Artificial Intelligence is expected to permanently change the banking industry in profound ways during the coming months and years. Companies want to seek a competitive edge by implementing more technology to achieve improvements in speed, cost, accuracy and efficiency. The key for global corporate enterprise is to benefit from the collective intelligence presented by RPA and cognitive technologies along with human workers. Only by having technology combine with human talent can global corporate enterprise achieve scalable intelligent automation. And only with scalable intelligent automation enterprise resiliency be realized.

Editor's note: This is a guest article from our partner Bain & Company, a top global management consultancy based in Boston. The company advises business leaders on strategy, marketing, organization, operations, IT, and M&A across industries, including financial services. As more fintechs enter the market and consumer preferences shift, traditional retail banks face significant challenges in attracting and holding customers while remaining profitable. They must become more efficient, responsive, and innovative to keep up with fintechs and stay competitive with a generation of customers expecting always-on, always-available consumer-like banking experiences. Recently, my company, Bain & Company, surveyed retail banks.

These are the 3 pillars behind the 4 key technology investments that can catalyse retail banking today – and in so doing, provide the foundation to build for digital agility well into the future. This piece considers the role of Artificial Intelligence and Machine Learning, Cyber Security, 5G and Edge Computing (MEC) and Safety Technology. And the integrative array of benefits afforded is vast, including real-time personalised consumer insights, 360 degree data visibility, embedded zero trust security, enhanced organisational and network efficiency, and enhanced safety. As a result, this builds consumer (and employee) trust, confidence, experience and loyalty. But what has sparked the need for transformation?

KB Kookmin Bank's AI Banker explains financial information on a monitor at the bank's headquarters in Yeouido, western Seoul, Wednesday. An image of a neatly dressed man welcomes visitors and answers questions on finance services on a monitor at KB Kookmin Bank in Yeouido, western Seoul. The male character, powered by artificial intelligence and modelled on TV personality Kim Hyun-wook, explains the difference between a debit and a credit card in a tone and manner identical to a real human staffer. He is a prototype of the AI bankers set to work alongside human bank staff in the near future. KB plans to test the AI banker service at selected branches starting this fall.

The increasingly rapid movement of technology out of back offices and into the hands of most of the world's population has profound effects. Even though the pandemic is widely credited with accelerating digital uptake, the full progression is really just beginning to shift from linear to exponential. As bank technology consultant Shanker Ramamurthy likes to point out, most of the world's population now walks around with "trillion-dollar" computers in their pockets. Ramamurthy is Global Managing Partner, Banking for IBM's Global Business Services group, the giant tech company's banking and consulting practice. Adding to that, IBM itself has been humbled by the same forces of digital transformation impacting the businesses it serves.

Almost all traditional banks and credit unions have been hampered by legacy technology that has made it difficult for them to compete with new tech-driven competitors. But options are now available -- and being used, in a few cases -- that free up institutions to compete in a far more agile, consumer-focused manner. The change could be liberating -- but only if banks and credit unions embrace it and make the necessary staff and cultural adjustments to take advantage of more modern technology platforms. Other than the largest financial institutions, to date very few banks and credit unions have deployed advanced technologies such as artificial intelligence, according to Cornerstone Advisors research. Although the numbers are beginning to move, particularly among credit unions, modernized core platform technology now available should speed adoption.

Artificial intelligence, or AI, has undoubtedly been the 2019 buzzword in financial services. While not new – the term "artificial intelligence" was coined in 1956 – AI is seemingly becoming the future of everything. The hype around its potential is certainly justified economically. According to a recent report by Autonomous Next, the cost savings achieved through AI applications across financial services – including banking, investment management and insurance – are expected to reach $1 trillion by 2023; $447 billion of which would be realised in the banking sector alone. Currently, one of the aspects of AI most applicable to banking is machine learning.

Artificial intelligence and machine learning promise nothing short of a customer experience transformation in retail banking -- but the best ideas for their application could fail if projects are not built on firm foundations of clean, accurate and complete data around customers and their behaviors and financial needs. The focus on customer experience among today's retail banks and credit unions should hardly be surprising. With financial services becoming even more commoditized, institutions increasingly must battle for consumers' attention and wallet share against disruptive new market entrants as well as their traditional competitors. More than ever, financial institutions need to find some way to differentiate themselves. In customer experience terms, AI and machine learning can help marketers in retail banking to predict client needs and deepen relationships.

Artificial intelligence and machine learning promise nothing short of a customer experience transformation in retail banking -- but the best ideas for their application could fail if projects are not built on firm foundations of clean, accurate and complete data around customers and their behaviors and financial needs. The focus on customer experience among today's retail banks and credit unions should hardly be surprising. With financial services becoming even more commoditized, institutions increasingly must battle for consumers' attention and wallet share against disruptive new market entrants as well as their traditional competitors. More than ever, financial institutions need to find some way to differentiate themselves. In customer experience terms, AI and machine learning can help marketers in retail banking to predict client needs and deepen relationships.

In January-March 2019 The Economist Intelligence Unit, on behalf of Temenos, surveyed 405 global banking executives on the changes they see taking place in their industry to 2020 and 2025, their organisational response, and the longer-term impact on their strategic development. This, the sixth iteration of the retail banking survey, focuses on how these retail banks are incorporating and advancing technology delivery for their current and future customers. The survey is part of a global research programme on retail banking, which includes in-depth interviews with retail banks, fintechs and regulators from North America, Europe, Africa and the Middle East, Asia-Pacific, and Latin America. The survey respondents were geographically diverse: 25% were drawn from Europe, 25% from Asia-Pacific, 18% from North America, 16% from Africa and the Middle East, and 16% from Latin America. Respondents came from a variety of job functions: marketing and sales (18%), IT (15%), and customer service and finance each accounted for about one in ten respondents (9% and 10% respectively).