Fraud Controls 101

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Fraud poses a significant risk to organizations of all sizes. As a matter of fact, approximately 5% of an organization's revenue is lost to fraud every year. (Source: ACFE, 2024) Implementing robust fraud controls is essential for safeguarding assets, maintaining financial integrity, and ensuring compliance with regulatory standards. This article delves into the importance of fraud controls, the various types available, and how they can be effectively implemented to protect your organization.

What Are Fraud Controls?

Fraud controls are measures and processes designed to prevent, detect, and respond to fraudulent activities within an organization. They form a critical layer of internal controls and range from policy-based preventive measures to technology-driven detection systems.

Effective fraud controls serve three purposes:

1. Deterrence: Making fraud difficult enough that potential fraudsters look elsewhere
2. Detection: Identifying fraudulent activity quickly, ideally before it compounds
3. Response: Containing damage and preventing recurrence once fraud is discovered

The challenge for most finance teams isn't understanding these purposes. It's building fraud controls that actually work when financial data lives across Salesforce, NetSuite, Zuora, and half a dozen other systems.

Types of Fraud Controls

Preventive Controls

Preventive controls aim to stop fraud before it occurs. These controls are proactive measures that help establish a strong foundation for fraud prevention within an organization by analyzing existing trends and leveraging predictive analytics.

Segregation of Duties ensures that no single individual has control over all aspects of a company’s finances. For example, taking on a large financial transaction requires one person to initiate the transaction and another to approve it. This way, the possibility of collusion or unilateral fraud is minimized. This method can flag potential collusion attempts and effectively prevent major fraud.

Authorization Controls require management approval for transactions over a certain threshold, reducing the risk of unauthorized activities. For instance, setting a policy where any expense over $10,000 requires multiple managerial approvals mitigates unauthorized spending. This method can reveal unauthorized purchases and lead to increased overall expenditure visibility and accountability.

Access Controls restrict access to systems and data based on user roles, ensuring that only authorized personnel can perform certain functions. Ensuring there are multiple employees reviewing transactions at various stages minimizes the potential for fraudulent activities. 

Detective Controls

Detective controls are designed to identify and uncover fraud that has already occurred. These controls help organizations respond quickly to fraudulent activities, minimizing damage.

Reconciliations, such as regularly comparing internal records with external statements, help identify discrepancies. Conducting reconciliations can reveal unauthorized transactions, which may be a result of embezzlement.

Audits and Reviews involve periodic internal and external audits that examine financial records and processes in accordance with requirements for signs of fraud. These audits can allow a company to take corrective action and tighten inventory controls.

Data Analytics utilizes software tools to analyze financial data for patterns indicative of fraud, such as unusual transaction volumes or irregular timing. For instance, employing advanced data analytics to monitor transaction patterns in an e-commerce company can detect refund scams. This method can flag unusual refund patterns, leading to the detection of fraudulent returns and prompting further investigation and resolution.

Corrective Controls

Corrective controls address issues after they have been detected, aiming to rectify problems and prevent future occurrences.

Error Correction Procedures establish clear processes for correcting errors identified through detective controls, including documentation and approval of corrections. For example, if an internal audit reveals several accounting errors, a company may create a detailed error correction protocol to ensure timely and documented correction of discrepancies, preventing recurrence and improving overall financial accuracy.

Process Improvements involve continuously refining and improving controls based on findings from audits and reviews to prevent recurrence of identified issues. Identifying weaknesses in different financial processes can lead to redesigning the process and implementing stronger controls.

Why Traditional Fraud Controls Fall Short in Multi-System Environments

Here's what fraud looks like in a growth-stage B2B company:

A customer success manager issues a credit memo for $8,000 in your billing system to resolve a "service issue." There's no corresponding ticket in your support system. No one checks because the credit is below the $10,000 review threshold. The same CSM has issued 15 similar credits in the past three months to different customers. Each one is below the threshold. Each one lacks a support ticket. The pattern is obvious if you look at all 15 together. But your monthly credit memo review samples 20% of transactions, and none of these happened to get selected.

Or this: A sales rep closes a deal at 11:47 PM on March 31. Commission gets calculated based on Q1 close date. The order doesn't actually flow to NetSuite until April 1 because of overnight batch processing. On April 2, the customer calls to change terms. The rep modifies the order in NetSuite. Your Q1 revenue number included a deal at terms the customer never agreed to, but it'll take until the Q2 audit to discover it.

Traditional fraud controls assume:

• Transactions happen in one place
• People with fraud capability have fraud authority (they don't, they have admin access to disconnected systems)
• Periodic review is sufficient (it's not when fraud is designed to avoid your review schedule)

How Modern Fraud Controls Actually Work

Effective fraud controls in multi-system environments operate on different principles:

100% data coverage instead of sampling. When fraud exploits small discrepancies across many transactions, sampling-based audits miss it by design. You need systems that compare every Salesforce booking to every NetSuite order to every billing event, not just the 20% you happened to sample.

