How to Detect and Prevent Fraud in Online Payments

For online payments fraud prevention, businesses in all industries must be able to identify types of online payment fraud and use training and software tools to detect fraud attempts and reduce their risks. Fraud detection in online payments is essential to avoid losing cash and reducing profitability. Online payment fraud is widespread and significantly increasing as a trend, as evidenced by the following statistics. 

The 2025 AFP® Payments Fraud and Control Survey results indicate that “79% of organizations were victims of payments fraud attacks/attempts in 2024.” Statista reports the monetary losses from payment fraud: “According to estimates, e-commerce losses to online payment fraud surpassed 44.3 billion U.S. dollars globally in 2024. The figure was expected to grow further to over 100 billion U.S. dollars by 2029.”

Common Types of Online Payment Fraud

Online payment fraud can occur through different methods.

Common types of payment fraud for online payments include:

• Stolen credit card fraud

• Account takeover (ATO)

• Wire transfer fraud

• Friendly fraud/chargebacks/refund fraud

• Synthetic identity fraud

• Triangulation scams/triangulation fraud

Stolen Credit Card Fraud

Stolen credit card fraud is the theft of credit cards or related information for making illegal online or in-store purchases. Credit cards can be stolen through the mail, in wallet or purse snatching, or the card details information can be obtained through a skimmer, phishing schemes, or Internet and mobile app hacking. 

Thieves can use card-not-present transactions to make purchases if the best fraud prevention systems aren’t being used to detect their online payment fraud at checkout or earlier in the fraud risk detection process for the customer journey. 

Account Takeover (ATO)

Account takeover (ATO) is a scammer’s deception or a hacker’s cyberattack that results in obtaining unauthorized access to a victim’s legitimate account. The purpose of account takeover, which may include getting account login credentials and passwords, is to fraudulently withdraw money, make purchases, or otherwise perpetrate online payment fraud. Device fingerprinting to detect online payment fraud can help identify account takeover fraud. 

Wire Transfer Fraud

Fraudsters consider using wire transfers to perpetrate a type of online payment fraud called wire fraud. Wire transfers are non-reversible bank-to-bank transfers. Wire transfer funds are usually not returnable after the victim’s funds are sent in a transaction.  

Friendly Fraud/Chargebacks/Refund Fraud

Friendly fraud is a name for chargeback fraud in which a customer has received the goods or services in a credit card or debit card purchase transaction, but files a dispute to claim that a refund is required because the shipped goods or services weren’t received. Friendly fraud may also be called refund fraud. 

Friendly fraud may be intentional or inadvertent if the buyer or a member of their family paying the credit cards isn’t aware of the purchase or forgets that they made a purchase. Nonetheless, merchants have revenue and financial losses when sales refunds are unfairly issued through chargebacks. 

Synthetic Identity Fraud

Fraudsters use synthetic identity fraud, a type of identity theft, to get loans from financial institutions or open accounts (like bank accounts or PayPal) that they will use for online payments fraud. Synthetic fraud uses stolen sensitive personal information (like social security numbers) and fake identity and contact information. 

Triangulation Scams/Triangulation Fraud

Triangulation scams (triangulation fraud) involve three parties: (1) a legitimate customer buying from the fraudster’s website that provides their payment information and shipping address, (2) a fraudster using the customer’s stolen credit card or debit card information to make a goods purchase to ship to the legitimate customer, and (3) a legitimate store or marketplace from which the fraudster purchased the goods with the stolen credit card. 

Through friendly fraud (refund fraud), the customer disputes the charge from the legitimate retailer’s site and requests a refund from their credit card issuer or bank. The legitimate merchant loses money. PayPal can also be used to perpetrate the triangulation scam. 

How Payment Fraud Detection Works

Online payment fraud detection works by using these techniques:

• Risk signals and data points
• Real-time vs. post-transaction analysis
• Machine learning and rule-based systems

Risk Signals and Data Points

Fraud detection in online payments uses risk signals that include IP address, device fingerprinting, and velocity checks. 

IP Address

An IP address (Internet Protocol address) is the numerical identifier assigned to each Internet user by their Internet Service Provider (ISP). 

Device Fingerprinting

In real-time, device fingerprinting collects identifying data points for each computer, mobile phone, or tablet device. The data points in device fingerprinting are unique hardware and software characteristics, including operating system, screen resolution, browser version, and other identifiers. 

Common purposes of device fingerprinting are to create a device profile and detect potential transaction fraud, identify users and personalize their experiences, and defend against cybersecurity threats. 

