Data Analytics for Fraud Detection
Turning Insights into Prevention
Why Use Data Analytics in Fraud Detection?
- Modern fraud is fast, digital and often hidden in plain sight.
- Traditional audits catch less than 20% of fraud.
- Data analytics offers a proactive, scalable and pattern-based approach to detection.
Key benefits:
- Real-time detection of anomalies
- Coverage of 100% of transactions (not just samples)
- Identification of hidden relationships between entities
- Better fraud prevention through predictive modelling.
Popular Analytical Techniques for Fraud Risk
|
Technique |
Use Case |
|
Benford's Law |
Spot fabricated numbers in financials or expenses |
|
Duplicate Testing |
Identify duplicate invoices, vendors, or payments |
|
Outlier Analysis |
Spot transactions outside normal thresholds |
|
Trend Analysis |
Compare trends in revenue, expenses, or approvals |
|
Link Analysis |
Connect employees to vendors, bank accounts, or addresses |
|
Text Mining / NLP |
Detect high-risk language in emails, expense justifications |
|
Machine Learning Models |
Score transactions based on historical fraud cases |
Real-World Use Cases (UAE Context)
- Banking: AML and suspicious transaction monitoring using pattern deviation
- Real Estate: Detecting payment manipulation, forged cheques, or overbilling
- Retail: Inventory shrinkage linked to point-of-sale fraud
- Government: Monitoring public procurement and tender irregularities
How to Get Started
- Baseline your risks – Map fraud risks across functions (e.g., procurement, payroll, GL)
- Integrate data – Pull from ERP, bank feeds, email logs, approval workflows
- Automate tests – Start with simple rules, then scale to machine learning
- Train the team – Combine forensic, data and audit capabilities
- Act on alerts – Route alerts to fraud response teams with SLA
Crowe’s Support in Analytical Forensics
We support clients with:
- Fraud analytics dashboards (Power BI/Tableau)
- Transaction testing scripts for ERPs like SAP, Oracle, Microsoft
- Link and pattern analysis for related-party or shell entity detection
- Red flag indicators automated in approval workflows
- Audit and forensic staff training in data-led investigation
Coming Next Week:
Join us in Week 8 as we wrap up the series with “Fraud in the Real World: Industry-Specific Case Studies”, sharing practical examples and lessons across sectors like real estate, healthcare, retail and more.
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