Real-Time Fraud Detection – Everything You Need To Know

Traditional fraud methods cannot detect fraud when it occurs. As fraud continues to evolve, traditional detection methods, such as manual review processes and rule-based systems, are no longer effective and efficient, posing a significant challenge for businesses.

As the rate of online transactions grows exponentially, fraud detection becomes more complex. Businesses need to manage Artificial Intelligence (AI) and Machine Learning (ML) workloads to stay ahead of the curve and prevent fraud.

Today, businesses confront various threats, including identity theft, credit card fraud, account takeover fraud, and insurance fraud. Real-time fraud detection systems such as HyperVerge ONE, Onfido Verification Suite, Socure ID+, and Jumio Platform mitigate such risks.

Let’s understand real-time fraud detection from the basics.

What is real-time fraud detection?

Real-time fraud detection involves monitoring and identifying any fraud taking place in real-time. The process instantly identifies suspicious activity as it happens. Thus, detecting fraud early saves time and money, as well as the expense of manual investigation and corrective actions.

Real-time monitoring is essential for a strong fraud prevention strategy. It involves detecting fraud, monitoring all digital transactions in real-time, and looking for any signs of fraud. 

This modern and proactive approach raises alarms when it detects something unusual or suspicious in real-time. This saves money, protects the business’s reputation, and maintains customer trust.

Let’s see what sets real-time fraud detection apart from traditional fraud detection methods.

What makes real-time fraud detection better than traditional fraud detection?

Here’s a comparison highlighting why real-time fraud detection is superior to traditional approaches:

Aspects	Real-time fraud detection	Traditional fraud detection
Approach	Facilitates a proactive approach to detect fraud in real-time and alerts customers and vendors immediately.	Offers a passive approach to fraud detection. It may also involve unintentionally detecting past fraud, either by luck or confession from the perpetrator.
Timeframe	Achieves immediate fraud detection through proactive measures for identifying and preventing fraudulent activities.	Detects fraud after it takes place, thus causing a delay in response.
Use of AI	Real-time fraud detection utilizes AI’s capability for increased efficiency and accuracy.	Traditional fraud detection systems rely on rule-based approaches and manual processes, which increase the time and effort required to detect fraud.
Preventing loss	Real-time fraud detection minimizes loss and prevents damage to a business’s reputation. This gives businesses a chance to intervene and prevent it from happening.	Traditional fraud detection systems do not detect fraud in real time, leading to unavoidable financial losses as well as brand reputation.

Now that you understand the importance of real-time fraud detection, let’s see how it works.

What are the challenges of traditional fraud detection?

Here are 4 key challenges you might face as a business owner if you choose not to opt for real-time fraud detection strategies.

1. Data analysis on a large scale

Data analysis is crucial of real-time fraud detection. However, when large firms or financial institutions gather a large amount of data to analyze, they need a secure place to store it. They also have to prevent data breaches, bringing a whole new set of problems.

Solution: Strategic allocation and compression are some of the best ways to accommodate large volumes of data. Another way of data management is incorporating a third-party solution provider like HyperVerge, Seon, and Sumsub, which takes care of all the additional needs and requirements with real-time fraud detection systems.

2. False positives during identification

A false positive occurs when a security system detects legitimate transactions as fraudulent ones. As fast as an AI module can be, it can still make mistakes, resulting in false positives. Businesses must minimize false positives since they can hinder the customer and merchant’s seamless experience.

Solution: Advanced machine learning algorithms and customizing the set rules can decrease the number of false alarms in real-time fraud prevention strategies.

3. Risk of worsening user experience

Extra security steps require more work for legitimate customers to verify and authenticate themselves as valid individuals. This, along with false positives, can infuriate customers and worsen the business’s user experience.

Solution: Additional safety and seamless customer experience often conflict. Businesses must balance stricter safety standards and customer experience to achieve optimal results in both areas. To do that, businesses have to increase the time efficiency of a real-time fraud detection system using AI and ML.

4. Difficulties integrating real-time fraud detections into an existing system

When you have an established business structure, it can be tricky to incorporate a real-time fraud detection system without impeding the existing workflow. In this case, fraud detection and prevention have to be a custom system that adapts to your business structure, integrates seamlessly with your business, and goes live quickly.