Velocity Checks

Velocity checks are a fraud prevention technique for monitoring the frequency and patterns of transactions from an IP address or account in a selected timeframe to detect overuse or anomalies that could signal a high risk of fraud (and bot usage). Velocity checks flag exceptions for suspicious behavior requiring further investigation or resulting in a payment card decline. 

From frequency and transaction data, velocity checks can detect stolen credit cards and other forms of online payment fraud. 

Real-time vs. Post-transaction Analysis

Real-time vs. post-transaction analysis is essential for fraud prevention in online payments. For effective fraud detection in online payments, your business needs to prevent payment fraud before it happens. Post-transaction analysis is too late because recovering funds from fraudulent transactions is generally difficult or impossible. 

Some software platforms for fraud detection monitor merchants’ users in real-time throughout the customer journey, including clicks to transaction payment attempts. Real-time monitoring can be applied to supplier invoices requesting payments to detect fraud risks. 

Machine Learning and Rule-based Systems

Machine learning detects anomalies in patterns and can be used in other ways to detect fraud. Rule-based systems use multiple algorithms to detect exceptions and set thresholds in velocity checks or other discrepancies. 

Core Components of an Effective Fraud Detection System

An effective payment fraud detection system includes these core components:

• Identity verification tools
• Behavioral analytics
• Transaction monitoring
• Chargeback management
• Blacklists and whitelists

Identity verification tools

Various identity verification tools can be used to detect and prevent online payment fraud. 

Identity verification tools include:

• Biometrics like face recognition or fingerprints
• Online verification with device fingerprinting 
• Matching provided information like TINs (taxpayer ID numbers) 
• Two-factor or multi-factor authentication
• Email, phone, and address verification
• Knowledge-based identification using personal information or security questions
• Document verification

Behavioral analytics

Behavioral analytics in payment fraud detection can identify users through historical data points and continuous monitoring in real-time of their normal patterns and actions. Behavioral analysis considerations include navigation, typing speed, devices used, and transaction amounts. A high typing speed may indicate a bot being used. When suspicious activity is detected, flagging based on risk scoring can include transaction blocking or account lockouts.

Transaction monitoring

Transaction monitoring uses different techniques to detect and prevent online payment fraud. It is continuous and flags suspicious activities in real-time. Transaction monitoring tracks clicks, logins, account profile changes, and the registration of new devices.

Transaction monitoring identifies data, including:

• Pattern anomalies using AI and business rules 
• Unique device fingerprints
• IP address
• Payment methods 
• Matching credit cards to contact information and bank identification numbers (BINs) 
• Transaction amounts and frequency 
• Channels used
• KYC (know your customer) and AML (anti-money laundering) checks

For flagged transactions, whitebox machine learning determines fraud risk scores and the logic for declining transactions. With a high transaction frequency (velocity frequency) bots rather than humans may be used in automatic payment fraud attempts. 

Chargeback management

Chargeback management consists of real-time software alerts from monitoring before chargeback occurs, refund policies and procedures to prevent or mitigate chargebacks, and dataset deep analytics using AI/machine learning tools. Businesses can use system metrics to track and determine the extent of their chargeback fraud.

Rapid Dispute Resolution(RDR) attempts to replace chargebacks with refunds, meaning the business gets its merchandise back (without losing the merchandise sold and the sales proceeds through a credit card issuer’s refund).

Blacklists and whitelists

Blacklists and whitelists are scanned or created to deny access (blacklists) or allow access (whitelists) to payment or other applications. Blacklists and whitelists are used for potential fraud prevention in online payments. 

A whitelist allows access to a system or resource using email addresses, IP addresses, software applications, etc. A blacklist is a database containing individuals, email addresses, credit card numbers, and individuals or companies that are associated with fraudulent or suspicious activities, or sanctions lists such as OFAC for global regulatory compliance. 

Choosing the Right Fraud Detection Tools 

One critical consideration regarding enterprise risk management and internal control is to choose the right fraud detection tools with functionality your business needs to prevent fraud. Your business can incorporate several types of fraud detection tools. 

Fraud detection tools include: 

• Built-in tools from payment processors 

• Third-party fraud prevention platforms

• API integrations and scalability considerations

Built-in Tools from Payment Processors

Payment processors incorporate fraud detection tools, including:

• Machine learning for anomaly detection 
• Device fingerprinting
• IP address analysis
• Rich payments data
• Real-time transaction monitoring
• Address Verification Service (AVS) for credit cards
• Pre-defined business rules
• Behavior analytics
• Two-factor authentication (2FA)

Third-party Fraud Prevention Platforms

Numerous third-party fraud prevention platforms are available from software providers for fraud detection in online payments. Three examples of third-party fraud prevention platforms follow. 

