Enhancing Fraud Detection in Digital Payment Services with AI and Data Analytics
DIGITAL PAYMENT SERVICE
At a glance
Industry
Retail
Challenge
Addressing revenue recovery by identifying false fraud flags and enhancing efficiency in processing flagged orders swiftly.
Success History
At a Glance: Our AI-driven approach with Tableau cut flagged order resolution time by 75% (48h to 12h), boosted accuracy (85% to 95%), and increased revenue recovery (80% to 90%). Automation reduced fraud analysis tasks by 70%, recovered 10% more transactions, and saved 1,000+ hours annually—enhancing efficiency and trust.
Problem Statement:
In the fast-paced world of digital payments, fraudulent transactions pose a significant challenge for merchants. Whenever an order is flagged as potentially fraudulent, a detailed manual analysis is required to evaluate its legitimacy. This process, though crucial, is time-intensive and involves assessing multiple orders, including those from repeat offenders.
The Challenges
For our team, the challenge was twofold:
1.
Revenue Recovery
Ensuring that legitimate transactions falsely flagged as fraud were promptly identified and converted into good revenue.
2.
Efficiency
This labor-intensive process not only impacted operational efficiency but also risked lost revenue opportunities for merchants due to delayed actions on legitimate transactions.
Our Solution
To tackle this issue, we introduced Tableau into our process to leverage its advanced data visualization capabilities.
This allowed our team to analyze historical data and identify patterns in fraudulent activities efficiently. By automating insights and flagging repetitive threats, we streamlined the decision-making process.
This enabled our team to:
1. Accelerating the resolution of flagged orders.
2. Reducing the time spent on repetitive fraud analysis.
3. Improving the accuracy and speed of identifying legitimate transactions.
By automating the visualization of threat metrics, we reduced the manual workload, saved valuable time, and significantly improved the speed and accuracy of our fraud detection process.
Business Outcomes
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Accuracy Improved
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Revenue Recovery Increased
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ART for flagged orders dropped.
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Accuracy Improved in legitimate transactions