Stop the Copy-Paste: AI Collects Data From One Source to Populate Another

Re-entering the same information across multiple systems is tedious, no matter what industry you’re in. Whether you’re populating claims forms or pulling repeat information from a document to a report, extracting and inputting data is more repetitive than most people would like! Whether it’s copying a paragraph or reformatting a date, reproducing data is a drain on your time. It’s also prone to errors, a costly part of the audit or discovery process, and tedious for the user. 

Despite the advent of AI, most fintech, insurance, lending, and compliance organizations are still moving information manually. Whether it is posting old data to a new form or rearranging inputs to file a claim, today’s AI tools are capable of more than you think! AI can collect data from one source and populate another – making your job that much easier. Here’s how it works:

Intelligent Data Population with AI

When you take data from one place to another, you often spend a few seconds thinking about what the format requires – are they looking for a date? What format should the date be? Did we answer this last time? Where did I put that document? 

You then go digging through folders, inboxes, or old submission, all while trying to keep the date or answer you’re looking for top of mind. This isn’t easy in the era of Slack messages, emails, and texts, where the mental effort of task switching can drag a small task out for hours. Once you find the information you need, you might still need to reread the form, pull out the information information, or save the pdf before rewriting it to match the standards of the new form. 

What was once a simple task has now become a lingering issue – and one that many users don’t realize can be solved with AI. With faster cycles of review, correction, and follow up, the time saved ends up shaving off exponential amounts of time. 

Automate Data Population with Natural Language Processing and Agent-Based AI

AI can fill forms for you, but what’s under the hood? In previous years, methods of Optical Character Recognition (OCR) converted images to text via probabilities – “there’s a vertical line and a short horizontal line, which could be an I, 1, or T. Given the specific combination of pixels in this pdf, the most probably character is the letter T.” The trouble with OCR is that it doesn’t understand what the letters mean. Natural Language Processing is a more modern digitization system that works to understand text, attach meaning to it, and work out the relationships between ideas. So if the human user would say “are they looking for a date? What format should the date be? Did we answer this last time? Where did I put that document?” NLP would mimic the process, detecting formatting rules, reading character limits, and adapting tone. 

The addition of agentic AI makes the process even smoother. Agentic AI employs AI “agents” in singles or groups to do tasks for you – for example, fill in questions 1-12, confirm the numbers, and craft the narrative. Together with NLP, agentic AI can plan and execute workflows, fill in forms, and shave hours off of your workflow – for a smoother, easier “copy and paste.”