SEON

SEON is a global fraud prevention and AML platform solution designed to detect fraud and global regulatory compliance lapses from these sources. SEON blocks fraudulent traffic and accounts from the initial click through onboarding with real-time digital footprint and device intelligence signals. It uses AI for transaction monitoring to identify fraud risks. SEON also uses built-in rules for automated fraud detection. 

Sift

Sift fraud detection is used throughout the customer journey for rule-based, AI-powered instant fraud detection and real-time risk decision-making. 

Riskified

Riskified is a fraud detection platform used by eCommerce companies. These online merchants use it for fraud prevention and chargeback fraud protection. The Riskified solution is scalable for growing businesses. 

API integrations and Scalability Considerations

Tipalti AP automation and mass payments products are API integrations with your ERP for supplier invoice processing, including online payments. 

Tipalti’s unified finance automation software platform lets your organization make online global payments with 50+ preferred payment methods in 200+ countries and 120 currencies. Tipalti automation software is scalable to meet business growth and your multi-entity corporation’s needs (when your ERP or accounting software is multi-entity capable). 

Tipalti Online Payment Fraud Detection Features

The Tipalti Detect® feature of Tipalti AP automation software helps your business detect vendor fraud in online payments. To further prevent online payment fraud, Tipalti uses 26,000+ payment rules. It validates suppliers upon onboarding with its KPMG-approved tax engine, which includes IRS taxpayer identification number (TIN) matching. 

Tipalti Detect® uses machine learning models (AI) to spot specific patterns and anomalies to help your company avoid online payment fraud before using its online payment system. Payers that are Tipalti users with the Tipalti Detect® feature can suspend or block payees from receiving payments, identify suspended or blocked payees trying to create multiple accounts, and receive notifications about suspicious payees. Tipalti Detect® uses contact details, emails, account numbers, TINs, and payments as data points to detect fraud. As another risk check, it compares details to other blocked or suspended payee accounts. 

Tipalti Detect® provides instant exception notifications and creates an audit trail to track cases. 

Other Tipalti Features and Products

Besides fraud detection in online payments, Tipalti AP automation software provides the following advantages. Tipalti finance automation adds financial controls, efficiently onboards new suppliers with self-service forms, including W-9 or W-8 for tax compliance, and performs automated digital invoice processing with supplier verification, matching, routed approvals, and global payments. 

Tipalti AP automation performs automatic 3-way matching of invoices by line item with purchase orders and receiving data. Without purchase order matching, your businesses might pay fake invoices (submitted in invoice fraud schemes) for which it hasn’t received the goods or services being invoiced. 

Tipalti AP automation reduces operating costs and hiring needs, detects fraud risks and errors, lets your business take lucrative early payment discounts on time, and provides real-time spend visibility and cash flow requirements. Tipalti AP automation also provides instant payment reconciliation to help your company speed up its financial close by up to 25%. 

For payouts to creatives, streamers, influencers, and freelancers, consider using Tipalti’s mass payments product, which also uses Tipalti Detect®. 

Best Practices for Preventing Payment Fraud

As best practices for preventing payment fraud, businesses should:

• Deploy multi-layered defense strategies
• Keep fraud rules up to date
• Educate staff and customers
• Monitor and adjust KPIs 

Deploy Multi-layered Defense Strategies

To prevent fraudulent transactions in payment fraud, businesses must research prevalent risks, plan a comprehensive, multi-layered risk management strategy, and implement fraudulent payment risk prevention security measures for their type of business and industry.

Update Fraud Rules

Business risk management strategies include issuing, updating, and following company policies that contain fraud rules to detect and deter online payment fraud. Fraud perpetration and protection methods change and require the best modern solutions.

Fraud rules to detect online payment fraud attempts must include:

• Using software driven by artificial intelligence/machine learning 
• Applying sets of algorithmic rules that alert to suspicious transactions
• Supplier validation 
• A strong framework for enterprise risk management (ERM)
  • Internal controls  
  • Ethical standards for the company, executive management, and employees
• Role-based access to sensitive information to prevent unauthorized access
• Know your customers (KYC) practices 
• Global regulatory compliance, including AML and sanctions lists screening

Educate Staff and Customers

Educating staff and customers to be vigilant in identifying fraudulent activities to avoid becoming a victim is one prong of a multi-dimensional fraud prevention strategy. It builds customer trust. 

