Blog 31 Jan 2024

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Fraud Detection

Online Fraud Detection | Combat Spoofing Attacks with AI

Author: admin | 31 Jan 2024

Digital identity verification solutions prevail, so scammers are searching for more ways to manipulate these emerging IDV checks. Face spoofing is employed widely to exploit security systems, in which scammers dodge biometric verification systems through various techniques such as 3D rendered models, photographs, and 3D printing masks.

Fraud detection techniques, including liveness detection and anti-spoofing face recognition, have emerged to reduce prevailing risks. To determine if the user is real or fake, the face recognition system detects and verifies the following things: 

  • Face texture
  • Features density
  • Relationship between features 

Modern technology helps businesses streamline user onboarding procedures by thoroughly checking the user identity. 97% of airports in the US implemented facial recognition technology by 2023 to quickly recognise passengers. 

Key Takeaways 

  • Credit cards, account takeover, and bonus abuse are the most common types of fraud. 
  • As per the FBI report, business email attacks continue to increase. 
  • Businesses can suffer millions of dollars from spoofing attacks if they don’t implement fraud detection solutions. 

Businesses are more focused on biometric verification systems, so scammers want to stay ahead of them, inventing new ways to spoof people. Hence, it’s crucial to understand what fraud detection is, its different types, and which advanced technology will help to combat it. 

A Brief Insight into Fraud Detection

Scams damage a business or individual’s reputation in the digital world. Firms have to limit them by implementing advanced fraud detection solutions. That’s why fraud prevention experts leverage advanced solutions that are more accurate and reliable. 

Fraud detection is the solution to restrict imposters from securing monetary benefits through false claims or identity. Before moving further, it’s important to understand the difference between fraud detection and prevention. 

Difference between Fraud Prevention and Detection

People are usually confused between fraud detection and prevention so the following points will clear their points thoroughly:

Fraud Detection

  • Identify fraud when it happens.
  • It’s a reactive approach and involves recognising suspicious activities. 
  • A practical approach that helps firms or individuals to take immediate actions, provides enough time to investigate, and immediately recover losses. 

Fraud Prevention

  • Identify fraud before its occurrence.
  • It’s proactive, firms take necessary steps to avoid scams and can take advantage of fraudster mistakes. 
  • Fraud prevention measures all the user, transaction, and device data, and analyse how the information was sent, which parties are involved, and when it was made. 
  • Typically, detection monitors the data pattern to understand fraud. 

Importance of Fraud Detection

Online businesses need real-time and advanced fraud detection systems as there is no way around it. Spoofing attacks affect firms in different forms, but they are pervasive. 

identity fraud insights 2024 key statistics

Industry-Specific Fraud Trends in 2024

Digital Technology Blooms Fraud Rate

A rising fraud risk comes with the growing fraud detection solutions, such as digital advertising and cryptocurrency. When fraud detection systems were not fully developed, most advertisements ended up redirecting to bots rather than potential clients. That’s how scammers dodge people and grab their hard-earned money to become rich illegally. Rising fraud rates highly impact FinTechs, banks, and other financial firms. 

Scammers Leverage Advanced Methods to Bypass Conventional Detection Procedures

Scammers trick people through fake identities, but with false information to inflate assets, enhance their creditworthiness, and generate a positive result. The primary concern is that conventional fraud detection systems just focus on recognising the fake identities but not their documents. That’s why it’s complicated for firms to restrict scammers by depending on traditional methods. 

Secondly, a significant threat to firms is a synthetic identity scam which is when a fraudster merges both fake and real personal IDs that serve multiple purposes, including bank, social service, and credit card fraud. Synthetic fraud is more complex to identify as the application is, in part, based on real information. 

Firms have to be prepared to deal with the rise in illegal activities. For example, in 2023, a Facia identity theft report revealed 1326 data breach cases in the US alone, bypassing over 28 million records. The Federal Trade Commission (FTC), within the first half of its tenure, received more than 1.7 million scam reports.

Rise in Business Email Attacks 

Business email compromise (BEC) targets individuals and firms to transfer money is one of the fastest-growing financial crimes as per FBI’s 2022 Real Estate Wire Fraud and BEC Congressional Report.  As reported by the Internet Crime Complaint Center (IC3), fraud from BEC attacks is $2.4 billion, which is a fivefold rise since 2016. However, these figures will grow with the increase in remote work and distributed workforce. 