Solution: Customized APIs that better suit a real-time fraud detection system to an existing process are the best way to achieve seamless integration. Therefore, businesses should choose a third-party solution provider with customizable APIs to go live with a real-time fraud detection system in hours.

If you want to implement real-time fraud detection in your business but want to avoid these obstacles, it’s preferable to choose a professional solution provider.

Top 5 real-time fraud detection solution providers for your business

Here’s a structured explanation of each fraud detection solution provider, along with their key features:

Solution provider	G2 ratings (out of 5)	Key features
HyperVerge	4.7	ID verification, KYC, AI-based fraud prevention, OCR, anti-money laundering (AML) screening, document verification, deep fake detection, KYB, and customer onboarding
Sumsub	4.6	ID verification, KYC, and AML
Jumio	4.1	ID verification and AML screening
Onfido	4.4	Document verification, biometric verification, and ID verification
Persona	4.5	Risk assessment and ID verification
Trulio	4.4	ID verification and business verification

As you can see in the table, multiple solution providers can implement real-time fraud detection in your business. However, HyperVerge stands out with more custom APIs to offer, and customers love it, as the high G2 review score suggests.

How does real-time fraud detection work?

Real-time fraud detection is an advanced system that identifies multiple types of fraud (more on that later). As a result, it consists of protocols such as data analysis, artificial intelligence, and real-time monitoring that function at their best. The following three phases encapsulate how a real-time fraud detection system works.

Phase 1: Collect and analyze data

Data collection and analysis involve gathering and examining raw data to spot patterns and draw meaningful conclusions. To catch a fraudulent transaction while it’s happening, the solution must accurately differentiate between a normal transaction and a fraudulent one. For that, the system needs to absorb and analyze heaps of data.

Phase 2: Use AI for behavioral analysis

Behavioral analysis uses an Artificial Intelligence (AI) module and general machine learning to recognize a particular account’s transaction behavior. Combined with fraud data analytics and predictive analytics, this analysis allows the module to detect anomalies as quickly and accurately as possible.

Phase 3: Verify identity during transaction

One of the key aspects of fraud prevention is a customer’s digital identity verification during a transaction or account operation. AI-powered facial recognition is another critical aspect of preventing identity fraud and deep fakes. Learn more about how HyperVerge helped Freo reduce fraud and increase business.

Now that you know how real-time fraud detection works, let’s check out what benefits it brings to the table.

What are the benefits of real-time fraud detection?

Many businesses are constantly under the threat of fraud, and having a safety net can reduce the severity of the threat. Here are 6 benefits that come with a real-time fraud detection and prevention strategy in detail.

1. Reduces overall loss from fraud

One of the primary advantages of real-time fraud detection is reduced financial losses. If you find out about a fraudulent transaction after the fact, you may or may not be able to reverse the damage. However, if you can prevent the transaction from finishing in the first place, you will save both money and time.

2. Improves customer experience

In most cases, customers are just as much fraud victims as businesses and suffer the damage. If incidents like this appear frequently, your business may lose the customer(s) altogether. Preventing fraud is a great way of retaining your customers and attracting new ones.

3. Decreases chargeback frequency

If a customer finds out about a fraud they were a victim of, they will issue a chargeback. In most cases, the merchant has to bear the loss, further adding to the damage. Hence, preventing fraud in the first place results in a decrease in chargebacks due to fraud.

4. Protects brand reputation

Out of many businesses and competitors, you can make your business stand out, boasting enhanced security to fight fraud. Such a feat elevates the brand reputation and customer trust, which can also result in increased customer onboarding.

5. Ensures easier compliance 

If your transaction vendor notices frequent chargebacks from your business, they may impose penalty fines. Additionally, they can increase fees for non-compliance with cybersecurity rules and regulations. Real-time fraud detection will make sure that you easily comply with ever-updating rules and regulations.

6. Improves cost savings

Besides direct financial losses, there are various costs associated with fraud for your company. These costs can be chargeback fees, costs associated with recovery efforts, fees for legal proceedings, and regulatory penalties. Thus, fraud prevention in real-time allows additional cost savings apart from the direct loss of money you fend off.

So far, we have discussed the process and benefits of real-time fraud detection, but which frauds can we detect? Let’s find out.

