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

MeasureBefore / without WexaWith 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

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