The Real Cost of Payment Fraud for Financial Institutions

For banks and financial institutions, the impact of payment fraud is typically measured by the immediate financial loss from unauthorized transactions, such as card fraud, account takeover, and similar chargebacks.

However, this measure often misses authorized fraud, where a customer is manipulated into approving a payment themselves, and the loss isn't captured the same way.

While these losses are significant, they represent only one part of the overall cost. Financial institutions also face investigation and recovery expenses, operational costs, customer reimbursement, false positives, and regulatory and compliance costs.

To effectively reduce those costs, financial institutions need to understand how fraud affects their business and why traditional approaches focused only on detecting suspicious payments aren’t sufficient.

Read on to learn more about the cost of payment fraud and the strategies you can use to prevent fraud more effectively.

Key Takeaways

• Payment fraud creates both direct and hidden costs for financial institutions
  Beyond immediate fraud losses, banks face reimbursement, investigation and recovery expenses, operational workload, false positives, compliance costs, and reduced profitability.
• Transaction monitoring alone can miss early signs of fraud
  Fraud often develops before a suspicious payment occurs, so analyzing account actions, relationships, and activity patterns can provide earlier and more useful risk signals.
• APP scams and organized fraud networks are driving new challenges for banks
  Social engineering, instant payments, and money mule networks allow criminals to move funds quickly, increasing recovery difficulties and the overall cost of fraud prevention.
• Predictive and real-time fraud detection can reduce losses and operational pressure
  Continuously assessing fraud signals across data sources and channels helps financial institutions identify emerging threats earlier, prioritize high-risk cases, and reduce unnecessary manual reviews and false positives.
• Fraud intelligence sharing can reveal risks that individual institutions can’t see
  Secure collaboration allows banks to identify connections between accounts and coordinated fraud patterns that may remain hidden when institutions rely only on their own data.
• Acoru helps financial institutions move from reactive fraud detection to proactive prevention
  Acoru combines account-level intelligence, AI-powered risk scoring, scam prediction, account classification, and privacy-preserving collaboration to help banks detect fraud risks earlier, reduce operational costs, and prevent losses before transfers are initiated.

What Does Payment Fraud Involve?

Payment fraud is the use of deceptive, unauthorized, or manipulated methods to illegally obtain money through payment channels.

It includes different tactics, methods, and infrastructures, such as social engineering, compromised accounts, fake identities, and networks of connected accounts.

The following trends increase the cost and complexity of fraud prevention:

• Faster payment methods: Instant payments allow criminals to move funds quickly, reducing the time available for detection and recovery.
• Social engineering scams: Customers are manipulated into authorizing fraudulent payments themselves.
• Organized fraud networks: Criminal groups use multiple accounts and identities to hide the movement of illegal funds.

Adding to an already complex situation, traditional fraud controls often detect suspicious transactions only after fraudulent activity has already occurred.

4 Main Types of Payment Frauds

For banks and financial institutions, the most relevant types of payment fraud include:

• Authorized push payment (APP) scams, where customers themselves authorize payments under social engineering or deception
• Card-not-present and eCommerce fraud, exploiting online card payments
• Real-time and instant payments fraud, where irreversibility and speed increase exposure
• ACH, wires, and cross-border transfers, frequently used in business email compromise and invoice scams

Regardless of the type, payment fraud costs can be divided into direct and hidden ones.

Direct Costs of Payment Fraud

The most visible cost of payment fraud is the immediate financial loss. Here are the main direct costs financial institutions face:

1. Customer Reimbursement

Depending on regulations, payment types, and circumstances, financial institutions may be required to reimburse customers affected by fraud.

For example, a customer may be deceived by a fraudster posing as a bank representative and authorize a payment to a fraudulent account. If the transaction meets the applicable reimbursement criteria, the bank may have to return the customer's money, even though the customer authorized the payment.

Reimbursement is quite common in APP fraud where liability is shared. According to the UK Finance Annual Fraud Report, banks returned £354.3 million to APP fraud victims in 2025.

Rules and industry schemes are moving toward mandatory reimbursement for eligible fraud cases, with tight timelines for paying victims and reimbursement limits.

For banks and financial institutions, this means:

• Funding large volumes of refunds upfront
• Absorbing operational overhead to assess claims and vulnerability
• Splitting losses with receiving institutions under shared-liability models

In addition to direct reimbursement, institutions face the risk of complaints, ombudsman escalations, and additional compensation if customers are dissatisfied with how their case is handled.

2. Investigation and Recovery Costs

Every fraud case requires resources. Fraud analysts, compliance teams, customer service, and investigators spend hours reviewing transactions, gathering information, communicating with customers, and reporting incidents.

