In the world of financial services, AI is no longer an experimental concept: Today, it’s a proven boon to both organizations and customers. In fact, AI is expected to increase the profitability of the financial services industry by 31 percent by 2035.
According to McKinsey & Company, financial services companies use AI most for service operations, risk, marketing and product/service development.
Drilling down further into these use cases, let’s look at three major applications of AI in the financial services industry:
- Risk management
- Fraud detection
We’ll start with robo-advisors.
With the help of advanced algorithms and mathematics, automated financial advisors known as robo-advisors have ushered in a new era of investment management.
In a survey from Financial Planning, where 37 percent of respondents said that robo-advisors will change wealth management.
Robo-advisors have been adopted by some of the biggest financial institutions in the world, including Wells Fargo, Charles Schwab and Morgan Stanley, as well as online-only banks like Ally Bank.
So far, their adoption has paid off: Barron’s reported that in 2017, automated investment platforms surpassed $200 billion in aggregate assets globally.
What’s more, that number is expected to increase significantly over the next few years. According to a report from Deloitte, robo-advisors are expected to manage more than $16 trillion in assets by 2025.
As Ken Schapiro, founder and publisher of The Robo Report, told Barron’s, “This robo movement isn’t going away.”
Risk management is of vital importance to financial institutions of any kind. Without it, organizations would be unable to clearly identify long-term objectives or comply with regulations.
Through AI and other forms of digitization, risk management can become even more precise, and banks are taking notice: According to McKinsey & Company, 70 percent of global systemically important banks (G-SIBs) state that a digital risk transformation is now in place.
This movement isn’t limited to the U.S., either: Chinese tech giant Baidu has started using AI to calculate the creditworthiness of individuals.
As an increasing number of organizations turn to AI for risk management, it’s likely that AI will become embedded in the roles of human risk managers. Risk and AI experts Daniel Wagner and Keith Furst explained that “AI may not replace risk managers, but risk managers who use AI will replace those who do not.”
With AI’s ability to rapidly and effectively analyze colossal amounts of data, it was inevitable that it would be used to detect fraud faster than humans ever could.
This has the potential to prevent billions of dollars in losses: According to a 2017 report from the American Banking Association, bank deposit account fraud cost banks $2.2 billion in 2016.
To avoid those losses, many banks are turning to AI.
The Wall Street Journal reported that Capital One is using AI to detect and prevent fraud in real-time, as well as to reduce the number of false positives. According to Nitzan Mekel-Bobrov, managing vice president of machine learning at Capital One, AI allows the company to be “protective, but not overprotective.”
In an effort to help customers, CitiBank has invested in AI that can quickly detect and alert customers of fraudulent or suspicious activity. Meanwhile, Bank of America is using AI to help employees detect fraud, too.
These examples are far from being the only applications of AI in the financial services industry: From portfolio management and algorithmic stock trading to customer service, the possibilities seem to be endless.
AI has already drastically transformed the financial services landscape and will undoubtedly continue to do so well into the future.