Today's blog post is a Q&A session with top fintech influencer and founder of Unconventional Ventures, Theodora Lau. Named one of 44 "2017 Innovators to Watch" by Bank Innovation, ranked No. 2 Top FinTech Influencers 2018 by Onalytica, and named to the list of LinkedIn Top Voices 2017 for Economy and Finance, she's a powerful voice in the industry.
If you probe into the rapid adoption of artificial intelligence (AI) initiatives in the enterprise, it quickly becomes clear what’s behind it: big data. In a 2018 NewVantage Partners survey of Fortune 1000 executives, 76.5 percent cite the greater proliferation and availability of data is making AI possible.
As Randy Bean in an MITSloan Management Review article puts it, “For the first time, large corporations report that they have direct access to meaningful volumes and sources of data that can feed AI algorithms to detect patterns and understand behaviors….these companies combine big data, AI algorithms, and computing power to produce a range of business benefits from real-time consumer credit approval to new product offers.”
To be able to process all that data, such as financial data, at speed and scale, enterprises need infrastructure to support it. Infrastructure specifically designed for financial and big data applications, with hardware and software that has been co-engineered to work optimally together, can offer better performance and faster analytics. It’s definitely helping deliver a better customer experience—and that’s especially true in the financial services industry.
We asked fintech influencer Theodora Lau to talk about the major innovations taking place in the traditionally conservative world of financial services.
Traditional financial institutions and fintechs have discovered that, by partnering, they can take advantage of each other’s strengths to develop innovative, revenue-generating offerings. PwC’s Global FinTech Report 2017 found that 82 percent of mainstream financial institutions expect to increase their fintech partnerships in the next three to five years.
Theo, how are fintech startups disrupting the industry, and how are the traditional financial services companies responding to that?
If you’d asked that question a few years ago, most people would have said banks are in trouble and need to defend against fintechs. But, starting sometime around 2017, the industry began to turn around and become more willing to collaborate. It makes sense because the services fintech startups are typically more focused on specific use cases: they hone in on those and do it really well. They have really good ideas and they tend to be very customer experience-driven, though they lack the scale compared to incumbent banks. And, as much as we talk about how bank infrastructure is aging, banks still have a large customer base and can scale.
Traditional financial services companies have existing customers and brand recognition; whereas, fintech startups are typically starting from scratch. At the end of the day, it’s money that we're talking about, and money is very personal and emotional. How much will a consumer actually go out and trust a company that has no history? While a startup may have the most beautiful customer experience, will I trust it enough to hand over my money? I see the two of them [traditional banks and fintechs] working together as the best outcome from a consumer perspective as well as for their own survival.
Is it true that new technology is making more collaboration possible as well?
Yes, exactly—through APIs and open banking. I don't believe that any single bank can offer everything that the consumer wants, and I don’t think it’s in their best interest to try to be everything for everybody. For instance, ING, a large bank based in Amsterdam, has multiple operating units in different countries. Its German operations formed a partnership with a startup called Scalable Capital, which is an online wealth manager and robo-advisor, to offer a fully digital solution for its customers in Germany. This is a brilliant example of a partnership where the bank extends its product offerings by leveraging the solutions and capabilities that someone else has.
What AI technology is changing the industry?
Open banking is the big game changer. One example is Starling Bank in the UK, which does a really good job being an online marketplace. Using APIs, it acts as a hub through which consumers can get access to different things that traditional banks don’t offer, including spending insights, location-based intelligence, and links to retailers’ loyalty programs.
Another example is Tencent and Alibaba in China and the big ecosystem that they’ve built. Between the two companies, they own over 90 percent of all of the mobile payments in China. They're not banks, but they’re technology companies that put the consumer in the center of everything they do. They view payments and financial services not as an end in itself, but as a tool to further enhance their offerings.
We can't forget about voice banking. We see more banks trying to get into that space—though we are not quite there yet. Voice is very intuitive. It’s just easier to talk than it is to remember how to navigate a menu, which is a challenge in online/mobile banking. Imagine if you can actually say, “Hey, pay my bills,” instead of having to remember where you need to go on the menu tree.
Let's go deeper into how AI has changed the customer experience. How has it affected personalization and the omnichannel experience?
When we’re talking about AI in customer experience, it’s important to remember that banks are not really competing with other banks anymore. When consumers do their “banking,” they're comparing their experience to that which they get with all the other online businesses. How does banking compare to me getting something from an ecommerce site? Is it quick and easy? Is it available when I want it and where I want it?
