If your company acts like most financially-concerned businesses, you’ve already implemented at least some internal controls to uncover and prevent fraud within your expense system.
Maybe you’ve tied spend limits to your purchasing cards. Or, perhaps you are restricting use on specific Merchant Category Codes.
But while these steps are all important and useful, are your current controls enough? Upon closer examination, you might find more ways to improve your program’s fraud detection and take it to the next level.
A great way to take that next step is by recognizing and taking full advantage of the role data can play in fraud control. The data generated from your company’s transactions is rich with information that, once tapped into, can be extremely useful in preventing fraud.
Consider the following data-driven methods that can detect and deter fraud like never before!
Data mining to prep fraud detection
Data mining is the act of taking data from your expense transactions, examining it, and analyzing it to determine patterns of behavior.
Because it looks at real-use behavior trends on a grand scale, data mining allows you to discover and prevent fraud in a deeper way than simply setting use-restriction policies.
Because of its “all-encompassing” nature, the use of data mining is less limiting in the types of fraud it can discover. Whether the act consists of personal expenditure, invoice overpayment, or unauthorized use of payment cards and accounts, data mining digs out and identifies the precise cause of the fraud.
It also provides insights on where these fraudulent behaviors are actually originating and who is responsible — helping you get to the source of the matter.
Lastly, it has the ability to check and analyze massive amounts of information, and yet streamline the process. No human alone could go through and analyze the same amount of data — and do so as quickly and correctly — as the artificial intelligence (AI) behind data mining. Data mining processes a staggering amount of data, while being much more efficient and effective.
Machine learning for fraud control
A huge way to ramp up your fraud control and take it yet another step further is with the introduction of machine learning.
Machine learning uses the data that’s mined from your company’s purchases, processes it with algorithms, and determines patterns from it over time — particularly in regards to fraudulent expense card use and transactions — all on its own.
Most methods of detecting fraud only do so after the fact. However, with machine learning, once the system “learns” the behavior trends, it then creates sets of data and rules that can often discern fraud in a more proactive way, that can actually lend itself to the prevention of fraud.
Moreover, machine learning happens without the need for human intervention. No rules have to be pre-programmed into the system. Instead, it uses its own AI to determine rules and sets of data by itself, based on the behavior it observes.
And, since its fully automated, machine learning eliminates the need for extra human resources that a company would have to seek out, train, and, of course, pay.
Taking the next step
As your company grows, so will your transactions. Having the means to track those increasing expenditures will become exponentially important. The ability to tap into all of that new and ever-growing data to discover and prevent fraud will be all-the-more valuable to your expense system, as well to your company’s overall financial health.
Card Integrity has the tools that can help you take your fraud program to the next level and make it even better than what it currently is. We understand and utilize data mining and machine learning in our solutions, so that your transaction data is always working for you, in the most efficient and effective way.
To learn more about how Card Integrity uses AI to create solutions that help you go to the next level, call us at 630-501-1507, or contact us today.