The Rise Of Machine Learning And The Risks Of AI-Powered Algorithms Posted on : Aug 23 - 2017

Back in the Old Days, you used to have to hire a bunch of mathematicians to crunch numbers if you wanted to extrapolate insights from your data. Not anymore. These days, computers are so smart, they can figure everything out for themselves. But the uncensored power of "self-driving" AI presents financial institutions with a whole new set of regulatory, compliance and privacy challenges.

More and more financial institutions are using algorithms to power their decisions, from detecting fraud and money laundering patterns to product and service recommendations for consumers. For the most part, banks and credit unions have a good handle on how these traditional algorithms function and can mitigate the risks in using them.

But new cognitive technologies and the accessibility of big data have led to a new breed of algorithms. Unlike traditional, static algorithms that were coded by programmers, these algorithms can learn without being explicitly programmed by a human being; they change and evolve based on the data that’s input into the algorithms. In other words, true artificial intelligence.

And this is one area where financial institutions plan on investing heavily. In 2016, almost $8 billion was spent on cognitive systems and artificial intelligence — led by the financial services industry — and that amount will explode to over $47 billion by 2020, a compound annual growth rate of more than 55%, according to IDC.

There are certainly many benefits to using these AI-powered, machine learning algorithms, particularly with respect to marketing strategy. That’s why money is pouring into data sciences. But there are also risks.

Dilip Krishna and Nancy Albinson, Managing Directors with Deloitte’s Risk and Compliance Consulting Practice, explain some of these risks and what financial institutions can do to manage through them.

The Financial Brand (TFB): Can you give an example of how financial institutions can use machine learning algorithms?

Dilip Krishna, Managing Director of the Risk and Compliance Consulting Practice at Deloitte: One financial institution is using machine learning in the investment space. They are collecting data from multiple news and social media sources and mine that data. As soon as a news event occurs, they use machine learning to predict which stocks will be affected both positively and negatively and then apply those insights in their sales and marketing process. View More