Real-time detection instead of periodic review. Continuous monitoring means fraud gets flagged during the quarter when you can actually correct it, not during the audit when your only option is explaining it.

Pattern detection instead of rule checking. A single $500 discount doesn't trigger alerts. Ten $500 discounts to different customers from the same rep over two weeks is a pattern. But you can't see patterns if you're only looking at one transaction at a time.

Cross-system audit trails instead of system-specific logs. When an order gets modified, you need to see what triggered the change, who approved it, and whether similar changes happened before. That trail needs to follow the transaction across every system it touches.

Here's what this looks like in practice:

Instead of monthly reconciliation between Salesforce and NetSuite, you have continuous monitoring that flags any booking where terms don't match immediately. Instead of sampling credit memos during quarterly review, you have automated analysis tracking patterns by rep, customer, size, and timing. Instead of approval workflows that can be circumvented by knowing who's on vacation, you have system-level controls that prevent orders from progressing if they violate parameters.

The goal isn't eliminating human judgment. It's eliminating the need for humans to manually detect fraud by comparing thousands of records across multiple systems.

Leveraging Financial Data Governance for Effective Fraud Control

In the modern financial landscape, leveraging advanced technology is pivotal for robust fraud control. Financial data governance (FDG) platforms have become essential tools in this domain, offering unparalleled capabilities to safeguard organizational assets and ensure compliance.

Complete Data Visibility

One of the significant advantages of financial data governance platforms is the ability to scan 100% of the data instead of relying on sampling. Traditional auditing methods often involve sampling a subset of transactions, which can overlook anomalies and fraudulent activities. However, with comprehensive data governance, every single transaction is scrutinized. This complete visibility ensures that no suspicious activity goes undetected, allowing for more accurate and effective fraud detection.

Automated Monitoring and Real-Time Alerts

Financial data governance platforms automate the monitoring of financial transactions, continuously scanning for irregularities and inconsistencies. Advanced algorithms can detect unusual patterns in real-time, such as transactions occurring outside of normal business hours or large sums being transferred to unfamiliar accounts. Real-time alerts enable organizations to respond immediately, minimizing damage and preventing further unauthorized activities.

Integration with Existing Systems

FDG platforms integrate seamlessly with existing ERP systems and other financial software, enhancing their capabilities without requiring an overhaul of current processes. This integration ensures that data governance policies are consistently applied across all financial transactions, maintaining the integrity and security of data across the organization.

Enhanced Reporting and Compliance

Financial data governance platforms provide robust reporting tools that enhance transparency and accountability. Detailed audit trails document every transaction, noting who accessed or modified data, and when these actions occurred. These reports are invaluable for regulatory compliance, making it easier for organizations to meet audit requirements and demonstrate adherence to financial regulations. The enhanced visibility and accountability provided by FDG platforms improve fraud detection capabilities and strengthen overall accuracy.

Predictive Analytics and Machine Learning

By incorporating predictive analytics and machine learning, financial data governance platforms can not only detect current fraud but also predict and prevent future fraudulent activities. These technologies analyze historical data to identify patterns that precede fraudulent behavior, enabling proactive measures to mitigate risks before they materialize. This forward-looking approach transforms fraud control from a reactive to a proactive strategy, significantly enhancing an organization's ability to protect its assets.

Advanced Fraud Control Strategies

Leverage AI for pattern detection. AI can identify unusual patterns that traditional methods miss. Predictive analytics and anomaly detection let you review 100% of financial data instead of samples, catching fraud that would otherwise slip through.

Cultivate a culture where fraud gets reported. Whistleblower programs work when employees trust they can report suspicious activity without retaliation. Organizations that support protected whistleblowing have demonstrably lower internal fraud rates.

Train employees on actual fraud risks. Generic "don't commit fraud" training is useless. Training that shows employees what fraud looks like in their specific role, what red flags to watch for, and how to report concerns actually works.

Ensure board-level oversight. Fraud risk management can't be delegated entirely to finance. Regular board updates on fraud controls, vulnerabilities, and incidents keep oversight active and ensure adequate resources.

Establish cross-functional fraud risk committees. Including finance, IT, operations, and legal in regular fraud control reviews ensures comprehensive coverage. IT knows where system access could be exploited. Operations knows where process gaps exist. Finance knows where the money flows.

FAQs About Fraud Controls

What are the main types of fraud controls?

The three primary types are preventive controls (stopping fraud before it occurs through segregation of duties, authorization requirements, and access controls), detective controls (identifying fraud that's already happened through reconciliations, audits, and data analytics), and corrective controls (fixing issues and preventing recurrence through error correction procedures and process improvements).

