As more industries recognize the value of moving many of their functions online, they are encountering new risks. Thwarting online fraud is a multi-million-dollar industry, continually fighting to stay one step ahead of perpetrators. Fraud is very damaging to a company's reputation, and for good reason.
Any entity that handles users' sensitive information has a responsibility to them to protect that information. Failing to do so can cause a potentially catastrophic loss of business, if not open them up to legal liability. Fortunately, human fraud detectors have an ally: artificial intelligence.
Online Fraud, Hacking, and Phishing
To commit fraud is to deceive someone for financial gain. There are a variety of ways for perpetrators to commit online fraud, from bypassing or hacking security features, to "phishing" — simply asking people for their passwords or other sensitive information.
While humans are pretty adept at spotting patterns and picking up on fraudulent activities, it can take a long time to sort through all of the necessary data. Humans are also error-prone by nature, and mistakes can become very expensive and frustrating for clients. That's where artificial intelligence comes in.
How AI Stops Fraud
Artificial intelligence can sort through massive amounts of information in a relatively brief period of time, making it much more efficient at detecting inconsistencies. Machine learning can pick up on patterns, making it useful at detecting who is likely to commit fraud.
Before someone commits fraud, three circumstances generally need to align: a financial need or desire, an opportunity, and the ability to justify committing the act. Machine learning can analyze these "tells" over time and pick up on who is likely to attempt fraud.
For example, if an employee posts about financial woes on social media, that's two potential signs that artificial intelligence might flag: a need, and the opportunity. After fraud had already occurred, things are a little more straightforward. Artificial intelligence can crunch numbers and look for discrepancies, no behavioral analysis needed.
AI Fraud Detection in the Financial Sector
Banking regulations and policies change frequently, and hackers are always working to step up their game. For these reasons, it makes sense for the banking industry to turn to artificial intelligence for some fraud detection help.
Putting bots in customer service positions allows banks to help mitigate risk by automating compliance and eliminating human error. People can have bad days or make careless mistakes — chatbots and algorithms don't. It's easy for algorithms to pick up on anomalies in transaction data. If a customer's location or device don't match up with their transaction history, that's a sign of potential fraud.
Machine learning is also useful for reducing the impact of fraud detection and prevention on users' experiences. Transactions can go more quickly and smoothly if there's an automated anti-fraud system in use.
AI in the Medical Industry
Detecting medical fraud is a unique challenge. Instead of using deception to access someone's bank account directly, fraudsters might bill for services that a patient didn't actually receive or bill a simple procedure as a much more complex, expensive one. Here, it's necessary to analyze more behavioral data.
Artificial intelligence can pick up on discrepancies in doctor's notes, insurance claims, and patient records. If a patient is billed for a visit or service they never had, AI can find the inconsistency between their patient record and insurance claim.
If a patient in need of a routine procedure is billed for a more expensive, complicated one, AI can compare their billed procedure to what the majority of patients receive for the same issue.
Challenges in Implementing AI
While artificial intelligence can be a huge boon when it comes to preventing and detecting fraud, it has a few drawbacks. For one, all AI is limited by the same thing: garbage data in equals garbage data out. If it's not possible to feed an algorithm a sufficient quantity of useful data, that algorithm won't be able to reliably detect fraudulent behaviors. This means that human fraud prevention teams can end up wasting time sifting through piles of false positives instead of pursuing cases of actual fraud.
Another problem lies in adaptation. While using AI can potentially save millions of dollars, it can cost a lot to initially put in place. Even then, the job isn't done — as soon as fraudsters' patterns get figured out, they change them to avoid detection.
Both artificial intelligence and human fraud prevention teams need to keep learning to detect and flag new behaviors as they continually emerge. With the prevalence of online fraud, few companies can afford not to have some kind of AI-based fraud detection in place. Using an algorithm supplied with good data allows human fraud prevention teams to spend their time on higher priority tasks, makes things easier for end users, and saves money.
If your business has fallen victim to computer fraud let the experts at Roman help you get peace of mind. To request a consultation, or to submit a case, contact Roman by calling us at 800.422.9032 or by sending us an email.