Cybersecurity is a growing concern in our densely connected, high-tech world, and the financial industry is a prime target because it contains a significant amount of money, not to mention potentially valuable customer data.
Statistics from PwC show a 130-percent increase in fraud incidents, all of which cause monetary losses and other disruptions for financial brands. However, analysts wonder whether artificial intelligence (AI) could finally stimulate meaningful progress in reducing such issues and others like them.
Although some banks are still reluctant to experiment with AI, others — including Wells Fargo and Ally — are exploring what it can do. They use it in a variety of ways ranging from risk analysis to chatbots that help users reset their passwords. As banks continue to discover AI’s capabilities and how they apply to daily operations, the likelihood goes up that more financial organizations will follow suit and find options that work for specific needs.
Cybersecurity has become a multi-billion dollar industry in Israel, which had over 400 firms specializing in it at the end of 2017. Company representatives there say they often partner with banks to see how AI and other technological solutions perform in real-world situations.
There are also Israeli firms that simulate attacks to determine the worthiness of individual solutions available from given companies. Outside of Israel, IBM uses its Watson AI platform to help banks find and shut down cyberattacks. Without the Watson technology, banks often lack information about past cybersecurity incidents, but IBM representatives hope to fill the gap with AI insights that get smarter with time and rely on input from multiple companies.
Not all cybersecurity incidents in the financial sector happen when infiltrators try to break in and snatch data. Sometimes, they occur when people engage in dishonest activities and a financial industry’s existing technology doesn’t pick up on them.
That’s why some financial institutions are beginning to use AI or invest in companies that specialize in it to attempt to cut down on fraud cases. As a growing number of people capitalize on the convenience offered by credit and debit card payments, AI algorithms have more opportunities to learn what differentiates a non-suspicious transaction from one that raises red flags.
In the summer of 2017, Mastercard acquired Brighterion, a company that uses AI and machine learning to provide real-time security analytics. Mastercard already depends on AI in other ways, but that investment signals that the card provider takes security seriously and thinks AI could provide necessary data. Such platforms can analyze billions of transactions and engage in things like sentiment analysis to gain a complete picture.
Financial experts are also hopeful about efficiently using AI due to the way it can adapt to changing trends. Cybercriminals regularly come up with new attack plans. However, AI can collect tremendous amounts of data and compare it against things currently happening on a network to detect potential instances of suspicious activity. The technology can then reduce false positives and find genuine matters of concern.
Recently, it became evident that HBSC was the top bank unknowingly complicit in a gigantic money-laundering scheme funneling money from Russia to the European Union called The Global Laundromat. To reduce the chances of something similar happening again, HBSC began working with an AI startup to use technology that could spot potential money-laundering activities. The system can analyze multiple information channels and gather data about customers from numerous sources, thereby doing more to curb money laundering than humans alone could feasibly achieve.
Analysts acknowledge that some representatives in the financial sector are reluctant to embrace AI because it is still a relatively new technology and may seem to some of them like an option that’s straight from a science-fiction novel. However, they point out that predictive analytics is one of the best tools available to use to safeguard data and pinpoint unusual occurrences.
Of course, technology isn’t perfect. Therefore, it must be coupled with intelligent people deciding how to use it most effectively to meet emerging needs.
Another thing to keep in mind about AI is that it’s adaptable. Many individuals are wary of using AI because they fear it will take over human jobs. Instead of assuming that the technology will replace what people do, perhaps people in the financial industry should start looking at how individuals can expand their skills to complement what AI does.
The information above highlights some of the many ways AI could make the financial industry more secure around the world and make it harder for criminals to orchestrate attacks. However, for it to be most useful, it’s necessary for the sector’s representatives to be open to the technological possibilities while being willing to grow their skillsets.
Bio: Nathan Sykes is the editor of Finding an Outlet. When he’s not writing about technology, he enjoys reading, traveling and a good beer.