INSURANCE
Underwriting analytics coworker
Underwriters spent most of their time gathering data across systems and applied guidelines inconsistently. Wexa built a coworker that prepares the case and recommends a decision.
- underwriting time
- consolidated risk view per applicant
- of cases checked against embedded guidelines
- CLIENT
- Retail and commercial insurance group
- REGION
- Confidential
- WHEN
- 2025
- ENGAGEMENT
- Proof of concept
- WEXA COMPONENTS
- Data sourcing agents · risk scoring · guideline engine · decision dashboard
01Case 27
The challenge
- Manual searches across internal and external sources
- Variation between underwriters' interpretations
- Application spikes causing delays
- Routine work crowding out complex cases
What Wexa built
- Automated sourcing of applicant data from internal and external systems
- Risk scores and anomaly flags from historical patterns
- Embedded underwriting guidelines for consistent decisions
- Decision-support dashboard; the underwriter makes the final call
02Case 27
How it runs on Wexa
03Case 27
Solution architecture
04Case 27
Results
| Measure | Before / without Wexa | With Wexa |
|---|---|---|
Underwriting capacity for the same application volume | 30 underwriters | 18 underwriters |
Annual cost of the process | $2.7M | $1.6M |
Time to implement the AI solution | 6 months | 6 weeks |
AI build cost (one-time) | $480K | $44K |
AI operating cost per year (models, infrastructure, upkeep, platform) | $312K | $166K |
Total AI cost in year 1 | $792K | $210K |
With Wexa
net annual value to the client after Wexa's own operating cost
faster to implement
lower AI operating cost
less AI spend in year 1
"The Wexa Underwriting Analytics Coworker gave our underwriters a new level of clarity and speed. We issued policies faster while improving the quality and consistency of our decisions."
More case studies
All 43 casesInsurance
Claims processing · insurer
−60%
claims processing time
Claims processing time −60%; 70%+ extraction accuracy at launch
Read the caseFinancial services logistics
ATM cash-out prediction · cash logistics
~3 days
to build and deploy the working POC
Working POC built in about 3 days for the client's CTO
Read the caseFacilities and logistics
CCTV safety incidents · facilities operator
~25 FPS
detection on a CPU, no GPU needed
~25 FPS detection on CPU; full pipeline at 1080p with p95 108 ms per frame; every event human-reviewed
Read the caseWant results like these?
Book a 30-minute call and we will map your workflow to this case.