How can we continuously improve fraud controls in an evolving threat landscape?

Continuous improvement requires regular audits that actually change processes based on findings, leveraging predictive analytics and machine learning to identify emerging patterns, integrating technology platforms that provide real-time visibility, fostering a culture where fraud gets reported, and staying current with fraud prevention technologies and strategies in your industry.

What technologies are most effective for detecting and preventing fraud in real-time?

AI-driven analytics, machine learning algorithms, and comprehensive financial data governance platforms detect fraud in real-time by identifying unusual patterns and anomalies, providing immediate alerts, and ensuring complete data visibility across systems. These technologies can monitor 100% of transactions rather than samples.

What are key fraud indicators CFOs and Controllers should monitor?

Watch for unusual transaction patterns (transactions outside normal hours, repeated transactions just below approval thresholds), discrepancies between internal records and external statements, unauthorized access attempts, modifications to closed periods, credit memos without corresponding support tickets, and any pattern that represents normal activity for a single transaction but abnormal activity in aggregate.

How do segregation of duties and role-based access controls work together?

Segregation of duties divides critical tasks among multiple people so no single person can commit fraud unilaterally. Role-based access controls limit system access based on job responsibilities. Together, they ensure that even if someone wanted to commit fraud, they lack both the authority and the technical access to complete the transaction without others being involved. The weakness is cross-system scenarios where different people have administrative access to different parts of the same business process.

How often should we reconcile financial data to detect fraud?

The frequency depends on transaction volume and risk exposure. High-volume businesses benefit from daily or even real-time reconciliation of critical processes like order-to-cash. Monthly reconciliation is minimum viable for most organizations, but sophisticated fraud is often designed to exploit the gaps between monthly reviews. Continuous monitoring provides the best fraud detection.

Broadening the Scope of Fraud Controls

Fraud controls should not be static. They must evolve with the organization and emerging threats. Here are some advanced strategies for effective fraud control:

Leveraging Technology

• Artificial Intelligence (AI) and Machine Learning: AI can identify unusual patterns and behaviors that traditional methods might miss. Through AI-powered predictive analytics and anomaly detection, a company can review and assess the entirety of its financial data, minimizing fraudulent activities.
• Complete Data Scanning: Utilizing financial data governance platforms to scan 100% of transactions, rather than relying on data sampling, ensures comprehensive monitoring and fraud detection.

Cultivating a Culture of Integrity

• Whistleblower Programs: Encourage employees to report suspicious activities by implementing secure and anonymous reporting mechanisms. Organizations that cultivate a culture where whistleblowing is supported and protected tend to have lower instances of internal fraud.
• Training and Awareness: Regularly train employees on fraud risks and controls. Awareness programs help employees recognize and report fraudulent activities, creating a trustworthy work environment.

Enhancing Governance and Oversight

• Board Involvement: Ensure that the board of directors is actively involved in overseeing fraud risk management. Providing regular updates and detailed reports to the board can enhance oversight and accountability.
• Cross-Functional Fraud Risk Committees: Establish committees that include members from various departments (e.g., finance, IT, operations) to regularly review and update fraud controls. This ensures a holistic approach to fraud risk management.

The Bottom Line on Fraud Controls

Effective fraud controls protect your organization from financial loss, reputational damage, and regulatory penalties. But "effective" means fraud controls that work in your actual environment, with your actual systems, against your actual fraud risks.

Textbook fraud controls assume transactions happen in one place, one person commits fraud alone, and periodic review is sufficient. None of those assumptions hold in modern B2B companies where financial data lives across multiple systems, access is distributed across teams, and fraud is designed to avoid your review schedule.

Modern fraud controls require continuous visibility across systems, real-time detection of anomalies, and automated monitoring that scales with transaction volume. Technology doesn't replace human judgment in investigating and responding to fraud. It eliminates the impossible task of manually detecting fraud by comparing thousands of transactions across disconnected systems.

The companies that get fraud controls right don't think about them as compliance checkboxes. They think about them as the infrastructure that makes trustworthy financial data possible, which in turn makes confident decision-making possible.

Your fraud controls should give you confidence that the revenue numbers you report are accurate, the transactions in your systems actually happened, and the audit won't uncover fraud you should have caught. If you can't say that with certainty, it's time to upgrade your fraud controls from reactive to proactive.

Safebooks helps Controllers and VPs of Finance at growth-stage B2B companies build fraud controls that actually work in multi-system environments. Our platform provides continuous monitoring across Salesforce, NetSuite, and billing systems, giving finance teams complete visibility into bookings, orders, billing, and revenue recognition. If your fraud controls rely on periodic review and sampling instead of continuous monitoring and complete data coverage, let's talk.