Fraud Prevention in the Banking Industry: A Complete Guide

In the banking industry, fraud often starts long before any payment is made, sometimes even weeks before any losses can be detected. For that reason, fraud prevention in banking increasingly relies on assessing behavior and risk signals across channels over time.

Fraud losses in global banking are on track to jump 153%, from $23 billion in 2025 to $58.3 billion by 2030. And the threat keeps changing shape. As banks harden defenses against one fraud type, criminals move to the next: In 2024, UK authorized push payment losses fell 2% while unauthorized cases rose 14%. Fraud didn't shrink. It moved.

That is the limit of fighting fraud, one type at a time. The earliest signals appear across accounts and channels, often weeks before a transaction is initiated.

In this article, you'll learn everything about fraud prevention in the banking industry so you can minimize fraud losses, strengthen compliance, and build a more resilient defense strategy against emerging threats.

Key Takeaways

• Stopping fraud requires more than transaction monitoring

Transaction monitoring fires at the payment, after the fraud is in motion. By then, the victim is groomed, and the mule is ready to receive. Continuous account monitoring, risk-based authentication, and AI classification intervene before a transaction is initiated.

• AI and shared intelligence help banks keep pace with evolving fraud tactics

Fraudsters often attack multiple institutions using the same tactics. Combining AI-driven risk scoring with cross-institution intelligence allows banks to spot emerging threats faster and reduce false positives.

• Cross-channel visibility closes critical fraud gaps

Fraud signals are scattered across digital banking and mobile apps, assisted channels like call centers, IVR, and branches, and payment channels including ATMs, POS, card-not-present, and P2P, as well as external enrichment sources. Connecting them gives banks a complete view of account risk rather than a fragmented view by channel.

• Continuous account intelligence gives banks an advantage

Acoru reads pre-fraud signals before any transaction exists: new payees, profile and limit changes, channel switching, test micro-payments, and reconnaissance logins. Analyzed continuously across channels and counterparties, they let Acoru classify accounts and surface mule networks and scams before a transaction is initiated.

What Is Fraud Prevention in the Banking Industry?

Fraud prevention is the proactive use of policies, technologies, and best practices designed to reduce the likelihood of fraud. These measures include:

• Customer verification and due diligence
• Risk-based controls for account opening
• Device intelligence
• Behavioral biometrics and user behavior analytics
• Transaction monitoring and anomaly detection
• Strong cybersecurity controls
• Employee training and fraud awareness
• Customer education

Common Types of Fraud That Can Be Prevented

Banks and financial institutions face a wide range of fraud threats. Below are some of the most common types of fraud, along with descriptions of how they operate.

1. Authorized Push Payment (APP) Fraud

Authorized push payment (APP) fraud happens when scammers manipulate victims into authorizing transfers directly from their bank accounts using real-time payment systems. Because the payment is approved by the account holder, banks typically have no reason to block it.

In 2024, total APP fraud losses in the UK declined by 2% from the year before, to just over £450 million, and the number of cases dropped by 20%. However, while this type of fraud is becoming less common, the average loss value per case has increased from £606 in 2020 to £663 in 2024.

2. Money Mule Fraud

Money mule fraud involves criminals recruiting individuals to receive and transfer illicit funds through their bank accounts. By moving money through multiple accounts, mule networks make it harder to trace its origin, which increases the risk of large-scale money laundering.

In 2024, 257 financial institutions across 21 countries reported nearly 2 million money mule accounts.

3. Synthetic Identity Fraud

Synthetic identity fraud occurs when criminals create fictitious identities by combining genuine personal information, such as Social Security numbers, with fabricated details like names, addresses, or employment records.

Once established, these synthetic identities are used to open accounts, build credit histories, and eventually commit fraud through loan defaults or large withdrawals.

4. Identity Theft and Account Takeover

Identity fraud and account takeover (ATO) involve the unauthorized use of personal information or compromised credentials to open new accounts, access existing ones, and conduct fraudulent transactions. Studies show that:

• US consumers reported 449,032 cases of credit card identity theft in 2024
• In 2024, account takeover fraud resulted in nearly $16 billion in losses for US consumers

5. Check Fraud

Check fraud involves the use of stolen, altered, or counterfeit checks to obtain funds or make unauthorized payments.

