Five Insights into Artificial Intelligence for Southeast Asia's Financial Services

The rise of artificial intelligence (AI) is the great story of our time, thanks to the ever-falling cost of computing and the increases in the availability and power of the machines. We are already surrounded by smart machines (from Alexa to Siri, Uber, and Netflix) that run on incredibly powerful and self-learning software platforms. This is just the beginning, as AI is transitioning from being our little daily helper to something much more powerful—not to mention disruptive—that is impacting every facet of our commercial lives. The banking and financial services sector is no exception. To understand how newly founded financial institutions are uniquely positioned to take advantage of AI, earlier this month we hosted an executive lunch briefing at the IDC Asian Financial Services Event in Singapore. Around 40 C-level executives participated in the discussion, in which we deliberated on the theme “Banking on AI.

It is safe to say that we had some eye-opening conversations. Below, I would like to share some key takeaways from our talks:

AI is here and now. It is crystal clear that AI is set to cause shockwaves in the banking and financial services industry, with almost every participant agreeing that it will fundamentally change the ways in which they interact with their customers and deliver products and services. In fact, our latest paper, The Work AHEAD in Banking and Financial Services, confirms that 58% of industry executives surveyed feel that the rise of the new machines will have a significant impact on their work, compared with the cross-industry average of 51%. There is no doubt that the future of work is the mirror image of the future of AI.

Chatbots are poised to take off. Southeast Asian banks are in the experimentation phase with Chatbots (many of their representatives mentioned doing POCs). Initial feedback from customers on this personalized ‘assistant’ has been very positive. Although Chatbots are still in their infancy, they will be ubiquitous within a few years and will have a game-changing impact on how customer support is conducted. For instance, a Singapore-based fintech startup, Active.ai, is in discussions with 20+ banks in the Asia Pacific region to deploy its Chatbot platform and expects at least 10 of these to go live on their platform this year.

Robo Advisors are another segment that is gaining attention from organizations when it comes to redefining wealth management space. Startups like Smartly are in a prime position to target the Southeast Asian millennial market with their robo-advisory platform. My view is that, while we are still in the early days of robo-advisory services in the region, banks must get on board this ship before it sets sail. They should not just be thinking about using robo-advice as just another channel to sell products, but rather as a medium for delivering a consistent experience to customers.

AI localization will be the biggest challenge (and opportunity). The Digital Head of a large Thailand-based bank shared a practical challenge with us. His bank had recently implemented the Chatbot platform with the aim of securing deeper customer engagement. The platform was meant to understand and respond to queries in the English language. When it went live, people started typing Thai language words (in English) to ask questions. The system got confused as it could not understand many of the words. As a result, they had to take the system down within 24 hours of going live. This highlights the need for organizations to consider local and unique challenges when developing their technological capabilities.

The back-office is a wildly overlooked opportunity. Our research shows that banking and financial services companies have yet to unlock the true value of their back offices. Industry executives expect their costs to decrease by an average of 1.8% by 2018 as a result of going digital. We believe that AI-led automation will accelerate the pace of modernization in middle- and back-office operations, thereby truly digitizing the fundamental operational blocks. For instance, Blue Prism is applying bots to risk, fraud, claims processing, and loan management in banking to save millions. In fact, automation will dictate organizations’ subsequent enterprise AI initiatives. Our latest book, What to Do When Machines Do Everything, provides guidance on how leaders should pick their automation targets across their organization.

Regulations, ethics, and security issues are top-line concerns. Security, ethics, and the lack of AI-related regulatory frameworks are the main concerns that could throw a spanner in the works when it comes to the rapid adoption of AI solutions. For example, the regulatory squeamishness around cross-border investment in robo-advisors is something that has yet to be resolved. In addition, what if a bank’s algorithm finds a pattern of loan defaulters for a certain racial community and, based on that, rejects their loan applications? Legal regulations denote that customers cannot be discriminated against based on race. Such an outcome could cause a bank to face a potential legal suit, leading to a loss of reputation and business. Other questions include: how will an algorithm identify and verify the user before providing information or allowing for complex actions such as money transfers? Will over-reliance on AI incur unknown risks? These and many other questions were debated by our executives.

There is no doubt that AI is already among us; it just hasn’t been evenly distributed yet. In the timeline of the AI revolution, we have just fired the opening shot. While all the concerns raised by executives are valid and call for further debate, frankly they will not halt the cross-field uptake of AI-led innovations. Do you remember when the “information highway” opened back in the early 1990s, it caused a wave of fear over the erosion of data privacy and control, intrusion, and hacking? Despite all the concerns about companies tracking our information online, few swore off the Internet entirely. Instead, smartphones and social media have become permanent fixtures in many of our lives. Once AI is assimilated, we will stop focusing on its perceived downside. We are in the ‘fear phase’ right now; the trick is to avoid getting fixated on it.

We are in an era of perpetual change, with AI at the rudder. To put it in simple terms, AI equates to real value. The implications for business decision-makers are almost stratospheric in proportions, and their strategies and investments should reflect this. It’s time to move beyond trifling experiments and take a long hard look at AI and what it means to your business. Process by process, throughout your entire value chain, you should identify ways of applying AI to change how work is done and how customers engage with your business. It’s not an either/or choice, as the impact of AI on the industry could be even bigger than anticipated.