FBI announced a public service message disclosing a 65% hike in BEC fraud from July 2019 to December 2021. The concerning point is that scammers are grabbing money and transforming it into cryptocurrency which is even harder to track. 

Compound Complexity of Cryptocurrency and Alternative Payment Methods 

Payment methods such as cryptocurrencies and e-wallets are gaining prominence, representing 29% of all money lost in fraud and 24% of global transactions. In 2021, cryptocurrency scams reached $6.2 billion, increasing to 80%. In the coming years, the cryptocurrency fraud rate will rise due to consumer interest and little awareness. 

Leading Practices for Online Fraud Detection

The following are the best practices for firms who want to implement fraud detection systems: 

Identify Fraud Threats in All Departments 

First, recognise fraud attempts and the potential damage they can do to every department. Afterward, categorise them as low, high, or medium threats. Implement fraud detection solutions along with getting help from stakeholders or leads in every department that deals with scams.

Implement Facia’s Fraud Detection System 

Facia’s fraud detection solutions restrict scammers as it works speedily to secure the firm. To streamline the procedures, it’s highly advisable to implement this advanced system in firms and train staff accordingly. Update this technology to get more out of it. 

Audit and Analyse Fraud Threats Continuously

After implementing fraud detection solutions, it also ensures monitoring and auditing for potential threats. This tells that advanced techniques are operational to restrict types of fraud.

Train Staff for Fraud Detection Systems

The technology operates better when the staff knows how to operate it. So, it’s advisable to train staff accordingly and give them a free hand to operate fraud detection technology. Give them training sessions from time to time so they may learn better. 

Revise Fraudsters Profiles Occasionally 

Customise the system so it can detect imposter behaviour by going through their profile from the last six months to detect any change in their fraud activities or if they are using any highly sophisticated technology. Add risks to the fraud detection system by re-examining fraud profiles with the passage of time. Imposters are continuously changing their methods, so list them in the company’s system to recognise them instantly. 

Combat Fraud with Facia AI Technology

Firms that don’t transform their conventional process are highly vulnerable to spoofing attacks. Therefore, defence scammers update the firm’s traditional systems and solutions with fraud detection systems. Online fraud detection is essential in all sizes and types of firms, as scammers don’t differentiate and attack any person who seems to be penetrable.

Facia fraud detection solutions automate the procedure of analysing fake or real users through liveness detection technology that is ISO Level1 certified.  This immediately detects manipulated users, providing a no-touch solution that can easily be trusted. By incorporating a facia fraud detection system into business workflows, employees can save plenty of time and lessen fraud. 

Get started with Facia today to restrict scammers and save your business from millions of losses. 

Frequently Asked Questions

What is fraud detection?

Fraud detection is a set of processes and analyses aimed at identifying and preventing unauthorized financial transactions or activities. It is crucial for protecting individuals and organizations from financial deceit and theft.

How does fraud detection work?

Fraud detection analyzes patterns and anomalies in transactions or activities that deviate from the norm. It utilizes advanced technologies such as machine learning, artificial intelligence, and data analytics to scrutinize vast amounts of data in real-time, identifying suspicious behaviors or transactions indicative of fraud.

How do you detect online fraud?

Online fraud detection employs methods like Transaction Monitoring, Identity Verification Checks, Device Fingerprinting, Behavioral Analysis, and Data Analysis. These techniques are crucial for observing transactions in real-time, verifying user identities, tracking devices used in transactions, analyzing user behavior, and employing big data technologies to detect fraudulent activities.

What is the most common way fraud is detected?

The most common method of fraud detection is through transaction monitoring and analysis, continuously observing transactions for unusual patterns that deviate from established norms, such as unusually large transactions, a high frequency of transactions, or transactions from new locations, signaling potential fraud.

What are the risks of online fraud?

The risks of online fraud include Financial Loss from unauthorized transactions, Identity Theft, Damage to Reputation affecting businesses and customer trust, Operational Disruption of normal business operations, and Legal Consequences for failing to protect user data or prevent fraud effectively.