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How a Large European Bank Increased Their Daily Underwriting Cases Throughput by 600%.

Key takeaways

  • A large European bank (€800B in assets, 16M clients) cut corporate & SME underwriting turnaround from 2–6 weeks to under 7 days with an end-to-end agentic flow.
  • Daily case throughput rose from under 5 to more than 35 — a 600% increase — while error rates dropped from 9–15% to under 3%.
  • The solution unified financial spreading, KPI analysis, market signals and risk tagging into a single flow, with robust human-in-the-loop protocols.
  • Consistency mattered as much as speed: industry-aware thresholds and standardized memos made assessments comparable across analysts.

The bank at-a-glance

The European bank was looking to increase their productivity in underwriting, as part of a larger mandate to improve operational efficiency.

  • 800 billion EUR in assets
  • 70 thousand employees
  • 35 billion EUR in annual new loans
  • 3,000 branches
  • 16 million clients

Context and challenges

Today, several teams and anywhere between 2 and 6 weeks are spent on 1 underwriting process. Their internal objective was made clear from the get-go: decrease the average processing time per process to 1 week. Today's context:

  • 20K - Est. loan files handled / year for corporate and SME cases
  • 210 - Est. FTEs dedicated to underwriting and credit ops
  • 12 - Average number of stages in the current underwriting process
  • 5-8 - Teams involved in the current underwriting process
  • 2-6 - Weeks, current turnaround, complex cases up to 12 weeks
BEFORE · 12 stages · 5–8 teams2–6 weeks · complex cases up to 12AFTER · one unified agentic flowunder 7 days
the same underwriting process, before and after — 12 hand-offs compressed into one flow

How the bank leveraged FlowX.AI

FlowX.AI proposed and implemented an agentic solution while unifying the whole underwriting process. The agentic solution covers the process end-to-end, automating most of the manual work and ensuring robust human-in-the-loop protocols:

  • Unified Process: Financial spreading, KPI analysis, market signals, and risk tagging in a single flow
  • Real-time Insights: Stacks of AI agents deliver contextual quality insights in real time
  • Faster Underwriting: Decision-ready outputs generated in minutes, cutting turnaround time significantly
  • Consistent Memos: Industry-aware thresholds and standardized memos ensure comparability across analysts.

Outcomes and business impact

Deeper Contextualization: Agents link financial KPIs to the company’s domain code, business model, and seasonality, highlighting what truly matters.

Forward-Looking View: Forecasting and market pulse agents add external and future-oriented signals, shifting the analysis beyond historical numbers.

Consistent Assessments: Standardized thresholds and structured memos ensure comparability across analysts, removing subjectivity.

Risk Visibility: Red flags surface automatically, giving underwriters more confidence in decision-making.

Quantifiable results included decreasing the processing time per application from 15-30 days to under 7 days, error rates dropped from 9-15% to under 3% and throughput of cases per day increased from under 5 to more than 35.

<5 → 35+cases per day — a 600% throughput increase
processing time15–30 days → under 7
error rate9–15% → under 3%
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Your underwriting,at this pace.