Fraud Detection and Prevention—Best Practices for 2025 

Fraud is one of the biggest threats to companies worldwide. Failure to properly confront fraudsters results in both financial and reputational losses. Moreover, fraud can trigger regulatory penalties for non-compliance with anti-money laundering (AML), counter-terrorist financing (CTF), and other regulations.

In the US only, according to the 2025 Federal Trade Commission Report, reported consumer losses to fraud hit $12.5 billion in 2024, a 25% increase over 2023. Investment scams and imposter scams were the largest contributors to losses.

Overall, fraud is expected to grow rapidly in frequency, scale, and sophistication through 2030, driven by technological advances, more digital transactions, and deep penetration of AI into all spheres and industries—including organized crime. This is prompting significant investments in fraud detection and prevention technologies worldwide.

According to Mordor Intelligence, the fraud detection and prevention market is projected to be valued at USD 58.18 billion in 2025 and is expected to grow to USD 153.91 billion by 2030, reflecting a CAGR of 21.48% over the forecast period (2025–2030).

However, not all anti-fraud systems are created equal. Different industries face unique fraud risks and require tailored solutions.

At Sumsub, we’ve compiled a comprehensive guide to fraud detection and prevention techniques. We’ve also gathered all our industry-specific guides in one place. Here, you’ll also find the essential features an anti-fraud solution must have to stay effective in 2025 and beyond.

What is fraud detection and prevention?

Fraud detection involves continuously monitoring users, their transactions, and behavioral patterns to identify signs of fraudulent activity. This could include tracking unusual changes in a user’s geolocation, spotting abnormal purchasing behavior, or flagging suspicious account activity.

As technology evolves, so do the tactics used by fraudsters. To stay ahead, companies are increasingly adopting advanced fraud detection tools, including automated systems and AI-powered solutions, to quickly identify and respond to emerging threats.

Fraud prevention, on the other hand, focuses on proactively stopping fraud before it occurs. It is built around company policies informed by thorough risk assessments, which help identify the most likely types of fraud a business might encounter. To remain effective, these assessments—and the resulting preventive measures—must be updated regularly to match the changing risk landscape.

Fraud detection and prevention are complementary components of a robust anti-fraud strategy, integrating seamlessly to combat threats—often using AI and automation to adapt to new fraud patterns as they emerge.

Fraud trends to watch for in 2025

In 2025, the fight against fraud is becoming increasingly complex and challenging, fueled by rapid technological advancements and the growing sophistication of cybercriminal tactics.

According to Sumsub’s latest Identity Fraud Report, identity fraud cases more than doubled between 2021 and 2024. During the same period, 67% of companies reported a rise in fraudulent activity.

The report also highlights a global shift toward more sophisticated and hybrid fraud schemes, along with the growing democratization of fraud as it becomes increasingly accessible and cost-effective to carry out. Artificial intelligence is now a major driver of these threats, with deepfakes accounting for 7% of global fraud incidents. AI is also widely used to create fake documents—a fraud type that now makes up 50% of all reported cases. As a result, businesses, users, and regulators alike are under increasing pressure to adapt their defenses in real time.

These are just a few of the alarming trends shaping the fraud landscape in 2025:

• Fraud-as-a-service
• The spread of deepfakes into everyday life
• AI-driven fraud beyond deepfakes
• The rise of hybrid fraud attacks

Explore the full list of fraud trends for 2025 in our article: Fraud Trends for 2025: From AI-Powered Scams to Identity Theft and Fraud Democratization

Most common types of fraud in 2025

Fraud may take many forms depending on the region and businesses that are targeted. 

In 2025, the most common types of fraud include: 

AI-generated fraud 

In 2024, deepfakes became deeply entrenched as accessible fraud tools, with a 4x increase in detections since 2023, now accounting for 7% of all fraud attempts. It’s easier than ever to create realistic fake content, from false news to synthetic identities. However, AI-driven fraud goes beyond deepfakes, fueling synthetic voices, chatbot impersonations, and fake document production. AI has enhanced the sophistication of digital fraud (e.g., deepfakes, synthetic identities) and related physical scams (e.g., forged documents).

Suggested read: What Are Deepfakes, and How Can You Spot Them? (2025)

Multi-accounting

Multi-accounting occurs when a single user creates multiple accounts to exploit an online service. This tactic is often used to repeatedly access free trials, discount codes, bonuses, or to bypass bans. While multi-accounting isn’t always fraud on its own, it often enables various fraudulent activities, such as promo abuse and smurfing.

Let’s take a look at the types of fraud involving multi-accounting that are on the rise in 2025.

