Human beings are wary of machines, especially when entrusting them with the most important aspects of their lives, such as finances. But as machine-learning and artificial-intelligence technologies become more sophisticated, learning from human brains, they are proving that when programmed correctly, they offer a wide range of advantages, especially in banking. The more human beings use them, the more successful they become in achieving what they were created to accomplish.
Change is as much a part of life as breath itself, and that’s true in banking. Already in the midst of transforming itself to meet the expectations of its increasingly digitally inclined customer base better, COVID-19 gave it a swift kick that has expedited those adjustments. As society transitions into the “new normal”, what are some of the positive changes in banking that will remain even as the virus wanes?
The investment-management industry is undergoing arguably its most disruptive period ever. Thanks to a new wave of disruptive technologies, the very concept of investing is being transformed from a practice that was relationship-driven
Artificial intelligence has become a must-have for banks today. AI in the form of robotic process automation and machine learning is going a long way to help banks become more efficient in customer service, more compliant in adhering to regulations and more capable in tackling fraud. But like all good things, it comes with a few strings. What are the responsibilities for senior individuals and boards attached to the many benefits AI brings to banking?
Every finance department is facing the same challenge, no matter their size, expertise or industry. New technologies are entering the workplace, changing the way we work and completely upending business models. Nowadays, consumers are ‘always on,’ demanding rapid service and communications. People want to subscribe to products, rather than buy them. Even investors are asking a lot, for example insisting companies precisely predict demand to keep the bottom line lean.
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.
There are times when no one wants to see history repeat itself, and that’s the case among today’s investors in technology stocks. Some fear that the dot-com bubble burst of 2000 may repeat itself 20 years later. Although some tech stocks may be overvalued, the flourishing Fourth Industrial Revolution displays no signs of running out of steam any time soon. Caution is advised but not panic.
Although banks have been in financial services longer than anyone else, they have a thing or two to learn about customer service from the mammoths in the retail sector. Retail subscription services are taking off, promising to deliver combinations of products conformed to the needs and likes of customers, whose preferences are well known from data analyses. What similar steps can banks adopt in their drive to augment customer satisfaction?
Many of us struggle with the concept of carrying on a rewarding conversation with a chatbot, but recent improvements in artificial intelligence are making this technology increasingly more valuable to banks around the world. From helping banks to offer targeted customer products and services, to tightening the security of credit transactions, to cutting costs while improving employee engagement, AI’s contributions to making customer service better are too important to ignore.
There are enough new terms floating around banking to make one’s head spin, and along comes greenfield bank. This refers to the growing trend among incumbent banks to create standalone digital banks that are as agile and innovative as the fintechs and neobanks. After considering how difficult and expensive it is proving to be for banks to break out of their legacy-infrastructure moulds, this approach makes a lot of sense.