The threat to banks isn’t so much fintech companies as the big tech companies like Apple, Amazon, Alibaba, and Tencent. They are the ones banks should be worried about. Look how many customers they have. Look at the products and services they offer, even payments. It’s because of the vast amount of customer information they collect, as well as data analytics and AI, that big tech companies can provide data insights into user behavior and spending habits, allowing them to anticipate your needs and offer contextual, personalized recommendations. That’s how payments are supposed to work as well. Consumers shouldn't have to think, “I need to pay something.” They have a specific task they want to do, and banking services are just a means to an end. From a consumer perspective, hopefully, AI can make banking ambient and transparent in our increasingly connected world.
We've been talking a lot about retail banking, but I presume AI is also making similar changes to other areas of financial services.
Marketing is a good example. A big thing is figuring out how to entice people to open an email because everything is digital now. HSBC ran a trial using AI to figure out whether its members would prefer rewards for travel or merchandise versus rewards in the form of gift cards or cash. It sent emails to 75,000 credit card members using recommendations that were generated by AI while a control group received emails with rewards from a random category. As it turned out, the emails using AI-generated recommendations had a 40% higher open rate. That’s a fascinating business use case because you don't want to waste your marketing dollars if people are not going to open your emails.
Do traditional financial service companies have the infrastructure in place to fully leverage AI or even to partner with fintechs? How is AI changing processes within their firms’ infrastructure?
Financial institutions have a lot of data, but when it comes to being able to leverage AI, which is very heavily data-dependent, the challenge is being able to access that data. A lot of times, all of these systems are very siloed. So while a bank may have a ton of data about a customer, how well can it actually pull all of the data together to be able to generate insights that are useful and can be leveraged?
The other challenge: If you can get the data together in a meaningful way, are they explainable? If you are using AI to make decisions, such as in lending, are you going to be able to explain what the AI is recommending, and how someone gets qualified for a loan, for example? That's something you need to do.
What’s holding the banks back in terms of modernizing their technology?
It’s a couple of things. You need to look at the make-up of the people, because it has to start from the top.
At the upper layer, finance people have been doing the same thing for many years. Until you have leaders, including senior executives and board members, that are passionate about and actually understand technology, it's hard to transform. It goes beyond just having a mobile app —true digital transformation and modernization involve change in culture, mindsets, and processes.
Of course, it’s also a heavily regulated industry. If you're going to be upgrading something, and you already have customers and money and transactions there, you need to be very careful about what you're doing. Privacy and security of data is of paramount importance.
It’s also a very expensive and lengthy process to upgrade core systems, so money is definitely one part of why financial institutions aren’t modernizing their infrastructure. Some of my friends would say that some banks are actually not scared enough yet. Look at their earnings—they're still making good money. So if they’re not feeling the pain as much yet, then how urgent is it for them to actually do something drastic? Yet many mid-size financial companies don’t have large budgets, but still need to modernize their technology solutions to manage the explosion of data.
There are banks that are certainly more at the forefront of technology, and they’re betting big on technology. For example, JPMorgan Chase’s technology budget is over $10 billion in 2018, with most of it going toward enhancement of mobile and web-based services.
Where do you see AI taking financial services in the future?
What I would like to see in the future in the US is what we see right now in China in regard to their platforms. In India, China, and Africa, the mobile adoption is so much higher compared to the US where the mode of doing things is so different. We shouldn't be looking at banking as an entity per se. Consumers are looking for banking services. That’s what we will be evolving to in the future, and we'll need AI to be the brain and the engine to offer a deeper, richer, more personalized experience.
Authentication is another interesting area. No one wants to remember passwords or carry those little tokens. That's not customer-friendly at all. So biometrics and voice authentication will be very fascinating. At least that’s true of voice banking, which is still in the exploratory stage. Checking balances is not really exciting, but, in the future, AI will let the bank know I got a work bonus and will automatically ask whether I’d like to put aside 10 percent of that into savings. Things like that will enable financial wellness and more value overall for customers. That’s where I think AI can help in the future—and that’s how we can make banking better.
And behind this future will be the enormous quantities of data that make this customer knowledge possible, and the ability to collect and analyze the data in real time, built on the right infrastructure.
Learn more about how machine learning and AI can add substantial value to the financial services ecosystem.