Promo abuse: This is when a company’s promotional materials are misused. These include referral bonuses, vouchers, sign-up bonuses, coupons, or discounts. While such campaigns aim to attract new audiences, certain individuals attempt to trick the system by taking more than their fair share—and, often enough, they succeed.

Fraud networks: A fraud ring, or fraud network, is an organized group using multiple accounts to commit criminal activities. These networks can range from a single fraudster managing several accounts to thousands of members. Accounts are often bought on the dark web or created with fake identities, enabling various types of digital fraud, including money laundering.

Money muling: This is a money laundering method where criminals use individuals—often with clean records—to transfer illicit funds. These “mules” typically have verified, low-risk accounts that face minimal scrutiny, making illegal transfers harder to detect. Mules are commonly used to launder proceeds from cybercrimes like malware attacks and romance scams.

Smurfing: In video gaming, it refers to skilled players creating new, low-level accounts to compete against less experienced opponents. This can unbalance matchmaking and negatively affect the gaming experience.

In finance, smurfing is a money laundering tactic where large sums are broken into smaller transactions to avoid detection. These funds are then deposited across multiple accounts, institutions, or locations—often by intermediaries called smurfs—to obscure their origin and bypass reporting thresholds.

Suggested read: What Is Smurfing?—The Full Guide (2025)

Payment fraud

Payment fraud involves stealing payment information to make unauthorized transactions. It comes in several forms:

Chargebacks occur when customers request refunds for disputed transactions—often following purchases made with stolen payment cards or data.

Credit card fraud happens when full card details are leaked, allowing fraudsters to make unauthorized purchases, typically with the goal of reselling goods for profit.

Card testing (or carding) involves fraudsters—often called “carders”—testing stolen card numbers to find valid ones. This can be done manually through small purchases or automated using bots to test large volumes in a short time. Effective transaction monitoring tools are key to detecting and stopping such attacks early.

Account takeover

Account takeover (ATO) occurs when fraudsters gain unauthorized access to a user’s online account, typically by stealing personal information or buying it on the dark web. They use tactics like phishing, social engineering, data breaches, and malware to obtain credentials.

Once inside, attackers can exploit the account for financial gain or use it to access other accounts owned by the same victim. ATO has become one of the most widespread types of fraud in recent years.

Key strategies for fraud detection and prevention in 2025

Companies need to implement comprehensive multi-layered solutions that can detect fraud at various stages. This can include advanced authentication methods, real-time monitoring for suspicious activities, regular employee training and awareness programs, as well as strong encryption for sensitive data.

There is no universal formula that can stop and detect all fraudsters. However, there are certainly some preventative practices that can minimize it. This includes:

• Advanced identity verification solutions
• Transaction monitoring 
• Behavioral pattern checks
• Device fingerprinting
• Background checks
• Password protection
• Deepfake detection

Companies should implement robust user verification and continuous monitoring—when done effectively, these measures can quickly identify fraudsters.

Some solutions that companies need to detect and prevent fraud includes:

• User Verification
• Business Verification
• Transaction Monitoring 
• Geolocation Tracking
• Deepfake Detection
• Device Fingerprinting 
• Fraud Scoring
• Fraud Network Detection
• Behavioral Intelligence

Best practices for fraud detection and prevention in 2025

We at Sumsub have prepared a downloadable checklist for fraud detection and prevention:

Download the Sumsub Identity Fraud Checklist for companies

Regulatory compliance and fraud prevention in 2025: Compliance requirements in the US, Europe, and APAC

Anti-fraud compliance requirements are evolving rapidly across regions to keep pace with increasingly sophisticated financial crime. Key areas of focus include customer due diligence, transaction monitoring, technology adoption, and cross-border collaboration.

Let’s take a look at the key fraud detection and prevention regulations across the US, EU, and APAC.

US

Bank Secrecy Act (BSA): The foundational law requiring financial institutions to establish robust anti-money laundering (AML) programs, including customer identification, due diligence, record-keeping, and reporting of certain transactions to FinCEN.

USA PATRIOT Act: Expanded AML obligations, notably Section 326 (customer identification) and Section 311 (special measures for high-risk jurisdictions).

Corporate Transparency Act (CTA): CTA requires beneficial ownership reporting, with deadlines extended to Jan 1, 2025, for existing entities.

Suggested read: The Full Guide to Beneficial Ownership Reporting: What Businesses Need to Know in 2025

Sarbanes-Oxley Act (SOX): SOX aims to combat corporate fraud by requiring public companies to implement strict internal controls, ensure accurate financial reporting, and hold top executives personally accountable for the integrity of financial statements. Key provisions mandate that CEOs and CFOs certify the accuracy of reports, establish severe penalties for fraudulent activity, and protect whistleblowers who report financial misconduct.

