Aashish Mehta
Extraction alone isn’t enough—and here’s why.
AI-powered data extraction is everywhere in financial services. It’s fast, flashy, and often the first step companies take toward automation. But too often, that’s where they stop.
In our latest article, “Beyond Extraction: Why Normalizing Financial Data Is the Key to Real Automation ROI,” CEO Aashish Mehta explains why stopping at extraction leaves you with incomplete automation, messy data, and no real ROI.
Key Highlights
- Inconsistent labels (like “Total Sales” vs. “Total Revenues”) make it impossible to compare or analyze data across sources.
- Normalization—not just extraction—is what turns raw outputs into actionable, reliable information.
- Traceability and trust are essential in finance. You need to know where every number came from—and be able to prove it.
- True automation means clean, standardized, ready-to-use data—not a pile of raw fields your team still needs to fix.