Air France Speeds Up Manual Reviews by 70% With FINRECOVRA
How a Global Airline Reduced Fraud Review Bottlenecks Without Compromising Security
Overview
Air France, one of the world’s leading airlines, processes thousands of transactions daily across multiple regions, currencies, and customer profiles.
With increasing fraud attempts and growing operational complexity, their risk team faced a critical challenge:
Manual reviews were slowing down operations — and scaling wasn’t sustainable.
By integrating FINRECOVRA, Air France transformed its fraud detection workflow, reducing manual review workload by 70% while improving decision accuracy and speed.
The Challenge
Manual Reviews Were Becoming a Bottleneck
Air France’s fraud prevention system relied heavily on manual checks for flagged transactions. While effective, it created several issues:
- High volume of flagged bookings requiring human review
- Delays in approving legitimate customers
- Increased operational costs and staffing pressure
- Inconsistent decision-making across teams
At peak times, review queues grew rapidly — impacting both customer experience and revenue flow.
The Goal
Air France needed to:
- Reduce dependency on manual reviews
- Maintain (or improve) fraud detection accuracy
- Speed up transaction approvals
- Scale operations without increasing headcount
The Solution
FINRECOVRA’s Intelligent Risk Automation
FINRECOVRA introduced a multi-layered risk analysis system combining:
- Device intelligence
- Behavioral analysis
- Email & phone risk scoring
- Velocity and pattern detection
- Global fraud data signals
Instead of sending most transactions to manual review, FINRECOVRA:
Automatically assessed risk in real time — and made confident decisions instantly.
Key Features Implemented
1. Real-Time Risk Scoring
Every transaction was evaluated instantly using hundreds of data points.
→ Legitimate users passed through seamlessly
→ Suspicious activity flagged with high precision
2. Automated Decision Engine
Transactions were automatically:
- Approved
- Rejected
- Escalated (only when truly necessary)
This dramatically reduced unnecessary manual checks.
3. Behavioral & Device Analysis
FINRECOVRA identified anomalies such as:
- Unusual booking patterns
- Device inconsistencies
- Suspicious session behavior
This allowed Air France to catch fraud earlier — before payment completion.
4. Smart Review Prioritization
Instead of reviewing everything, teams focused only on:
High-risk, high-value cases that actually required human judgment
The Results
70% Reduction in Manual Reviews
- Massive decrease in operational workload
- Faster processing across all regions
Significantly Faster Approvals
- Legitimate customers experienced fewer delays
- Improved checkout and booking experience
Improved Fraud Detection Accuracy
- Fewer false positives
- Better identification of high-risk transactions
Operational Efficiency at Scale
- No need to expand fraud teams
- Systems handled increasing transaction volumes seamlessly
Impact on Customer Experience
Before FINRECOVRA:
- Customers were delayed or blocked unnecessarily
- Friction in booking flow
After FINRECOVRA:
- Faster approvals
- Smoother checkout experience
- Increased trust in the platform
What Air France Achieved
✔ Reduced manual workload by 70%
✔ Accelerated transaction approvals globally
✔ Improved fraud detection precision
✔ Scaled operations without increasing costs
Why FINRECOVRA
Traditional fraud systems rely too heavily on rigid rules and manual checks.
FINRECOVRA replaces that with:
Adaptive intelligence that learns, analyzes, and acts in real time.
Conclusion
Air France didn’t just optimize fraud prevention —
they transformed it into a scalable, automated system.
By reducing reliance on manual reviews, they unlocked:
- Faster operations
- Better customer experience
- Stronger fraud protection