EU

In the EU, member states are required to adopt harmonized criminal law measures and reporting mechanisms to combat fraud. There is a strong emphasis on cross-border cooperation, digital forensics, and advanced surveillance to address fraud, corruption, and misuse of EU funds. Here are the key legal anti-fraud initiatives currently impacting EU member states:

Union Anti-Fraud Programme (UAFP): Provides funding and strategic direction for anti-fraud actions, including the purchase of investigation and digital forensic tools, and specialized staff training for fraud prevention and detection.

PIF Directive: Harmonizes definitions, sanctions, and prescription periods for criminal offenses affecting the EU’s financial interests, strengthening protection against fraud and facilitating recovery of misused EU funds.

EU Anti-Fraud Office (OLAF): Coordinates investigations and cross-border cooperation to protect EU financial interests.

Financial Regulation (EU, Euratom) 2024/2509: Governs EU budget protection, mandating fraud prevention controls.

6th Anti-Money Laundering Directive (6AMLD): Harmonizes and expands anti-money laundering rules across EU member states by broadening the list of predicate offenses (including cybercrime), increasing individual and corporate liability, mandating stricter penalties, and enhancing cross-border cooperation to ensure more effective prosecution and deterrence of financial crime.

Anti-Money Laundering Authority (AMLA): will oversee high-risk financial institutions across member states starting in 2028.

APAC

Jurisdictions across APAC are increasingly aligning with Financial Action Task Force (FATF) standards—enhancing National Risk Assessments (NRAs), improving transparency in beneficial ownership, and expanding oversight of virtual assets and DeFi platforms. There is also a growing emphasis on cross-border collaboration and the use of technology-driven compliance tools, particularly to counter the misuse of AI and cryptocurrencies by bad actors. Below are a few regulatory developments in some APAC countries:

Hong Kong

• Anti-Money Laundering and Counter-Terrorist Financing Ordinance (AMLO): Requires financial institutions and designated non-financial businesses to implement customer due diligence, record-keeping, and suspicious transaction reporting to prevent money laundering and terrorist financing
• The Hong Kong Monetary Authority (HKMA) has mandated AI/ML-driven risk monitoring and launched the AML/CFT Surveillance Capability Enhancement Project, along with enhanced fraud management guidelines emphasizing a risk-based approach and collaborative initiatives with banks to combat digital ecosystem scams.
• The AML/CFT (Amendment) Ordinance 2024 further tightens controls, especially for digital assets.

Singapore

• Corruption, Drug Trafficking and Other Serious Crimes (Confiscation of Benefits) Act (CDSA): Provides the legal framework to combat corruption, drug trafficking and other criminal activities.
• Monetary Authority of Singapore (MAS) Notice 626: Sets out AML/CFT requirements for financial institutions including customer due diligence and suspicious transaction reporting.
• The Monetary Authority of Singapore (MAS) has expanded the scope of predicate crimes, enhanced monitoring and surveillance, and introduced the Shared Responsibility Framework for banks to share responsibility in fraud prevention.
• MAS has revised the Money Laundering and Terrorism Financing National Risk Assessment (MLNRA) and introduced the Payment Services Act (PSA) to regulate digital payment tokens and virtual asset intermediaries, with stricter AML/CFT requirements for Virtual Asset Service Providers (VASPs).

Australia

• Scams Prevention Framework Bill 2025 establishes a comprehensive, economy-wide legislative framework to prevent, detect, disrupt, respond to, and report scams, imposing enforceable obligations on businesses in key sectors such as banking, telecommunications, and digital platforms, with significant penalties for non-compliance up to AUD 50 million.
• Commonwealth Fraud and Corruption Control Framework 2024 provides guidance and policies for Australian Government entities to manage fraud risks, but the Scams Prevention Framework Bill represents the primary legislation targeting fraud and scams in the broader economy.
• Under AUSTRAC reporting obligations, regulated entities must submit reports such as Suspicious Matter Reports (SMRs), Threshold Transaction Reports (TTRs), International Funds Transfer Instruction Reports (IFTIs), and Cross-Border Movement (CBM) Reports—each with specific thresholds and timeframes—to help detect and prevent money laundering and terrorism financing. They must also maintain records, implement AML/CTF programs, and file compliance reports as required, ensuring robust oversight and due diligence.
• The Australian Securities and Investments Commission (ASIC) has called on superannuation trustees to strengthen anti-scam and anti-fraud practices, providing detailed guidance on prevention, detection, and response to fraudulent activity.

