United KingdomFinance and insurance2026 – ongoingLloyds Banking Group
Pega GenAI extraction and drafting for commercial banking cases
Lloyds reported 99% extraction accuracy after adding generative AI to asset-finance cases
Problem
Commercial banking staff manually copied PDF data into case forms. Complaint handlers also read lengthy correspondence before drafting responses.
Approach
Lloyds redesigned its Pega workflow and used GenAI Connect to extract fields from structured PDFs. It extended generative AI to complaint summaries and draft letters, with employees approving output before clients received it.
Results
Takeaway
Asset-finance savings were reported after deployment; complaint-handling savings remained projections.
Categories
- Size
- Large enterprise
- Industry
- Finance and insurance
- Business function
- Production and qualityCustomer service
- Innovation type
- Process innovation
- AI technology
- Generative AI
- Adoption
- Vendor solution
- Evidence
- Vendor case study
Sources
Source summaries
Pega reported 99% extraction accuracy and over 500 hours saved across over 5,000 asset-finance cases. Employees reviewed complaint summaries and draft letters; the associated time savings were projected.
Full details are in the original sources.
