How to Test Fraud Detection Software and What to Expect?

In the contemporary world, having a fraud detection software is essential for the well-being of any business. It can help protect your customers’ information and safeguard your company’s reputation. It also helps save a lot of money for companies. 

Today, around 46% of companies have reported that they have experienced some sort of fraud. With the increasing threat to businesses, companies have realized the importance of having a fraud detection software. With so many options available in the market, the question is which one is the best for your company and how to choose an effective fraud detection software. 

To reap the benefits of this technology, you need to know how to test it properly. This article discusses the ways of testing a fraud detection software. Before diving into the features of a fraud detection software and the expectations a company should have before investing money into the tool, let’s analyze the benefits of having such a software. 

What are the benefits of using fraud detection software?

The most obvious benefit is that it can help you detect and flag potential fraudulent activity. This can save your business a lot of money by preventing fraud before it happens and the information can help you take steps to prevent fraud in the future. Fraud management systems can help reduce the manual reviews that need to be done by the team. Automating the fraud detection process will boost the efficiency of the team.

Fraud detection software makes use of machine learning technologies that help in identifying and analysing patterns in a short amount of time that humans will be unable to comprehend.  With valuable insights into the types of fraud that are being committed, you can focus on other important aspects of your business – such as building a strategy and focusing on increasing your revenue.  

How to test a fraud detection software?

When testing fraud detection software, you should expect it to be able to accurately detect and flag potentially fraudulent activity. The first step in testing a fraud detection software is to create a data set that can be used to train the software. This data set should include a variety of different types of fraud, so that the software can learn to identify them. Once you have created this data set, you need to upload it into the software and let it run through its algorithms.

After the software has had a chance to learn from the data set, begin to test it on actual data. To do this, generate a series of transactions that you believe may be fraudulent. Once you have generated these transactions, submit them to the software and see how it responds. If the software is able to correctly identify the fraud, then you can be confident that it is working properly. However, if the software is not able to identify the fraud, then troubleshoot the issue. This may involve changing the data set that you are using to train the software or adjusting the algorithms that the software uses. Create a system that can track all of the transactions that occur within your company. This system should be able to generate reports that show you which transactions are most likely to be fraudulent.

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The best way to be satisfied that the software is working correctly, you should try to commit fraud yourself. This will help you understand how the software works and whether it is able to detect all types of fraud. Make a better decision whether to implement the software into your business or not.  With this information, you can then take steps to prevent these fraudulent transactions. Now that you know the steps, it is time to discuss some of the best features to detect fraud

 

Let’s get right into it:

Artificial intelligence/machine learning

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Test a fraud detection software using data from the company. If the software makes use of artificial intelligence, it will be able to detect a wide range of fraud. An efficient software will be able to provide a risk score. The higher the risk score, the higher is the chance of a fraudulent activity taking place. 

The software should also be able to take into account the historical data of the company. This will help in better understanding customer behaviour and detecting fraudulent activities.

With fraud detection using machine learning, it is possible to extract value from data that would otherwise be too difficult for humans to process. So, if a fraud detection software makes use of machine learning, it will be able to detect frauds that would be easily missed if there was a manual review. 

Ability to detect different types of fraud 

The software should be able to identify different types of fraud. Some of the common types are: account takeover, fake accounts, affiliate fraud, stolen credit card purchase, return fraud and bonus abuse. In simple words, the software should be able to detect fraud that is specific to the industry. For example, in the case of e-commerce, chargeback fraud is a common type of fraud that happens when a customer orders a product and then asks for a refund from the credit card company. 

 

Similarly, in the case of digital marketing, click fraud happens when someone clicks on an ad multiple times or clicks on an ad from a fake account. This helps websites earn more money since they are paid according to the number of clicks on their website. The higher the diversity of the types of fraud detection, the better will be your return on investment on the software. 

Number of false positives 

The fraud detection system should not be over-efficient. If the fraud detection software churns out a high number of false positives, it will deter customers. Imagine, if you were looking forward to purchasing a product from an e-commerce store that has been on your wish list for a long time. You have been saving to buy the product for a long time. Now that you finally have the money, you add the product to your cart. When you reach the checkout page, it keeps blocking your credit card due to some reason that you are not aware of. How frustrating!

In the contemporary fast-paced world, customers have little patience. In addition, the number of options available is too high. So, if it is hard to purchase from one platform, customers will move on to purchase from a competitor if their process is simple. Therefore, if the fraud detection system ends up giving a high number of false positives, it will result in genuine customers getting blocked. This in turn leads to customer attrition and a loss in revenue for the company.  

Summary of your expectations from a fraud detection software

One should expect that a fraud detection system is able to provide an all-in-one solution that helps businesses detect, investigate, and prevent fraud. 

The software uses artificial intelligence/machine learning to detect fraud and has a rule engine that can be customized to the specific needs of your business. It should be easy to use and able to provide valuable insights into the types of fraud being committed. Most importantly, expect that the software has a low false positive rate, which means that it does not block genuine customers. This is important because it ensures that customers can purchase from your platform without any hassle. It is a bonus if the software offers a free trial, so you can try it out before deciding if it is the right fit for your business. Another nice-to-have is the software’s ability to be quickly implemented into your business without having to spend a lot of time training employees on how to use it. In other words, the software should be easy to understand. Lastly, the software should also be updated on a regular basis with the latest trends in fraud. This will ensure that it is able to detect the latest types of fraud.

 

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