The longer fraudulent activity remains undetected, the more difficult recovery becomes.

That’s why banks should treat recovery as a selective, risk‑based decision and focus on preventing scams earlier in the customer journey instead of trying to retrieve money once it has started moving.

3. Reduced Profitability Costs

Fraud losses directly affect financial performance. However, the cost grows even more when institutions are required to continually increase spending on fraud prevention tools, operational teams, monitoring systems, and compliance processes.

This combination of rising fraud losses and growing spend on fraud operations gradually drives total costs up faster than income, worsening the bank’s cost–income ratio and making efficiency targets harder to reach and sustain.

Hidden Costs of Payment Fraud

Every confirmed fraud triggers a chain of internal tasks that consume more time and budget than the initial financial loss alone. Below are the main hidden costs financial institutions should know about.

1. Operational Costs

Traditional fraud monitoring systems often generate large volumes of alerts that require manual review. Fraud teams must determine whether activity is legitimate, suspicious, or part of a wider fraud pattern.

As alert volumes increase, the process creates challenges, such as:

• Longer investigation times
• Higher operational costs
• Increased pressure on fraud analysts
• More difficult prioritizing high-risk cases

Without sufficient context, teams may spend a lot of time reviewing low-risk alerts while more complex fraud patterns remain hidden.

2. False Positives Costs

While fraud detection systems can spot suspicious activity, they don’t always distinguish between fraudulent and legitimate transactions.

When customers are incorrectly classified as high risk, financial institutions face additional costs through declined transactions, unnecessary account restrictions, increased customer support demands, and potential damage to customer relationships.

More accurate risk assessments help financial institutions protect customers from fraud while reducing the business costs associated with unnecessary disruptions.

3. Regulatory and Compliance Costs

Payment fraud creates additional compliance costs for financial institutions as regulators continue to introduce stricter requirements around fraud prevention and customer protection.

These requirements “force” banks to invest in systems, technologies, processes, and expertise to ensure they can identify, investigate, and respond to fraudulent activity effectively.

In addition, as fraud schemes change, financial institutions must regularly update their controls, risk frameworks, and operational procedures to address new threats.

Failure to maintain effective fraud prevention measures can create extra costs through regulatory penalties, remediation efforts, increased oversight, and reputational damage.

Why Traditional Payment Fraud Detection Isn’t Sufficient

Traditional fraud prevention systems focus primarily on transaction monitoring. These systems evaluate whether a specific payment appears suspicious based on predefined rules or historical patterns.

However, they provide only a limited view.

Fraud almost never begins with a single payment. In most cases, suspicious behavior develops before the transaction happens, leaving early warning signals that include:

• Changes in important account information
• New devices, beneficiaries, or unusual access patterns
• Unexpected changes in payment activity
• Transferring large amounts of savings to a current account
• Extending credit card limits
• Connections with high-risk accounts
• Multiple accounts showing similar behavior

These signals aren’t actionable on their own, but together, they give a fuller view of account risk. By focusing only on individual transactions, financial institutions miss the broader context behind fraudulent activity.

Therefore, fraud prevention requires a transition from transaction-level detection toward account-level intelligence.

How Can Financial Institutions Reduce the Cost of Payment Fraud?

Financial institutions can reduce losses by identifying risks earlier, improving decision accuracy, and responding more effectively.

An effective fraud prevention strategy should focus on the following aspects:

1. Widening Risk Visibility Across Channels

Account-level risk intelligence provides a broader understanding of customer and account activity by analyzing changes in transaction patterns, unusual access activity, connections with other accounts, and other indicators associated with fraud.

By understanding the full context behind an account, financial institutions can recognize potential risks earlier and take preventive action before funds are lost.

For example, a single transfer to a new recipient may appear legitimate on its own. However, reviewing the account's broader history could reveal an unusual payment pattern and a higher risk.

Continuous account intelligence can strengthen fraud prevention. By continuously analyzing account activity and relationships across channels, financial institutions can identify risk changes as they appear, instead of reassessing the account only when a new transaction is initiated.

This approach helps reduce fraud losses by allowing banks to prioritize higher-risk accounts and improve investigation efficiency.

Worth knowing:

Instead of evaluating risk only at the point of payment, Acoru continuously analyzes account actions, relationships, and interactions across channels to identify fraud risks earlier.

By unifying fraud prevention capabilities within an omnichannel platform, our solution helps financial institutions address multiple fraud types and detection use cases.

2. Combining Real-Time Monitoring with Earlier Warning Signs

With instant payment systems, funds can move within seconds, leaving financial institutions with limited time to detect and stop fraudulent activity.

Real-time monitoring identifies suspicious behavior only at the moment it happens, but on its own, it has no visibility into the risk building up beforehand.

