396,714 total files according to preferences (i.e. with/without note files). We maintained the client’s original folders and respective files, and we created mapping between original and new file names in the server. We used and maintained Python automation files, and finally performed Quality Assessment to ensure accuracy of folder renaming algorithm. Of 2,300 random samples, 100% were renamed and categorized correctly.

RESULTS THAT RESONATE

The client saved 2+ years of time, frustration, and resources. The PDF renaming/categorization process was completed in 4 weeks with automation in Python, compared to its initial estimation of 2+ years, resulting in a 96.15%+ reduction in time at 26x faster completion than first estimated. This allows the client to spend its time focusing on business growth rather than dealing with tedious processes and potential human error. The client can have freedom to prioritize elsewhere and has confidence in the accuracy of the information at-hand.

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