Aligning fraud strategies with compliance

Fraud strategies in the US, EU, and APAC are increasingly aligned with compliance frameworks through integrated risk management, technology adoption, and regulatory harmonization, though regional approaches differ in focus and maturity.

In the US, regulatory mandates like the Bank Secrecy Act (BSA) and USA PATRIOT Act require financial institutions to embed fraud detection into AML compliance programs. This includes transaction monitoring, FIU reporting (SARs/CTRs), and customer due diligence.

In the EU, the AML Package (2025) mandates a single rulebook and centralized supervision via the Anti-Money Laundering Authority (AMLA), requiring tighter alignment between fraud detection and AML compliance. Integrated financial crime units combine fraud detection and AML efforts via shared data pools and analytics to identify cross-jurisdictional threats. Digital forensics and AI are prioritized to combat synthetic identity fraud and deepfake scams, with investments in tools like blockchain tracing. Centralized reporting platforms streamline SAR filings and suspicious transaction analysis across member states.

In APAC, anti-fraud strategies are closely aligned with compliance frameworks by integrating risk-based approaches, enhanced Know Your Customer (KYC) procedures, and continuous monitoring to meet both local regulations and international standards such as those set by the Financial Action Task Force (FATF). For example, Singapore’s MAS has implemented collaborative platforms like COSMIC to facilitate information sharing and risk identification across institutions, while Australia is extending AML/CTF controls to new sectors and adopting beneficial ownership registries to address emerging risks. These strategies are further reinforced by technological innovation, such as AI-driven client screening and fraud detection, ensuring compliance and proactive fraud prevention across the region.

Future trends in fraud prevention

Emerging technologies and their role

As fraud tactics become more sophisticated, organizations are increasingly turning to advanced technologies to create complex multiple-layer defense mechanisms, involving:​

• Fight AI with AI: AI/ML enable real-time analysis of vast datasets, allowing for the detection of anomalies and patterns indicative of fraudulent activity. AI-driven systems can adapt to new threats by learning from emerging fraud patterns. ​
• Threat intelligence: Enabling the detection of fraudulent activity by analyzing bank cards, IP addresses, and stolen accounts across various databases, it’s a must in 2025.
• Digital risk protection: Consolidated online fraud prevention platforms that integrate cybersecurity components—such as business logic protection and digital risk protection—with established market solutions like identity verification and online decision engines.
• Behavioral intelligence: By analyzing user behaviors—such as typing patterns, mouse movements, and navigation habits—systems can establish a baseline of normal activity and detect deviations that may suggest fraudulent access. ​
• Ongoing monitoring: Continuous monitoring of transactions and user activities throughout the entire user lifecycle allows for immediate detection and response to suspicious behaviors, reducing the window of opportunity for fraudsters.

Integrating these technologies creates a multi-layered defense strategy, which improves the ability to prevent and respond to fraudulent activities effectively.​

Adapting to evolving fraud tactics

Fraudsters continually refine their methods—which requires adaptive and proactive fraud prevention strategies: for businesses to stay ahead. This includes:

• Continuous learning systems: Implementing systems that learn from new data ensures that fraud detection mechanisms evolve alongside emerging threats, maintaining their effectiveness over time. ​
• Cross-industry collaboration: Sharing information about fraud trends is key to strengthening defenses against emerging fraud threats. In 2025, this is especially critical for cybersecurity and anti-fraud teams, as the line between cyberattacks and fraud continues to blur. Criminals increasingly blend technical exploits with deceptive tactics, making shared intelligence essential. A unified approach that addresses both system vulnerabilities and human manipulation is now vital for comprehensive protection.
• Adaptive risk scoring: Traditional static risk models are being replaced with dynamic systems that adjust to changing behaviors and transaction contexts, improving the precision of fraud detection.

FAQ

• What’s the difference between fraud prevention and fraud detection?

  Fraud prevention aims to stop fraud before it happens, while fraud detection identifies suspicious activity after it occurs.

• What are the most effective methods for detecting fraud?

  Real-time transaction monitoring, anomaly detection, and machine learning-based systems are among the most effective fraud detection methods.

• What role does AI play in fraud detection?

  AI analyzes large volumes of data to identify patterns, anomalies, and potential fraud in real time, improving accuracy and speed.

• How can small businesses implement fraud prevention strategies?

  Small businesses can adopt basic measures like strong authentication, employee training, secure payment systems, and regular audits.

• What are the emerging trends in fraud prevention for 2025?

  Key trends include AI-powered defenses, behavioral biometrics, cross-industry data sharing, and greater integration of cybersecurity with anti-fraud efforts.