Although check usage has declined, checks remain an attractive target because they are relatively easy to intercept and manipulate. A Federal Reserve survey found that 63% of respondents experienced attempted or actual check fraud in 2024.

5 Effective Strategies for Fraud Prevention in the Banking Industry

Effective fraud prevention requires a comprehensive approach that combines technology, strong policies, employee awareness, and collaboration. Below are some of the most effective fraud prevention strategies you can implement.

1. Adopt Continuous Account-Level Monitoring

Many fraud prevention programs focus on transactions, overlooking the broader account activity that provides important context for fraud detection.

Continuous account-level monitoring helps you detect suspicious patterns by identifying changes in customer behavior and account activity throughout the customer journey.

To support continuous account-level monitoring, look for solutions that can help you:

• Continuously assess account risk: Build a dynamic account risk profile that evolves as new activity, relationships, and behaviors emerge, rather than relying on one-time assessments.
• Monitor accounts across the entire customer journey: Connect activity from online banking and mobile apps, as well as assisted channels such as call centers, IVR, and branches. Also incorporate payment channels including ATMs, POS, card-not-present, and P2P, together with external enrichment sources.
• Detect pre-fraud indicators early: Identify sequences of low-risk events, such as profile changes, new payees, channel switching, or unusual customer interactions, that may indicate an emerging scam.

Worth knowing:

Acoru continuously tracks pre-fraud signals across the customer journey, including:

• Profile and account changes
• New payees and payment preparation activity
• Login patterns and channel switching
• Customer interactions across online banking, mobile apps, branches, and contact centers
• Counterparty behavior and account relationships

2. Strengthen Authentication with Risk-Based Intelligence

Although MFA significantly reduces the risk of unauthorized account access, it cannot stop fraud when legitimate customers complete authentication themselves.

Instead of applying the same authentication challenge to every customer, you should adapt authentication based on continuous account risk, pre-fraud signals, and cross-channel context.

To do this, you need tools that help you:

• Assess authentication risk before login: Evaluate device, behavioral, and account-level risk signals before initiating authentication.
• Apply the appropriate level of verification: Dynamically recommend or trigger authentication methods based on the customer's current risk rather than using the same challenge for every login.
• Continuously reassess risk throughout the session: Update risk scores as new activity occurs, enabling additional verification if suspicious behavior emerges after authentication.

Worth knowing:

Acoru scores and classifies each account before the customer confirms a transaction, prior to 2FA or SCA. This provides a risk read before authentication to match the level of verification to the account's current risk instead of challenging every customer the same way. Its Predictive Challenge Analytics draw on challenge, device, session, and behavioral signals.

3. Leverage Cross‑Institution Fraud Intelligence

Traditional intelligence-sharing typically relies on static blacklists and raw indicators such as:

• Compromised credentials
• Suspicious IP addresses
• Fraudulent phone numbers
• Known mule accounts

While valuable, these indicators become outdated quickly, lack behavioral context, and cannot distinguish between different levels of account risk, such as an unwitting mule account vs a complicit one.

A more advanced approach is to share dynamic account risk classifications using zero-knowledge techniques, allowing banks to gain cross-institutional context without pooling raw customer data.

Worth knowing:

Acoru's Consortium Manager enables financial institutions to collaborate through a real-time, privacy-preserving intelligence network. Rather than relying on static blacklists, it helps you share actionable fraud insights and continuously improve fraud and mule account detection without exposing customer data.

Acoru analyzes accounts across three coverage levels: your own accounts (Level 1), the external accounts your customers transact with (Level 2), and external accounts with no relationship to your customers, reached through optional consortium sharing (Level 3).

Here is what it does:

• Surfaces mule accounts and scam endpoints at other banks from your internal data alone through Levels 1 and 2, with optional consortium sharing that extends coverage to external accounts with no direct relationship to your customers
• Delivers real-time account risk insights and dynamic account classification, enabling institutions to identify threats even in accounts they do not directly monitor
• Supports secure information sharing through privacy-enhancing technologies, including encrypted processing and Zero-Knowledge Proofs, so no PII is exposed
• Integrates with existing fraud detection tools, allowing institutions to collaborate without changing their internal systems
• Helps institutions meet regulatory expectations for collaborative fraud prevention while maintaining compliance with privacy requirements such as GDPR and GLBA

Request a demo today and learn how Acoru can help you stay ahead of emerging fraud threats.

