Transaction Fraud: Examples, Impact, Detection and Prevention

Transaction fraud, also known as fraudulent transactions or a fake transaction, is any unauthorised transaction that occurs when a legitimate user’s payment is exploited without their consent. This can happen in several ways but majorly through the use of stolen credit card data to make purchases, an example of a fraud transaction on credit cards.

With the emergence of digital modes of payment and banking, as well as the rise of sophisticated cyber criminals, transaction fraud has been on a constant rise. In 2023, the United States lost ten billion dollars to fraud. Transaction fraud may continue to evolve as time goes by, considering that there might always be vulnerabilities in digital systems that can be exploited and creative ways to execute them such as transaction fraud. It is therefore important for fintechs, financial institutions, and their customers to duly understand fraudulent transactions in banking as well as detection and prevention measures to always remain one step ahead.

This article will explore several aspects of transaction fraud including its examples, impact, detection and finally prevention. Ready? Let's dive in!

What is Transaction Fraud?

Understanding the meaning of transaction fraud is easy. It is simply any unauthorised or deceptive transaction conducted with the intent to achieve dishonest or illegal benefits. There are plenty of categories and types of transaction fraud.

Online transaction fraud is usually done via the Internet or digital platforms. Fraudulent transaction acts often take advantage of unsuspecting victims or customers through phishing attempts or sometimes social engineering.

Types of Online Transaction Frauds: What are the Examples of Transaction Fraud?

Transaction Fraud Examples, Impact, Detection and Prevention.

The types of online transaction fraud may include;

1. Identity Fraud

One of the most common examples of transaction fraud is identity fraud, which usually or typically occurs when there is a data breach.

A data breach is a security incident that results in the unauthorised or illegal access of confidential information belonging to employees or third parties. This data can be personally identifiable information (PII) or sensitive personally identifiable information (SPII). PII may include data that can be available to a subset of the general public, such as email addresses, pictures, phone numbers, addresses, etc. In comparison, SPII might include bank balance, password codes, etc.

When an individual's PII is in the hands of malicious individuals, the data can be used to impersonate the original owner. Identity fraud can be identified easily and quickly through the use of an AI-powered fraud check solution.

Recommended: Guide to Identity Proofing

2. Phishing Attacks

Phishing attacks often mimic legitimate organisations or contacts. Cybercriminals may try to contact unsuspecting individuals with emails that look like those of a reputable organisation or individual.

For example, info@regtechafrica.com can become info@regtechfrica.com or Info@Regtechinafrica.com. Fraudulent emails or messages trick individuals into giving out sensitive information, such as login credentials or financial details.

Criminals may try to contact bank customers who pose as credible or legitimate bank officials. They often use social engineering techniques that may create a sense of urgency or fear in the mind of the recipient of the mail.

3. Account Takeover

Account takeover happens when fraudsters gain unauthorised access to an individual's account, typically through hacking or phishing, and conduct transactions as the account holder. This can involve bank accounts, email accounts, or e-commerce platforms. Once they have control, they can transfer funds, make purchases, or engage in other fraudulent activities, including identity fraud.

4. Fake Transactions

Fake transaction is another example of fraud transaction that includes a wide range of illegal means aimed at creating false or misleading transactions to deceive individuals or organisations. This type of fraud is commonly used to manipulate financial records, steal money, or exploit system vulnerabilities. There are several types of fake transactions, including;

5. False Billing

Fraudsters generate fake invoices or billing statements for goods or services that were never delivered or provided. They then send these fake bills to businesses or individuals, hoping the recipient will pay without verifying the legitimacy of the bill.

6. Refund Fraud

This fraud transaction involves making a legitimate purchase and then requesting a refund by claiming the item was not received or was defective. Alternatively, fraudsters might return an item that is different or of lower value than the original purchase, pocketing the difference.

7. Fake Payment Confirmations

Fraudsters send false payment confirmation messages or emails to sellers, tricking them into believing that a payment has been made. This is often used in online marketplaces where sellers may ship goods before verifying payment.

8. Overpayment Scams

The fraudster sends a payment that exceeds the amount owed. They then ask the victim to refund the excess amount, often before the initial payment clears. When the original payment bounces, the victim is left out of pocket.

9. Chargeback Fraud

A customer makes a legitimate purchase and then challenges the transaction with their bank or credit card company, claiming it was unauthorised or that the goods or services were not received. The bank issues a chargeback, and the seller loses both the goods and the payment.