Top 6 types of fraud real-time fraud detection covers

Here are 6 popular examples of fraud that real-time fraud detection can detect.

1. Payment card fraud

Payment card fraud is one of the most popular types of online payment fraud. In this type of fraud, a criminal obtains the private data of a cardholder, such as the credit card or debit card number, expiry date, card verification value (CVV), bank account number, and/or transaction PIN, to make illegal transactions on behalf of the cardholder.

2. E-commerce fraud

E-commerce fraud involves a fraudulent transaction on an e-commerce platform that incurs a loss on the business, customer, or both. E-commerce fraud also includes a fraudster (posing as a legitimate customer) exploiting the platform’s shipping and return policies for personal gain, incurring losses for the business.

3. Insurance fraud

This type of fraud is when someone files false claims to gain payouts illegally. Insurance fraud occurs when someone knowingly lies to the insurance company to gain benefits or denies benefits on the benefactor’s behalf. Here, the former negatively affects the insurance company, while the latter negatively affects the benefactor. The healthcare industry is one of insurance fraudsters’ most frequent targets.

4. Mobile payment fraud

Mobile payment fraud means exploiting vulnerabilities or weak spots in mobile payment or digital wallet services to make unauthorized transactions. If a fraudster gains access to someone’s mobile device or transaction PIN, they can easily make transactions before anyone knows anything.

5. Chargeback fraud

Chargeback fraud is when a person orders an item online and falsely claims that the item is either damaged or undelivered. In such a case, the merchant is liable to pay back the amount for which they sold the item. In many cases, apart from the money, the merchant also has to bear the loss of the product they sold.

6. Account takeover (ATO)

Account takeover fraud is the process of a fraudster assuming the identity of an account holder and making illicit transactions for their own benefit. In these cases, the legitimate account holder has the right to gain compensation, thereby costing the business. Even with implementing CKYC (Central Know Your Customer), cybercriminals exploit vulnerabilities and loopholes through dormant accounts or obfuscation tactics.

 Now, let’s check out the benefits of using real-time fraud detection for your business.

How can businesses implement real-time fraud detection?

Businesses can implement real-time fraud detection through these 3 significant protocols to identify frauds quickly.

1. Implement stricter safety standards

Increasing safety and security is a no-brainer to prevent and catch fraud in real time. Solutions like multifactor authentication, face recognition, KYC, and biometrics help reduce the amount of fraudsters that can get past the transaction process.

2. Use AI to decrease detection time

AI can be the backbone of a competent real-time fraud detection solution. Businesses can leverage AI to prevent fraud and minimize the time it takes to detect fraud. Here, advanced tools such as liveness checks, selfie verification, and deep fake detection come into play to detect any fraudulent attempt accurately. The less time it takes to identify a fraud, the more time we have to step in and prevent the transaction process from completing.  

3. Develop a system to help anticipate fraudulent transactions

A powerful machine learning module can help your real-time fraud detection solution predict or anticipate fraudulent online transactions. Businesses can speculate on fraudulent transactions in advance by utilizing data analysis and monitoring ongoing transaction processes. In such cases, opting for a solution provider that excels at AI-based ID verification, such as HyperVerge, can help detect fraud in real-time with high accuracy.

Now you know what methods you can use to secure your business with real-time fraud detection. However, it comes with its challenges that you should know about.

8 real-time fraud detection use cases across business sectors

Real-time fraud detection is crucial in combating various types of fraud across different industries. Here are the 8 significant use cases across various business sectors:

1. Detects fraud in financial services

Real-time fraud detection enables financial institutions to observe transactions closely and detect fraud, including unauthorized credit card transactions, account takeovers, and fraudulent loan applications. HyperVerge’s AI-based identity verification and KYC solutions verify the parties’ identities in real-time, helping reduce identity theft fraud and ensuring that all transactions are legitimate.

2. Enhances security in E-commerce platforms

E-commerce platforms face numerous fraud risks. Payment fraud, fake account creation, and return fraud are some. Real-time monitoring can help businesses identify fraudulent transactions or suspicious activities like unusual spending patterns and geographical anomalies through IP addresses while placing orders or repeated failed payment attempts.

