September 11, 2024
Anonybit Team
Fraud Management In Banking (Best Methods For Detection & Prevention)
First-party fraud is an increasingly common and costly issue for banks. According to the Association of Certified Fraud Examiners, organizations lose an average of 5 percent of their bottom line to fraud. In many cases, the schemes are perpetrated by employees or trusted insiders.
A fraud management system can help banks identify, investigate, and mitigate first-party fraud prevention schemes to prevent significant losses. In this article, we’ll explore how these systems work and how banks can use them to combat first-party fraud.
What Is Banking Fraud Detection?
Fraud detection in banking involves a set of strategies and technologies designed to protect customers, assets, and financial systems from fraudulent activities. This process aims to identify, analyze, and mitigate various types of fraud, including phishing, ATM fraud, check fraud, etc.
Given the advancements in generative AI, banks face growing challenges in staying ahead of new threats and vulnerabilities and it is only getting more challenging.
Leveraging Automated Fraud Detection in High-Volume Banking Environments
Banks increasingly rely on biometric authentication solutions to address these challenges. A study indicates that banks generating at least $10 million in annual revenue encounter an average of 2,000 attempted fraud attacks monthly, with larger institutions experiencing tens of thousands.
Due to the high volume and complexity of these attacks, relying solely on traditional fraud detection methods is impractical. Banks implement advanced, automated systems to efficiently detect and prevent fraudulent activities at scale.
Most Common Banking Frauds
Banking fraud is constantly evolving. The digital transformation of the financial services sector has been accompanied by a sharp rise in online fraud, particularly amid the COVID-19 pandemic. While banks have made significant advancements in their fraud management systems and security protocols, so have cybercriminals. They are continually refining their techniques to exploit vulnerabilities and bypass security measures.
As a result, financial institutions regularly see fresh variations of old fraud schemes, and many of these crimes are now perpetrated by organized, sophisticated criminal networks. To stay ahead of the game, banks must adopt a proactive approach to fraud management that prioritizes biometric authentication to ensure that people are who they claim to be continuous, automated learning to identify and eliminate emerging threats. In this post, we’ll take a closer look at the common banking fraud types.
Phishing
Phishing involves cybercriminals pretending to be legitimate entities, like banks or service providers, through email, phone calls, messaging apps, texts, voice mails and more. They aim to trick individuals into disclosing sensitive information, such as passwords, social security numbers, credit card details and other personal details.
Sometimes, these phishing attempts involve urgent or threatening language to create a sense of panic and compel the victim to turn over information quickly.
Check Fraud
Check fraud involves the unauthorized use or manipulation of checks. Methods include forging signatures, altering check amounts, or stealing and using checks from others. By washing checks, changing payees and adjusting payee amounts, fraudsters are able to divert funds. Check fraud is one of the fastest growing fraud vectors today.
Wire Fraud
This fraud involves using electronic communication, such as emails or phone calls, to deceive individuals or businesses into transferring money or sensitive information. Scammers often pose as trusted entities or use fake documentation to trick victims into wiring funds to fraudulent accounts.
ACH Fraud
ACH (Automated Clearing House) fraud involves unauthorized transactions within the ACH network, which are used for electronic payments and transfers. Criminals may exploit vulnerabilities to redirect funds, make unauthorized transfers, or create fraudulent transactions. This type of fraud can affect businesses and consumers alike.
Card Fraud
Card fraud occurs when a credit or debit card is used without authorization to purchase or withdraw funds. Techniques include card cloning, copying, and using card information to make unauthorized transactions or using stolen card details to shop online.
Account Takeover (ATO)
With ATO fraud, criminals use stolen data obtained on the dark web or through phishing to gain unauthorized access to an individual’s financial accounts, such as bank accounts or credit cards. They may then use the account to conduct fraudulent transactions, withdraw funds, or make unauthorized purchases.