10. Fake Donations

Fraudsters create bogus charitable organisations or donation requests, often exploiting recent disasters or popular causes. They solicit donations from well-meaning individuals who believe they are contributing to a legitimate cause.

11. Business Email Compromise (BEC)

This is a type of online transaction fraud that involves fraudsters spoofing or hacking into a company's email system to send fake payment requests to employees or business partners. These emails often appear to come from senior executives or trusted partners, prompting recipients to transfer funds to the fraudster's account.

12. Transaction Reversal Fraud

This is a type of online transaction fraud that involves making a legitimate transaction and then using technical means to reverse the payment after receiving goods or services. This can be done by exploiting flaws in the payment processing system.

13. Point-of-Sale (POS) Fraud

Fraudsters tamper with POS systems to create fake transactions or void legitimate transactions while pocketing cash. This is often done in retail environments where cash handling and record-keeping might be less stringent.

What are the Impacts of Transaction Fraud on Banks and Businesses?

Transaction fraud is a crime, and like most crimes, it comes with negative consequences for both the criminal and the victim. Some of the impacts include:

1. Financial Losses

Victims, who can either be individuals or organisations, can suffer significant financial losses. Businesses may incur additional costs for chargebacks, refunds, and fraud investigations.

2. Reputational Damage

Organisations affected by transaction fraud can experience a loss of trust from customers and partners. Rebuilding a tarnished reputation can be quite tricky and time-consuming, and some companies or financial institutions may never be able to recover.

3. Legal and Regulatory Consequences

Businesses may face legal penalties or regulatory fines if they fail to implement adequate fraud prevention measures. Compliance with regulations such as PCI-DSS (Payment Card Industry Data Security Standard) is crucial.

4. Emotional and Psychological Impact

Victims of fraud can experience stress, anxiety, and a sense of violation. The process of resolving fraud issues can be time-consuming and distressing.

What are Transaction Fraud Detection Rules?

Transaction fraud detection involves identifying and preventing unauthorised transactions that can harm businesses and consumers. Various rules and strategies are employed to detect potential fraud, which can be categorised into several types:

Types of Transaction Fraud Detection Rules

Transaction fraud detection rules are the basic elements of any effective fraud prevention system. These rules are designed to identify suspicious activities that may indicate fraudulent attempts. By setting up and monitoring these rules, businesses and financial institutions can significantly reduce their risk of financial loss.

The Transaction fraud detection rules are:

1. Static Rules

These are basic, fixed rules that follow simple if/then logic. For example, if a transaction originates from a blacklisted IP address, the transaction is blocked. While easy to implement, static rules can lead to false positives due to their inflexibility.

2. Scoring Rules

Scoring rules assign a risk score to transactions based on various factors, helping businesses assess the likelihood of fraud. Transactions that exceed a certain score may trigger additional verification steps.

3. Velocity Rules

These rules monitor user or customer behaviour over a specific time frame. For instance, if a customer attempts multiple logins or transactions in a short period, it may indicate account takeover attempts, prompting further investigation.

4. Machine Learning Rules

Leveraging artificial intelligence, these rules analyse historical data to identify patterns of fraudulent behaviour. Machine learning algorithms adapt over time, improving their accuracy in detecting anomalies.

5. Anomaly Detection

This involves identifying unusual patterns or behaviours that deviate from established norms. For example, a sudden increase in transaction amounts or a change in purchasing patterns can trigger alerts for potential fraud.

Best Practices for Transaction Fraud Detection

1. Real-Time Monitoring:

Implementing systems that provide immediate alerts for suspicious activities, allows for quick responses to potential fraud. Financial institutions and businesses can implement these best practices to detect transaction fraud quickly before it happens.

2. Behavioural Analytics:

Analyse typical user behaviour to spot deviations that may indicate fraud, such as unusual login locations or transaction amounts.

3. Collaborative Fraud Intelligence:

Share information about fraud transaction, trends and tactics with other organisations to stay ahead of evolving threats.

4. Ongoing Updates:

Regularly review and update fraud detection rules to adapt to new fraud strategies and patterns.

Financial institutions and businesses can also utilize these 10 ways of detecting online transaction fraud.

How Can Artificial Intelligence (AI) Prevent Transaction Fraud?

