Identifying and Preventing Payment Fraud: 15 Key Data Points

In today’s digital landscape, payment fraud is a growing concern for businesses.

With evolving threats and sophisticated fraud techniques, organizations must leverage the right data points to detect and prevent fraudulent transactions effectively.

In a recent webinar hosted by IOFM and sponsored by apexanalytix, Matthew Morookian, Director of Product Marketing discussed 15 key data points that can help organizations gain actionable strategies to identify and prevent payment fraud.

How Can Businesses Identify and Prevent Payment Fraud? (Quick Answer)

Businesses can identify and prevent payment fraud by monitoring high-risk data points that commonly indicate suspicious activity, including unauthorized bank account changes, mismatched supplier tax IDs, suspicious invoice patterns, and payment approvals outside normal business hours. Fraudsters frequently exploit weaknesses in vendor onboarding, invoice approvals, and payment workflows through tactics like business email compromise, vendor impersonation, and invoice fraud.

To reduce risk, organizations rely on AI-driven detection systems that continuously analyze supplier data, banking details, and transaction patterns. Validating bank account ownership, screening suppliers against sanctions lists, and monitoring approval thresholds are now considered essential controls.

Ultimately, payment fraud prevention is about building a proactive risk management framework that strengthens financial controls and protects supplier payment integrity across the entire procure-to-pay process.

In short: Businesses prevent payment fraud by combining supplier validation, transaction monitoring, automated analytics, and strong payment controls to identify suspicious activity before money leaves the organization.

The Growing Threat of Payment Fraud

Is your business prepared to combat the rising threat of payment fraud?

Fraudulent activities aren’t just a financial drain—they can severely damage your company’s reputation and erode customer trust. With businesses losing millions each year to sophisticated fraud schemes, the challenge is no longer if you’ll be targeted, but when.

How can you stay ahead?

The key lies in real-time data analytics and automated fraud detection tools that identify suspicious activity before financial losses escalate. By taking a proactive approach, businesses can strengthen their defenses and mitigate risks before they turn into costly setbacks.

Understanding the Risks and Challenges

Payment fraud isn’t just an IT or finance problem, it affects the entire organization.

Fraudsters use tactics like business email compromise (BEC), vendor impersonation, and invoice fraud to exploit vulnerabilities. Many businesses still rely on outdated verification methods, making them easy targets.

Addressing these challenges requires a structured approach that includes:

• Increased visibility into vendor payment data
• Automating fraud detection processes
• Strengthening authentication procedures for vendor payments

The 15 Critical Data Points for Detecting and Preventing Payment Fraud

In today’s evolving fraud landscape, proactive detection is crucial.

These insights highlight critical red flags and essential fraud detection measures designed to safeguard your organization against financial threats.

1. Bank Account Ownership Validation – Ensuring the legal entity matches the bank account prevents payments from being diverted to fraudulent or unauthorized accounts. This process involves verifying the registered business name against bank records to confirm ownership and legitimacy.
2. Recent or Frequent Bank Account Changes – Multiple or sudden changes to bank account details can indicate fraud attempts, such as business email compromise (BEC) schemes. Monitoring and validating all account change requests helps prevent unauthorized fund transfers.
3. Tax ID Validation – Verifying the supplier’s tax identification number (TIN) ensures the business is legally registered and helps detect shell companies or fake suppliers attempting to commit fraud.
4. Prohibited or Sanctions List Matching – Screening suppliers against global watchlists, such as OFAC, ensures compliance with international regulations and prevents doing business with entities involved in financial crimes, money laundering, or other illicit activities.
5. Email Address Analysis – Fraudsters often use generic, free, or spoofed email domains to impersonate legitimate vendors. Avoiding group emails, detecting high-risk domains, and ensuring the email address aligns with the supplier’s registered domain add extra layers of security.
6. Address Validation – Verifying supplier addresses helps identify whether a business operates from a legitimate commercial location or a high-risk residential address, PO box, or virtual office commonly linked to fraudulent activities.
7. Phone Number Risk Assessment – Identifying prepaid, burner, or suspicious phone numbers can help detect fraudsters who avoid traceable communication. Suppliers using temporary numbers may warrant further verification before processing payments.
8. Employee Data Matching – Cross-referencing supplier data with internal employee records helps prevent insider fraud. If a supplier’s details match an employee’s address, phone number, or bank account, it could indicate a conflict of interest or fraudulent activity.
9. Benford’s Law on Invoice Numbers – Fraudulent invoices often deviate from natural number distribution patterns. Analyzing invoice numbers using Benford’s Law can help detect anomalies that suggest fabricated or manipulated invoices.
10. First Payment Small Test – Fraudsters often submit a small test payment request before escalating to larger fraudulent transactions. Monitoring initial payments for unusually small amounts can serve as an early warning sign.
11. Approval Threshold Avoidance – Fraudulent actors may keep invoices just below approval limits to bypass extra scrutiny. Identifying suppliers consistently submitting invoices just under these thresholds can help flag suspicious activity.
12. Escalating Invoice Amounts – A pattern of increasing invoice values from a vendor may indicate a fraud scheme in progress. Regularly reviewing supplier billing history helps detect unusual changes in payment amounts.
13. Even Gross Amounts – Fraudulent invoices often contain round-dollar amounts, which may indicate artificially generated or inflated billing. Monitoring for unusually even invoice amounts helps identify potential fraud.
14. Exception Processing Dates – Payments approved outside normal business hours, on weekends, or during holidays can indicate fraudulent activity. Monitoring and restricting after-hours payment approvals adds an extra layer of protection.
15. Credit Percentage Outliers – Suppliers with abnormally high or low credit transactions compared to industry norms may signal fraud risks. Monitoring credit percentage variations helps identify irregularities and prevent financial losses.

Leveraging Data & Taking Action Against Fraud

Modern fraud prevention relies on automation and integrated data sources to analyze vendor s and identify suspicious transactions in real time.

Businesses that implement data-driven fraud prevention strategies

• Experience fewer fraudulent payments
• Improved financial security
• Greater compliance with industry regulations

By integrating proactive fraud detection measures, organizations not only safeguard their financial assets but also gain a strategic advantage in risk management.

Conclusion

Payment fraud continues to evolve, but businesses can stay ahead by leveraging the right data points and technologies.

By applying these 15 key insights, companies can detect anomalies, prevent fraudulent transactions, and enhance their financial security. Proactive fraud prevention is no longer optional—it’s essential for long-term success.

To learn more about how to identify and prevent payment fraud, explore apexanalytix’s fraud detection solutions. Schedule a demo and take the next step in securing your payments.