Employees and customers should be alert to types of fraud used by scammers, including suspicious emails, texts, or social media posts with malicious links, imitation website scams, and fake supplier invoices with no goods or services received by the company. They should resist messages with a sense of urgency or requiring non-standard payment methods with no reversibility, like instant bank transfers, wire transfers, money orders, and gift cards. 

When possible, customers should use credit card tokenization. Tokenized credit cards like Apple Card replace credit card numbers and CVV security numbers with a one-time random set of characters for added payment transaction security.  

Additionally, train employees to select and use software products that prevent fraud in the organization. Add-on third-party software should be secure to avoid introducing new cybersecurity vulnerabilities to your company. 

Monitor and Adjust KPIs 

Businesses should include payment fraud prevention KPIs in their system list of monitored KPIs. A starting point for these KPIs related to payment fraud is using fraud rates and false positives as KPIs, with the current rate and trends tracking.

In payment fraud, false positives are incorrect exceptions that flag alerts by algorithms for suspicious activities or fraudulent online transactions that are actually legitimate. The result is wasted staff time for investigations, the potential for lost revenue from unauthorized transactions, and a negative impact on customer experience from a sales decline or delay.

Compliance and Data Security Considerations

To reduce the risks of online payment fraud, implement these types of compliance and data security measures in your business:

• PCI DSS compliance
• Data privacy (GDPR, CCPA)
• Secure authentication (2FA, 3DS)

PCI DSS Compliance

PCI DSS compliance is a payment card industry standard for businesses that store, process, and transmit credit card data, carrying fines, penalties, and possible business disruption for not complying with its 12 security requirements (that reduce risks of unauthorized access, misuse, and theft). PCI DSS stands for Payment Card Industry Data Security Standard.

The PCI DSS standard and other related standards are available as downloads from the PCI Security Standards Council’s Document Library. Research recent revisions in the standard to ensure compliance. 

Data Privacy 

Data privacy regulations include GDPR and CCPA. 

GDPR (General Data Protection Regulation) is an EU law effective May 25, 2018, protecting the privacy of personal data of individuals who reside in the European Union (EU)/European Economic Area (EEA). It applies to organizations, regardless of location, if they process the personal data of these protected EU/EEA individual residents, offer them goods or services, or monitor their behavior. 

CCPA (California Consumer Privacy Act) is a California law effective January 1, 2020, granting California consumers personal information protection rights. The CCPA informs California consumers about their personal information businesses collect and provides the right to delete it and opt out of the sharing or selling of their personal information. 

Secure Authentication

Secure authentication uses various methods to verify a user, device, or system before allowing access to sensitive information and resources. Two types of secure authentication are 2FA and 3DS.

Two-factor authentication (2FA) requires two forms of identification before allowing data and resource access. 

Options for two-factor authentication include:

• Authenticator apps or employee key fobs that continuously generate different security codes. 
• SMS text messaging or email, supplying a one-time code. 
• Push notifications to your phone signal the approval or denial of access to an app or website. 
• Voice authentication automatically identifies you after you state your name or press a key after a phone prompt. 
• Biometrics such as Face ID, retinal scanning, or fingerprints. 

Hackers and scammers use different methods to bypass two-factor identification. Therefore, although 2FA is recommended to increase security access, it’s not foolproof. 

Instead of two-factor authentication (2FA), multi-factor authentication (MFA) may be used. 

3-D Secure (3DS) authentication adds security to online credit card and debit card transaction processing. 3DS requires payment cardholders to authenticate their identity with the card issuer before approving an online transaction for payment processing. This authentication process is performed through an in-app interface or pop-up window. 3DS is used for fraud detection in online payments. 

Staying Ahead of Fraudsters

Businesses and non-profit organizations must create and continuously optimize effective online payment fraud detection and prevention policies. Their payment services must embed fraud prevention tools. Companies should train their employees and customers to identify fraudulent payment scams and prevent falling victim to these malevolent schemes. 

With the right policies, training, and systems, leveraging fraud detection in online payments becomes a competitive advantage. Automating fraud detection in online payments works better than solely using human detection methods. 

To succeed at fraud detection in online payments, integrate scalable and efficient Tipalti AP automation software with your company’s ERP system. Online payment fraud is a global problem. To detect and help your business prevent online payments fraud, you need a supplier invoice processing and global online payments solution that strengthens financial controls with Tipalti Detect® and supplier validation tools. Prevent Payment Fraud with Controls.