Extracting key information from PDFs is a persistent challenge for insurers and banks, especially when documents are long, inconsistent, or produced in high volume. Manual review slows down processes, increases operational costs, and delays critical activities like underwriting, claims analysis, and model validation. See how SAS Viya’s Computer Vision can automate PDF data extraction to reduce bottlenecks and improve scalability. You’ll see two practical demos: single‑policy feature extraction for targeted insights and a trained, multi‑PDF batch workflow for large‑scale processing. You'll learn how these capabilities help financial organizations accelerate turnaround times, improve accuracy, and modernize document‑driven workflows.
What if one of the biggest risks in financial models isn’t the math—but the documents behind them? This session reveals how messy, unstructured data like PDFs, emails, and scanned contracts create major bottlenecks in banking and insurance workflows—and how SAS Viya can transform them into scalable, auditable pipelines. Through a hands-on insurance use case, you’ll see how document intelligence can automate extraction, validation, and traceability, drastically reducing manual effort and human error. If you want a glimpse into how AI, low-code workflows, and document intelligence can modernize risk and audit processes, this is a story worth watching.
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