It is hard to believe that we just wrapped up another year. The beginning of a new year is one of the best times to both reflect on the previous years successes, while looking ahead at what the biggest challenges, priorities and opportunities will be for companies as they enter the new year.
The game of cat and mouse between the regulators and banks against money launderers has now moved to a new level – all thanks to the emergence of AI and machine learning technologies. AI and machine learning technologies have been around for some time, but have recently started coming into prominence in the world of financial services.
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.
The term “operational efficiency” is not new, and in fact, applies to many industries because it works toward a common goal: to optimize operations so they provide greater returns – whether they be faster time to market, greater volume and/or increased revenue – relative to inputs.
What’s not to like about a process that simultaneously slashes costs and boosts efficiency? Increasingly, senior executives of financial-services firms, with eagle eyes focused on the bottom line, are jumping enthusiastically into the RPA game. Perhaps surprisingly, others in these organizations, such as IT employees, are reluctant. But adopting robotic process automation to best advantage must involve the active participation of the whole company-wide team.
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 it feels as if artificial intelligence is taking over, there’s a reason for it. It is. The democratization of AI has begun, and the technology is set to change the world as we once knew it. Banks won’t be left out of the transformation. While bank senior executives cheer the cost-saving and efficiency-boosting potential of AI, bank employees may fear for their jobs. But that’s where reskilling steps in
Automation saves time, cuts cost and carries out routine tasks with unmatched efficiency, so who wouldn’t welcome it? Possibly the people whose income currently depends on carrying out those tasks. Digitalization is guaranteed to strip out much routine work in banking, but it will not necessary mean fewer bank jobs. Roles will be reinvented so that technology frees human staff to provide customers with excellent advice and service.
Weighing the possibility of adopting AI and automated decision-making is no longer a choice for banks; this technology has proved its worth in everything from combating fraud to meeting compliance requirements to providing excellent customer service via chatbots. As banks struggle to be profitable in the post-financial crisis era, AI has been an invaluable friend to those that have learned how to make it work for them.
What a huge advance it is that the financial sector now has robots to relieve the ever-growing pressure of regulation. Almost everyone handling or processing personal data now faces vastly increased compliance requirements once the European Union’s General Data Protection Regulation