Machine learning sounds like something scary out of The Matrix or iRobot, but artificial intelligence and machine learning are already all around us impacting our everyday life, particularly interactions with computers, retail businesses, and our finances. While there may be a small creep factor in how some of this works, overall machine learning is doing a ton to protect our personal finances from fraud.
In our daily lives, machine learning does a lot more than send targeted advertisements your way. It looks at every credit card and debit card transaction, for example, to determine if you actually made the purchase. Through a combination of big data and artificial intelligence, businesses are working to save both you and themselves a lot of money. Read on to learn more about how and how it works.
What is machine learning?
Machine learning is a system where computers can “learn” how to respond to a series of patterns or data inputs. That’s a mouthful, so simply put you can think of it as a computer looking for patterns in giant data sets, and use those patterns to make a decision.
These types of patterns and decisions can reach into all aspects of our lives. The place you most likely see machine learning in action is when shopping online. Computers learn that people who look at a certain set of products on Amazon are likely to buy another list of product, for example, and Amazon uses those trends to advertise products you are more likely to purchase based on those browsing habits.
But while advertising is one of the ways we most visibly run into machine learning, it is happening behind the scenes in our banking and finances as well. Banks analyze virtually every transaction that goes through their systems looking for fraud, and other businesses use similar techniques to find patterns that stand out from the norm on the hunt for fraudulent activity.
How computers can detect fraud
With machine learning, computers are not quite smart enough to look at a data set and make a human decision. Instead, the computers look at the patterns to create a score, and a human sets the threshold on what score a computer deems to be fraud, and which are not likely fraud.
One of the biggest and most popular fraud prevention system in finance is FICO® Falcon® Fraud Manager, from the same company that makes the FICO credit score. Falcon is employed by banks, card issuers, and card technology providers to keep cyber and financial criminals from stealing money from you and your financial institutions.
Falcon and similar systems do this by looking at every transaction you and other people make. If you have multiple credit and debit cards, you can expect Falcon likely knows about all of them, and uses your transactions to build a profile of your regular activity. Each time you use your card, your bank processes the transaction through Falcon or a similar system. Based on the location, transaction amount, and other factors, that transaction gets a risk score. Depending on the score, Falcon will mark it as fraud or let it through as a regular transaction.
Banks tweak and adjust the ideal cutoff score at the same time FICO works to improve the Falcon algorithms and analysis. If they make it too sensitive, it will mark legitimate transactions as fraud and cut off your card at the register, which is a huge hassle for you. On the flip side, turning down the score sensitivities can lead to bad transactions going through. Managing this decisions process is the core of anti-fraud machine learning and the growing industry that supports this type of analysis.
The future of fraud prevention
We are just scratching the surface in what is possible in the world of fraud prevention from machine learning. Artificial intelligence, arguably the next evolution of machine learning, should do a lot more to prevent fraud as computers get smarter and stronger.
Fraud is a very expensive problem for finance companies and other businesses, so there is a lot of investment and development going on in this space. Some future ideas to prevent fraud go far beyond scoring transactions with a fraud manager like Falcon. If you think this sounds like a science fiction movie, strap yourself in for what the future has in store.
One major opportunity to prevent fraud is biometrics. Imagine an ATM machine scanning your retina and fingerprint in addition to a PIN. Maybe the credit card terminal will include a camera that takes a picture of your face and analyzes that photo against images your bank keeps on record, or even your social media profiles!
This article lists out 11 top companies working to fight fraud with machine learning today. The vast majority are focused on transaction fraud, identity theft, and similar scenarios. For example, CoreLogic has a major focus in mortgage application fraud, while identity theft prevention company LifeLock bought ID Analytics to help detect and prevent identity theft.
An exciting and fraud free future?
It seems like every time we make a big step forward in preventing fraud, the criminals come up with a new way to avoid it, or a new way to commit fraud. But with machine learning and artificial intelligence, commiting fraud is getting harder and harder.
In the future, biometrics will likely bring down the fraud rate significantly, but we can expect new bad guys to emerge and find a way to exploit it. Only time will tell if this game of cat and mouse will go on forever, or if we will eventually crush fraudsters for good.
But keep in mind that while businesses use machine learning to combat fraud every day, it is our role as consumers to protect ourselves. Always keep your computers and applications up-to-date. Use strong passwords and anti-virus programs. And stay vigilant against phishing and other scams. If you do, you are at the front of the curve and have the best odds of fending off fraud for many years to come.