Artificial Intelligence (AI) has revolutionised the fight against transaction fraud, offering businesses and financial institutions a powerful tool to protect their customers and assets. By leveraging advanced algorithms and machine learning techniques, AI can detect patterns, anomalies, and suspicious activities in real-time, helping to identify fraudulent transactions in banking before they can cause significant financial damage.

There are several ways AI can help prevent transaction fraud:

1. Transaction Monitoring

Transaction monitoring, as a tool, aids proactive fraud prevention by utilising artificial intelligence software to monitor transactions in real-time.

YouVerify's transaction monitoring solution provides a comprehensive approach to transaction monitoring, combining pattern recognition, anomaly detection, and risk assessment capabilities. This integrated approach ensures that businesses can effectively identify and mitigate fraudulent transactions, regardless of the nature or complexity of the fraud scheme.

By leveraging AI-powered technology, the solution enables businesses to stay ahead of fraudsters and protect their customers and financial assets.

2. Liveness Detection

Deep fakes are often a mischievous means that cybercriminals use to commit identity fraud, which can lead to fraudulent transactions. Deep Fakes are hyperrealistic digital manipulations of media, typically videos, images, or audio, that use artificial intelligence (AI) and deep learning techniques to create content that appears authentic but is actually altered or entirely fabricated.

Deep Fakes are often used to bypass checks or security measures that have to do with transitions, such as video recognition security systems, passports, interviews, etc.

Liveness detection involves using advanced algorithms to differentiate between real, live human interactions and spoofed or fake ones. For instance, when performing identity verification, AI systems can analyse various factors such as eye movement, blinking patterns, and subtle facial expressions to determine if the person in front of the camera is indeed a living individual and not a deepfake or a pre-recorded video.

3. Fraud Scoring

AI-driven fraud scoring systems are programmed or trained to assign a risk score to a specific transaction, considering various factors, such as the user's transaction history, device information, and geolocation. Transactions with a high fraud score are subjected to further verification before being processed. This measure ensures that legitimate transactions are not unnecessarily delayed while suspicious transactions are flagged for further investigation.

By incorporating AI into their fraud detection measures, businesses can reduce the occurrence of transaction fraud. Fraud scoring is an essential tool for financial institutions and fintech companies seeking to protect their customers and assets from fraud. Youveriy's Fraud Check is an efficient tool for fraud scoring.

4. ID Data Matching

Identity fraud remains a major threat to the banking sector and users alike. ID data matching can help reduce identity fraud by matching the data provided by the user, such as their name, date of birth, and identification number, against official government databases or other trusted sources. This ensures that the individual attempting the transaction is who they claim to be.

5. Address Verification

Trained AI systems can help execute this important part of fraud prevention, especially in e-commerce and online banking transactions. Fraudsters often use fake or stolen addresses to carry out fraudulent activities, like making purchases with illegally obtained credit cards or applying for loans under fake identities. AI-powered address verification systems help eliminate this risk by cross-referencing the provided address with reliable databases, like postal services or government records, to make sure that the address is truly valid and tallied.

6. Bank Account Verification

Bank account verification is another important tool in preventing transaction fraud. Before processing payments or transfers, AI-backed systems can verify the validity or authenticity of the bank account details provided by the user. This involves checking whether the account is active, whether it matches the user's name, and whether it has been flagged for suspicious activity in the past. AI algorithms can also analyse patterns in bank account usage to detect potential fraud.

For example, if a bank account that has been dormant for a long time suddenly begins processing large transactions, the system can flag it as suspicious. By implementing bank account verification, businesses can significantly reduce the risk of processing fraudulent transactions, ensuring that funds are transferred only to legitimate accounts.

Detect and Prevent Suspicious Transactions with Youverify's AI-Powered Transaction Screening Solution

As digital payment methods and online transactions continue to grow and evolve, so does the risk of transaction fraud. Understanding the various forms of transaction fraud, transaction fraud detection rules its impact, and how to detect and prevent it using advanced technologies like AI is important for financial institutions, businesses, and consumers to stay protected.

With Youverify’s transaction monitoring and detection AI solution, You can automate your transaction monitoring and screening with one solution- Youverify’s flagship product. With this transaction monitoring solution, you can identify and block high-risk transactions with advanced AI and machine learning algorithms before they get approved. Want to know how to go about this? Schedule a FREE demo with our transaction monitoring expert today.