İşbank cuts credit proposal processing time from 354 minutes to 4 with DefineX generative AI

İşbank deployed Large Language Models & Generative AI for Credit Underwriting & Lending in Commercial & Corporate. As reported by DefineX: 354 to 4 minutes processing time per credit proposal.

Maintained by Peter Korpak, Lead EditorHow evidence is checked
354 to 4 minutesProcessing time per credit proposal
114 FTEFTE-equivalent value within 7 months
5,000 to almost 200,000Customers with expert-level assessments

Source-reported figures (cited source: DefineX)

What İşbank was trying to fix

İşbank aims to deliver fast and reliable access to financing for commercial clients, a key priority in maintaining its market leadership. Its customer and proposal data was dispersed across multiple systems, the expanding commercial portfolio increased demand on expert analysts, and credit officers needed better tools to interpret risk indicators and reduce review cycles between branches and headquarters. These areas created an opportunity to modernize credit decisioning and enhance productivity.

What İşbank deployed

İşbank launched Credit360, a centralized platform that unifies dispersed data into a single, ready-to-use interface to streamline credit assessments. DefineX led the transformation through project management, solution design and AI development, consolidating and standardizing customer and proposal data from multiple systems and co-creating the interface with credit teams through workshops. Generative AI was applied to the consolidated data to automate key steps and deliver actionable insights for credit officers. Feedback loops prioritize high-value enhancements so the platform evolves with business needs.

Results

Automating 13 key data preparation and interpretation tasks reduced processing time from 354 minutes to 4 minutes per proposal, across nearly 120,000 cases annually. Generative AI models on financial and interbank data eliminated 1.5 hours of manual effort per proposal, generating 114 FTE in value within 7 months. Advanced analytics now extend expert-level assessments from 5,000 large customers to almost 200,000 across the full portfolio.

Key Takeaways

  • Consolidate dispersed data into a single environment before layering generative AI on top of it.
  • Co-design the interface with the credit teams who will use it and keep feedback loops running to prioritize improvements.
  • Automate data preparation and interpretation tasks, and use analytics to extend expert-level assessments beyond the largest customers.

Evidence for İşbank's Credit Underwriting & Lending deployment

Reported outcome metrics
3 cited below
Cited source
DefineX
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