New Account Fraud
New account fraud involves creating new financial accounts using stolen personal information. Fraudsters use this information to open accounts in the victim’s name, often racking up debt or conducting fraudulent transactions before the victim realizes what has occurred.
Credential Stuffing
Fraudsters increasingly leverage software or bots to test stolen or leaked credentials at scale.
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- Identity Providers
- Liveness Detection
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- Fraud Detection In Banking
Fraud Detection Challenges For Banks
Banks are inundated with the sheer volume and diversity of fraudulent activities that they must monitor. Every month, they sift through millions of transactions to identify thousands of fraudulent cases, ranging from credit card fraud to the increasingly sophisticated synthetic identity theft. The variety of fraud attempts is vast, with criminals continually evolving their tactics to stay ahead of detection systems.
This flood of potential threats means compliance teams are often overwhelmed with false positives—legitimate transactions flagged as suspicious—and false negatives, where actual fraud goes undetected. The challenge lies in implementing advanced, agile, rapid detection methods. This is where biometric authentication comes in.
Impact on Customer Experience
While stringent security measures are necessary to combat fraud, they often come at the cost of customer convenience. Complex processes can frustrate customers, making accessing and managing their accounts difficult. As a result, banks often trade-off security and customer experience. Biometrics, like face recognition, require the user to simply capture a selfie in order to access their accounts and verify transactions. Next generation privacy-enhancing biometrics can provide robust security without imposing burdensome procedures on customers, ensuring their smooth and uninterrupted experience.
Burden of Technical Debt
Banks are also grappling with technical debt—the accumulation of outdated systems and technologies that are difficult to update or replace. Banks struggle to integrate new, cutting-edge solutions with their legacy systems as fraudsters quickly adopt new technologies to perpetrate crimes.
This struggle is compounded by the need to keep pace with rapidly evolving criminal tactics, which requires banks to upgrade their technology infrastructure continuously. The urgency to modernize while maintaining operational continuity is significant, as falling behind in this technological race could leave banks vulnerable to increasingly sophisticated fraud attempts. Solutions like Biometric OTP and face recognition fit seamlessly into a user workflow and minimize user disruptions.
Overlooked Fraud Attempts: Create a Database of Known Threats and Fraudsters
Banks must be aware of and look for active and emerging threats. By collecting fraud data from internal and external sources, banks can gain a comprehensive view of the fraud landscape and make more informed risk decisions.
One of the most overlooked fraud prevention methods is selfie deduplication and blocklist checks which can be run at the time of account origination, before the fraud occurs. Running these selfie checks can flag people who may be attempting to open accounts under multiple names or fake identities. Standard KYC and data checks just don’t cut it anymore.
Related Reading
- Third Party Fraud
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- First Party Fraud vs Third Party Fraud
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- Biometrics In Banking
- Real Time Transaction Monitoring
- Digital Injection
- Payment Fraud Trends
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- Fraud And Identity Management
- First Party Fraud vs Third Party Fraud
- Fraud Detection Software For Banks
Fraud Management System In Banking: 6 Best Technology For Detection & Prevention
1. Biometric Authentication
Biometric authentication uses unique physical or behavioral characteristics—like fingerprints, facial features, or voice patterns—to verify a user’s identity. This technology adds a robust layer of security, as these characteristics are difficult to replicate or steal.
Biometric Authentication in Modern Applications
For example, many modern smartphones incorporate biometric methods for unlocking devices or authorizing transactions. Banks have also adopted two-factor or multi-factor authentication systems that include biometrics to enhance security further.
Addressing the Limitations of Traditional Authentication
Traditional multi-factor authentication has limitations in combating cyberattacks. To address these, technologies like Anonybit offer more secure and convenient biometric verification methods, eliminating the need for passwords and reducing risks such as phishing and identity theft.
2. Behavioral Analytics
Behavioral analytics focuses on monitoring and analyzing how users interact with their devices and services to establish a baseline of normal behavior. This can include tracking how a user types, swipes, toggles between fields and more.