4. Use AI Across Every Stage of Fraud Prevention

AI has become a core component of modern fraud prevention, with 91% of US banks already using it for this purpose.

AI is now core to fraud prevention, and the banks pulling ahead use it to read accounts, not just transactions. Static rules catch known patterns. They miss the slow, cross-channel buildup that precedes a scam or a mule cash-out. Continuous, AI-driven risk scoring closes that gap. It spots unusual behavior earlier, focuses analysts on the highest-risk accounts, and cuts false positives.

Here is what to look for:

• Read accounts, not just events: Account-level models surface the subtle, multi-channel patterns that static rules and single-transaction scoring miss.

• Score risk continuously: Update each account's risk as new behavior arrives, so the classification is ready before a transaction is initiated.

• Keep analysts in control of AI: Use AI to draft dashboards, investigation narratives, and rule changes, with a person approving every output.

• Automate the routine within your policies: Let AI run multi-step investigation and mitigation workflows inside the limits you set, and keep every action auditable.

Worth knowing:

Acoru is AI-native, not analytics bolted onto a rules engine. It scores accounts on continuous behavior and pre-fraud signals, not point-of-transaction events. Its AI capabilities include:

• AI Assistant: Turns natural-language questions into dashboards, investigation narratives, and rule proposals your team approves
• AI Workforce: Runs multi-step investigation and mitigation workflows within the limits you set
• Large Account Model: Reads an account's full behavioral arc to power Continuous Account Classification while keeping every output explainable and auditable

5. Strengthen Internal Controls and Segregation of Duties

Many fraud incidents originate from within organizations. By separating responsibilities among multiple employees, you reduce the likelihood that a single person can initiate, conceal, and benefit from fraudulent activity.

To implement stronger internal controls, you should:

• Require two or more independent approvals for high-value transactions
• Apply the same approval process to changes to customer or vendor records, account closures, and other sensitive activities
• Limit access to systems, accounts, and sensitive information based on employees' job responsibilities
• Review user permissions regularly to ensure they remain appropriate

Worth knowing:

To learn more about the past, present, and future of fraud prevention, watch what Acoru CEO Pablo de la Riva has to say on the topic.

Strengthen Your Fraud Prevention Strategy with Acoru

Fraud signals often emerge hours, days, or even weeks before a transaction is initiated, making point-in-time decisions insufficient for detecting scams, authorized fraud, and money mule activity. This is where Acoru can help.

Unlike traditional fraud tools that focus on transactions, logins, sessions, or devices, Acoru helps you understand how risk develops over time.

Rather than activating only when a transaction occurs or an isolated session, the platform continuously analyzes account behavior, pre-fraud signals, and counterparty activity. This helps you identify scams, money mule activity, and laundering patterns earlier and intervene before major losses occur.

With Acoru, you can:

• Unify data without replacing existing systems: Acoru creates a complete view of every account by normalizing data from any source, format, or schema as it enters the platform. You can connect existing systems and data feeds without costly rip-and-replace projects.
• Identify account risk with proprietary pre-fraud signals: Acoru analyzes account risk patterns to continuously score and classify accounts, helping you detect fraud during the preparation phase.
• Extend visibility beyond your own customers: Acoru helps you assess recipient accounts before payments are made. When a customer enters a recipient account, Acoru provides risk context based on previous encounters using your own customer and transaction data, without requiring data sharing or a consortium.
• Empower analysts with AI assistance: Using the AI Assistant, you can ask questions in natural language and instantly receive dashboards, investigation summaries, rule recommendations, and regulator-ready reports. AI-generated outputs are presented for review and approval, ensuring your team remains in control.
• Automate investigations and fraud operations: The AI Workforce executes multi-step workflows within policies you define, helping you detect coordinated mule networks and evolving fraud schemes faster. Every action is fully auditable, and all processing remains within your environment.

Request a demo today and learn how Acoru can help you prevent fraud and stay ahead of emerging threats.