Claims processing · Production
AXA Switzerland detects insurance fraud in real time at first notice of loss using Shift Technology
The problem
AXA Switzerland needed to process claims quickly for customer satisfaction but faced the risk that accelerated handling would increase exposure to fraud — forcing a structural trade-off between speed and fraud prevention.
Workflow diagram · grounded in source
1
FNOL triggers detection
trigger
“check for fraud as soon as first notice of loss (FNOL)”
2
AI fraud model analysis
ai_action
“AI fraud detection for motor and property: More than 100 fraud scenarios, tuned to the Swiss market and AXA's portfolio”
3
Route claims by fraud risk
routing
“honest claims could head straight to processing, handlers wouldn't have to perform additional reviews, and fraud would be stopped immediately”
4
Expert investigation with context
human_review
“Full details on fraud alerts to accelerate AXA's investigations”
5
Continuous real-time re-detection
ai_action
“As new data on any claim is recorded, we can continually run Shift Claims Fraud Detection fraud models, in real time, to discover if the claim has become suspicious over time”
Reported outcome
AXA Switzerland analyzed more than 1 million claims with Shift and stopped over €12M in fraud, freeing its teams to focus on customer satisfaction.
Reported metrics
Claims analyzedmore than 1 million
Fraud stoppedover €12M
Fraud scenarios coveredMore than 100
detection speed at FNOLseconds
Reported stack
Shift Claims Fraud Detection
Source
https://www.shift-technology.com/resources/case-studies/axa-switzerland-insurance-fraud-detection-success
Read source ↗Frequently asked questions
What did this team achieve with this AI workflow?
AXA Switzerland analyzed more than 1 million claims with Shift and stopped over €12M in fraud, freeing its teams to focus on customer satisfaction.
What tools did this team use?
Shift Claims Fraud Detection.
What results were reported?
Claims analyzed: more than 1 million; Fraud stopped: over €12M; Fraud scenarios covered: More than 100; detection speed at FNOL: seconds (source-reported, not independently verified).
How is this claims processing AI workflow structured?
FNOL triggers detection → AI fraud model analysis → Route claims by fraud risk → Expert investigation with context → Continuous real-time re-detection.