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AdebiyiDeborah/A-Data-Driven-View-of-Nigeria-s-Digital-Payment-Landscape.

Domain:

socioeconomicdigital infrastructure

Record type:

project
Creator:
Ade
Host:
Fraud rarely announces itself through a single transaction. More often, it emerges through patterns: repeated activity within minutes… # A-Data-Driven-View-of-Nigeria-s-Digital-Payment-Landscape. A professional fraud and AML analytics project built around **2,500 financial transactions**, designed to identify fraud concentration, quantify financial exposure, monitor recovery performance, and provide actionable risk intelligence for financial institutions. ## Project Overview Financial fraud is difficult to understand from raw transaction records alone. This project transforms transaction-level data into an analytical dashboard that helps stakeholders identify where fraud occurs, quantify its financial impact, and determine where fraud-prevention efforts should be concentrated. The project combines an **Executive Overview Dashboard** with a **Fraud Risk Analysis Dashboard**, providing both strategic and operational perspectives. The analysis covers: * Fraud exposure and loss * Payment channel risk * Geographic concentration * Merchant category risk * Transaction amount patterns * Fraud trends over time * Hourly and daily fraud activity * AML-flagged transactions * Funds recovery * Risk-management recommendations --- ## Project Objectives The primary objectives of this project are to: 1. Measure overall fraud exposure. 2. Identify high-risk payment channels. 3. Analyze fraud concentration by geography. 4. Identify high-risk merchant categories. 5. Examine fraud trends over time. 6. Analyze fraud activity by transaction amount. 7. Identify high-risk periods using hourly and daily patterns. 8. Track recovered funds. 9. Identify AML-flagged transactions. 10. Translate transaction data into actionable fraud-prevention recommendations. --- ## Key Metrics | Metric | Value | | ------------------------------ | -----------: | | Total Transactions | **2,500** | | Total Transaction Value | **₦517.41M** | | Fraudulent Transactions | **75** | | Fraudulent Transaction Value | **₦130.50M** | | Fraud Rate | **3. …

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github.com

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