Combining real-time monitoring with earlier warning signs enables financial institutions to continuously assess risk and predict new threats before they lead to financial losses.

Instead of matching a transaction to known fraud patterns, this approach looks at signals across an account’s history to determine whether activity resembles a fraudulent one.

By evaluating these factors together, financial institutions can get a more accurate understanding of risk. This way, they can reduce operational costs by allowing fraud teams to prioritize cases most likely to pose threats.

Worth knowing:

Acoru assigns dynamic, contextual risk scores across accounts and their relationships to help banks identify suspicious patterns that would otherwise lead to financial losses.

Through Acoru’s pre-fraud signals, along with transaction monitoring, online fraud detection, new account fraud prevention, and strong customer authentication, banks can more quickly detect patterns linked with fraudulent activity.

3. Improving Collaboration and Intelligence Sharing

Fraudsters often operate across multiple banks, accounts, and payment networks, using different channels to move funds and avoid detection. This means that individual institutions may only see one part of a much larger fraud pattern.

Secure collaboration and intelligence sharing can help financial institutions detect risks that would remain invisible within their own data.

By combining insights from multiple sources while maintaining privacy protections, banks can recognize relationships between accounts, devices, and behaviors that indicate coordinated fraud.

Collaboration also reduces the time needed to respond to new threats. Instead of each institution discovering fraud patterns independently, organizations can benefit from collective intelligence and adapt their protective measures more efficiently.

Worth knowing:

With Acoru’s Consortium Manager, banks can build real-time account classification networks while keeping sensitive customer information protected. Instead of relying only on internal account data, banks can benefit from collective intelligence to spot fraud patterns and risky accounts that may not be visible within their own systems.

How to Build a More Effective Fraud Prevention Strategy with Acoru

Acoru is an AI-native fraud and scam prevention platform that helps financial institutions move from reactive to proactive fraud detection.

By focusing on continuous account intelligence, Acoru helps financial institutions address the root causes of payment fraud and reduce both the visible costs of fraud management and the hidden ones.

Our unified solution provides banks and financial institutions with:

• Continuous account intelligence: Account actions, relationships, and risk signals analysis along with individual transactions, as well as any other connected data channels to detect fraud patterns earlier
• AI-powered risk scoring: Advanced AI models that assess account risk continuously and detect potential fraud before suspicious payments happen
• Scam prediction and mule classification: Identification of accounts associated with potential victims, money mule activity, or fraudulent behavior to help prevent scams before funds are transferred
• Holistic fraud prevention across channels: Combined fraud prevention capabilities across new account fraud, online fraud, transaction monitoring, and scam detection within a unified platform
• Account activity monitoring: Changes monitored in account activity, payment patterns, and relationships to detect emerging threats faster and reduce reliance on reactive investigations
• Privacy-preserving fraud intelligence sharing: Collaboration between financial institutions and identification of fraud networks across organizations without exposing sensitive customer data
• Reduced false positives and operational costs: Improved detection accuracy that helps fraud teams prioritize high-risk cases and reduce incorrect fraud alerts

Request a demo today to see how you can reduce the cost of payment fraud through account-level intelligence, earlier warning signals, and proactive prevention.

See Acoru in Action

Fraud in Latin America is moving fast, and the institutions keeping pace are the ones rethinking how they detect, share, and act on intelligence. If the challenges discussed in this episode sound familiar, we would be glad to show you how Acoru works in practice. 

FAQ:

1. Why are the costs of payment fraud increasing for banks?

The costs of payment fraud are increasing because of the growth of digital payments, instant payment systems, advanced social engineering scams, account takeover attacks, and organized fraud networks.

2. How can financial institutions reduce the cost of payment fraud?

Financial institutions can reduce the cost of payment fraud by adopting proactive prevention strategies, including a wider view of account-level risk, continuous monitoring of account activity over time, and closer collaboration through fraud intelligence sharing between institutions.

3. What factors contribute to the total cost of payment fraud?

The total cost of payment fraud includes direct fraud losses, investigation expenses, customer reimbursement, compliance requirements, technology investments, operational disruption, and reputational impact.

The overall cost depends on the type of fraud, the payment channel, and the effectiveness of existing prevention measures.

4. How can banks calculate the cost of payment fraud?

Banks can calculate the cost of payment fraud by measuring:

• Direct losses
• Recovery rates
• Investigation expenses
• Compliance costs
• Fraud prevention investments
• False-positive impacts
• Customer-related costs

5. What is the biggest financial impact of payment fraud on banks?

The biggest financial impact of payment fraud varies by institution and fraud type, but major costs typically include lost funds, customer compensation, operational resources for investigations, and investments in fraud prevention systems.