Financial markets are among the fastest-moving markets around. People and organizations need to know where their money is, what it’s doing for them, and whether it’s at risk, on a moment-by-moment basis. Yet banks and other financial services organizations are often well-established, even venerable, with their names and reputations a vital tool in their ability to prosper.
The wealth-management industry is in the midst of some seismic changes at present. The traditional channels through which money has been managed and advice dispensed are now being decisively disrupted. And as a result, those who are being affected the most—from multi-billion-dollar hedge funds to retail investors managing their own portfolios—are now operating in an almost entirely new landscape.
With all of the new developments in banking these days, it’s easy to lose touch with what really matters: the customer experience. To enhance their customers’ journeys and earn their loyalty, research shows that bank staff need to develop effective communication channels, listen and then learn what matters most to customers. What’s important to them may not be precisely what bank employees expect.
Digitally native customers are driving banks to jump into the future by embracing technological breakthroughs such as artificial intelligence, machine learning and robotic process automation. And in the process, banks are discovering the many advantages of these innovations, from cutting down on costly human errors to improving everything from fraud management, operational efficiency and trading. As they progress through their digital evolutions, many are reinventing themselves for the better.
If last year was any indication of what financial markets will look like in 2019, we are in for a very bumpy ride. Last December alone, the Dow Jones Industrial Average fell and rose more than 8 percent as finance experts struggled to make heads or tails of a bizarre political climate, unsteady interest rates and global tariffs.
The rapid adoption of artificial intelligence and machine learning in all corners of the financial sector, particularly in anti-money-laundering (AML) efforts, has excited and inspired onlookers and participants alike. But as with all innovations, there are pitfalls to unquestioning acceptance that can actually worsen the situations these technologies are meant to address. Human intelligence must work cooperatively and in the lead role alongside AI and ML to guarantee the best results.