3. Prevents identity fraud in telecommunications

Telecommunication companies can use real-time fraud detection to prevent identity fraud, where fraudsters use stolen or fake identities to obtain services. HyperVerge’s digital KYC solutions enable telecom providers to verify customer identities quickly and accurately during onboarding, reducing the risk of fraud.

4. Reduces insurance frauds in healthcare

Insurance fraud primarily targets the healthcare industry. Real-time fraud detection can help healthcare institutes identify fraudulent insurance claims. HyperVerge’s facial recognition and identity verification solutions assist healthcare providers in verifying patient identities and reducing fraud.

5. Prevents fraud in online marketplaces

Online marketplaces must ensure that buyers and sellers are legitimate to maintain customer trust. Real-time fraud detection can recognize dubious activities like fake reviews and fraudulent transactions. HyperVerge’s end-to-end digital KYC solutions can help these platforms ensure the legitimacy of their users.

6. Protects against digital fraud in gaming apps

In the gaming industry, real-time fraud detection prevents cheating and fraudulent transactions within games. This includes monitoring in-game purchases and identifying abnormal user behavior. Before fraud can tarnish your gaming app’s reputation, HyperVerge’s AI-led behavioral analysis and identity verification solutions can ensure a fair and secure gaming environment for your users.

7. Enhances safety in the government and public sector

Government agencies incorporate real-time fraud detection to prevent illegal activities like tax and benefit fraud. Real-time fraud detection systems can ensure only eligible individuals get government services and benefits. HyperVerge’s AI-based identity verification solutions help government agencies accurately verify identities and reduce false claims.

8. Prevents fraudsters from creating multiple accounts

If a fraudster gets a customer’s ID, they can create more accounts with the customer’s credentials to carry out fraud. Face deduplication technology identifies and flags duplicate faces in a database to prevent the same person from creating multiple accounts.

How does HyperVerge help you detect fraud in real-time?

If you want your business to have the fastest and most accurate real-time fraud detection system, you must choose a solution with a powerful AI platform. This is where HyperVerge stands out from the rest.

HyperVerge specializes in AI-based identity verification and KYC solutions, among other things. To detect and combat fraud in real-time, HyperVerge ONE provides solutions with a powerful AI model that excels at identity verification and facial recognition. HyperVerge also offers real-time data monitoring, an essential tool in fraud detection systems.

With over 800 million IDs verified, HyperVerge’s face authentication system with liveness detection takes as little as 0.2 seconds to match a face with 99.8% accuracy to detect fraud as it is taking place. HyperVerge’s end-to-end digital KYC solution, equipped with face de-duplication technology and multiple AI-based checks, can complete a call in 1 minute and detect fraudsters simultaneously.

“An excellent tool for easy fraud detection. This AI-powered tool is easy to use and has a quick turnaround time.The customer service is very impressive. The onboarding process is smooth and hassle-free.”-Abhishek K, CEO & Co-Founder, Small-Business ★★★★★ (5/5)

FAQs

1. What is the role of fraud monitoring?

Apart from looking for fraud in ongoing processes or transactions, fraud monitoring can yield useful insights into emerging fraud trends. It can help businesses stay prepared for any trending fraud.

2. What data is used in fraud detection?

Fraud detection uses various data such as transaction details, user profiles, and account information. Some real-time fraud detection systems also use IP location or other geolocation data to detect anomalies for possible fraud.

3. How are most frauds detected?

The most common fraud detection methods are using rules-based systems (employing predefined rules to identify potential fraud), anomaly detection, artificial intelligence, machine learning, behavioral analytics, and biometric verification.

4. Can real-time fraud detection help with credit card fraud detection? 

Yes, real-time fraud detection is one of the best ways to help with credit card fraud detection. Real-time fraud detection systems can catch unusual activities, such as unusually large transactions or a different shipping address that doesn’t match frequent customer locations.

5. What does the future of real-time fraud detection look like?

Artificial Intelligence (AI) and Machine Learning (ML) seem to be the driving forces behind the development and advancement of real-time fraud detection in the future. Since time is crucial in real-time fraud detection, the faster the AI module accurately detects fraud, the more effective and impressive it becomes. Moreover, Generative AI (GenAI) can be a foundation for effective real-time fraud detection.