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Top 7 Techniques and Methods for Fraud Detection

Consumers lost $5.8 billion in fraud in 2021, according to the Federal Trade Commission. This represents a 70 percent increase when compared with the year previously. Furthermore, a record-breaking 2.8 million people filed fraud complaints.

These fraud statistics show why it is imperative that businesses dedicate time and resources to fraud detection and prevention.

Not only is fraud rife but you need to consider what would happen if your business were to fall victim to such a breach. You would face losses in the form of fraud losses, non-compliance fines, customer compensation, the cost of rectifying the issue, and the monumental expenses associated with rebuilding your reputation.

This can be very difficult to come back from, which is why it makes sense to deploy premium fraud detection methods so you can reduce the chances of such an incident happening. 

With that being said, let’s take a look at some of the best techniques and methods for fraud detection to help you get started:

1. Use a specialist fraud detection solution

There is only one place to begin, and this is by using a specialist fraud detection solution. This is even more imperative in industries whereby fraud is rife and there are more stringent regulations, such as banking.

When it comes to fraud detection in banking, there are many rules and regulations you need to adhere to. At the same time, there are lots of risks throughout the process.

Customer onboarding is a prime example of this. As we have moved to the digital onboarding space, there are regulations like AML and KYC that need to be followed. At the same time, fraudsters are getting more and more sophisticated, using synthetic IDs to try and trick the system.

As a consequence, it is imperative that banks find methods of fraud detection that are stringent while reducing friction. The only way you can do this is if you use a solution that has been designed specifically for the banking sector.

2. Use AI to detect fraud

Artificial Intelligence (AI) is one area of technology that is thriving at the moment, and we are certainly seeing it play an increasing role in fraud detection. It can help companies to streamline processes and improve their internal security.

Machine learning can help to detect fraud because ML algorithms can learn from historical fraud patterns, recognizing them in future transactions. There are both unsupervised and supervised learning methods of machine learning.

In supervised learning, a random sub-sample of all records will be manually classified as either non-fraudulent or fraudulent. On the flip side, with unsupervised learning, methods look for common patterns, i.e. fraudulent patterns, and correlations in the raw data. Predictions are created without extra labeling. 

Neural networks are also being used in AI, performing forecasting, generalization, clustering, and classification of fraud-related data, and then comparing them against conclusions that have been raised in formal financial documents or internal audits.

We’re also seeing data mining play a key role in fraud detection. This will segment, classify, and cluster data, automatically locating rules and associations in the data that may indicate interesting patterns, including those relating to fraud.

Finally, pattern recognition algorithms can also be used to detect suspicious behavior patterns, either manually or automatically. There are other techniques as well, including sequence matching, decision theory, Bayesian networks, and link analysis.

3. Prevent bots

A lot of fraud is carried out using bot software at the moment. There are many different strategies that bots can use, including entering thousands of passwords and user combinations until they ‘crack the code’ and gain access to someone’s account. 

Either way, you need to make sure that you have an effective bot management solution in place. However, the problem today is that a lot of the bot tools available are out of date.

They rely on the likes of CAPTCHA, which only serves to frustrate the human user, making them do all of the work. Instead, it makes sense to look for a solution that requires the bot to do the work via difficult cryptographic challenges. 

This essentially makes your company too expensive and resource-intensive to crack, and so the hackers will focus their efforts elsewhere instead.

4. Teach your employees about fraud

Aside from the suggestions that we have mentioned so far, it is important to educate your employees about fraud so that they know what to look out for and how they can prevent your business from becoming the next victim.

A lot of cybercrimes happen today due to insider breaches. While this can sometimes be because of a malicious insider, it is often because employees make a security mistake without realizing it. We often take for granted that our employees may not know the basics about creating strong passwords and avoiding phishing scams.

At the same time, by educating your employees on fraud, they will get a better understanding of what they should be looking out for while doing their job. This increases the chance that they will be able to spot a fraud incident, enabling you to prevent it before it turns into a much bigger and more serious issue for your business. 

5. Use 3-D secure

We also recommend that you use 3-D secure for your online store. This is something that more and more businesses are embracing, and rightly so.

If you have never heard of 3-D service before, this is a type of technology that operates as a PIN code whenever someone makes a purchase online. The objective here is to authenticate purchasers to make sure that they are the authorized cardholder.

A lot of businesses were hesitant to use the original 3-D Secure version. Nevertheless, a lot of changes have been made, with 3~DS 2.0 and later versions addressing the shortcomings and concerns that businesses had. 

Now, most merchants view 3DS as a necessity to prevent fraud and subsequent chargebacks. If you’re not using this, now is the time to implement it.

6. Geolocation

Geolocation is an effective and popular tool in fraud detection. Whenever someone submits an order on your e-store, this technology will pinpoint where the user is located while making their purchase. 

You can then automatically verify whether this is a legitimate transaction by comparing it with the data the issuer has on file and the information submitted during the checkout process. 

This solution is not sufficient on its own to prevent fraud. After all, someone could easily make a purchase while on vacation. However, it can be used in conjunction with other strategies to ensure you have an effective approach to verifying transactions.

7. Statistical data analysis

There are a number of different approaches you can use when it comes to statistical data analysis for fraud detection. This is all about conducting detailed investigations to detect and validate fraud. 

Let’s take a look at some of the different approaches to get a better understanding:

  • Data matching – Data matching is used to compare two collect data sets, i.e. fraud data. This procedure can be carried out either base on programmed loops or algorithms. Furthermore, data matching is used for removing duplicate records and identifying links between two data sets for security, marketing, or other purposes.
  • Probability models and distributions – With this technique, you will map probability distributions and models of different company fraudulent activities, either in terms of probability distributions or different parameters. 
  • Regression analysis Regression analysis enables you to assess the relationship between two or more variables of interest. It will also estimate the relationship between dependent and independent variables. This will give you the ability to understand and identify relationships between several variables of fraud, giving you the power to predict fraudulent activities in the future. These predictions are based on the utilization patterns of fraud variables in a possible fraudulent use case. 
  • Statistical parameter calculation – This refers to the calculation of a number of statistical parameters, including probability distributions, performance metrics, quantiles, and averages for fraud-related data collected throughout the capturing process.

Protect your business from fraud today

So there you have it: some of the best techniques you can use when it comes to detecting and preventing fraud at your business.

It does not matter what industry you operate in or how big or small your company is, fraud detection should be a priority for everyone today. Use the techniques and methods we have mentioned above to help you get started.

And, don’t forget; fraud detection is not a one-time thing. Cybercriminals are getting more and more sophisticated, so you need to make sure you continue to work on this area of your business.

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