Any deviation from known users’ patterns can indicate potential fraud, such as account takeovers or unauthorized access. By translating these behaviors into actionable insights, behavioral analytics provide a proactive approach to fraud detection, allowing organizations to detect and mitigate threats and push step up authentication with biometrics for a seamless user experience.
3. Machine Learning and Artificial Intelligence
Machine learning (ML) and artificial intelligence (AI) have transformed fraud detection by enabling systems to recognize and adapt to new fraud patterns in real time. Unlike traditional methods, ML models can analyze vast amounts of data to identify complex patterns that might elude human analysts.
These models can be trained using supervised learning (with labeled historical data), unsupervised learning (without labels) or a combination of both. As these models continuously learn from new data, they become increasingly accurate in predicting and detecting fraudulent activities, making them highly effective against sophisticated schemes.
4. Anomaly Detection
Anomaly detection centers on identifying outliers—instances deviating significantly from the norm. This technique is precious for uncovering previously unknown or unexpected fraud patterns.
Using machine learning algorithms, anomaly detection systems can learn what constitutes normal behavior within a dataset and flag any deviations for further investigation. This method detects novel or emerging fraud tactics that have yet to be incorporated into rule-based systems.
5. Rules-Based Systems
Rules-based systems utilize predefined rules to detect potential fraud based on specific conditions or patterns. For example, if a credit card transaction exceeds a certain threshold or occurs in an unusual location, the system might flag it for further review. While this approach is straightforward and effective for well-known fraud scenarios, it may struggle to keep pace with rapidly evolving fraud tactics without regular updates to the rule set.
6. Two-Factor and Multi-Factor Authentication
Two-factor (2FA) and multi-factor authentication (MFA) are identification techniques that require banking customers to provide two or more pieces of evidence to verify their identity. 2FA and MFA are fairly standard security measures that, like biometric authentication, should be layered to create a comprehensive anti-fraud strategy.
Banking Fraud Patterns & Trends
Enhanced Social Engineering
Fraudsters are becoming more sophisticated, especially when it comes to social engineering. They are honing their skills to execute better attacks using technology and collaboration.
These include spear phishing attacks like CEO fraud that target specific employees to trick them into providing access to sensitive company data or transferring funds to the attacker. Remembering that these tactics also have offline applications, underscoring the need for heightened awareness and preparedness is crucial.
Crime-as-a-Service
The barrier of entry for criminals is lower than ever these days, as many are available for hire on the dark web. Bad actors offer their services online or access to their specialized tools, tutorials, and walk-throughs. Anyone can become a fraudster. They must purchase the right kit, tools, and instructions, and they can become an effective criminal overnight.
Synthetic IDs
Synthetic IDs combine real stolen information (like names, addresses, and social security numbers) with made-up data or deep fakes to create new identities that are harder to detect. As the latter becomes increasingly believable, customer onboarding for neo banks, BNPL, micro-lenders, and others calls for increased vigilance, highlighting the need for caution and attention to detail.
Book A Free Demo To Learn More About Our Fraud Prevention Software
At Anonybit, we help companies prevent data breaches and account takeover fraud with our decentralized biometrics technology. With our decentralized biometrics framework, companies can enable passwordless login, wire verification, step-up authentication, help desk authentication, and more.
Comprehensive Security Solutions for Companies
We aim to protect companies from data breaches, account takeovers and synthetic identity on the rise, privacy regulations, and digital transformation. To achieve this goal, we offer security solutions that cover the user lifecycle such as:
- 1:N deduplication, synthetic and blocklist checks upon account origination
- Passwordless login
- Step up authentication
- Account recovery
- Secure storage of biometrics and other PII data
Balancing Privacy and Security with Anonybit’s Integrated Identity Management Platform
Anonybit eliminates the tradeoffs between privacy and security. Prevent data breaches, reduce account takeover fraud, and enhance the user experience across the enterprise using Anonybit. Book a free demo today to learn more about our integrated identity management platform.