Steve Monaghan, General Partner at FinMirai, a Tokyo-based venture studio, and previously the Chief Innovation Officer at DBS, recently voted the world’s best bank, spoke at FINSUM on the panel discussing “The Future of Banking”. We have captured his key points.
The future of banking will be an algorithm on a central bank server. Everything else between now and then is simply the journey of transformation. Banking is moving from being a reconciled business to being a real time business. And soon it will become a predictive business. Banking will move from the age of facilitation to the age of prediction and optimization.
And when we do that, the value proposition of banking changes entirely. So from a bank transformation perspective, when you look at this, banks are mathematical businesses. As a former CIA intelligence officer, who was a double MIT PhD, said to me once: “Don’t send in a man to do a machines’ work.” The way that we look at mathematics today in banking is actually often based on convention rather than pure mathematics. So when we start to utilize technology to better manage that mathematics, we can start moving banking on to real technology cost curves, which means that we are able to give customers far better convenience, far less bureaucracy and far greater accuracy.
As an example, nobody would lend money to their employer so that they could get paid later on, right? However, this is how we manage finance today. Most people have loans, and in fact, Japan has been a pioneer on capping the consumer finance rates. Most people have debt, mortgages, credit cards and consumer finance loans, and yet we often do not get paid for a month. During that time, we have a real cost of funding. In a real time world, this makes no sense. So were banking is heading is to be able to actually optimize cash both for consumers and for corporations. And this is not a role that banking does well today.
The CEO of a particular bank once was quite adamant that there was no way that banks would become what he called “dumb pipes”. Last year, however, that was exactly how he was quoted in the press, saying that the banks are at the risk of becoming dumb pipes and no longer actually creating enormous value for customers.
Doing that transformation and rethinking how money is used and looking at from the customer back into into the financial institution, that transformation has enabled the bank to double its net income on digital customers versus traditional customers. So everything in technology is built on tech curves — better, faster, cheaper every year. While banks have an enormous amount of data, they do not do anything with that data. And that’s almost a tragedy, because the tech companies are creating data at a far greater rate than the than the financial institutions. That data and insight into customer behaviors gives them an ability to react in ways that banks cannot and create value propositions far better than the financial institutions can.
So the opportunity for financial institutions now is to start utilizing that data while it is still valuable, because data has a half life. That means that every year it gets outdated. You might have 100 years’ worth of historical data, but it is going to become irrelevant in the next two years if you do not use it. So that advantage that banks have is disappearing fast. If you put that data to work, because banks understand core risk in ways that the technology companies do not, they are able to use that data for two things. One is to better manage risk and the second is to empower customers with better information and better decisions around financial services. This is the most powerful formula available to the banks today.
There are two major implications that are driving this change. The first is behavioral change. It used to be that the we would serve the banks in terms of creating productivity for the bank. So if you look at an old mortgage form, you would ask for “Mr. Mrs. or Miss.” And the second question would be “Are you male and female.” The reason that existed was to make sure that you could actually optimize the bank’s processes for data entry. That has driven organizational productivity ever since Henry Ford.
Everything about today is about consumer experience and increasing consumer productivity. That is a fundamental shift that many banks have not realized. So when we start redesigning banks around the customer it becomes a very different outcome.
The second major influence is the rise of technology. Processing power doubles every 18 months to two years for the same cost, while human productivity increases at about two to three percent during that period of time. That means you can do more with less every year on a tech curve. So the exponential tech curve is actually the same as a compound interest formula in banking. So these are actually aligned.
What we have done as humans, because we cannot scale in the way that technology can scale, we create all of these divisions, complexity and silos inside of organizations. So in one institution I worked at, some of our best customers had up to 40 security tokens. The purpose of those security tokens with twofold. One was to identify customers’ right to transact. The second was security. Now, from a security standpoint, the only way you could remember 40 different passwords was that most customers were putting them in unsecured Excel spreadsheets on their PC so that defeats the security purpose. In terms of the right to transact, it implied that the customer either had 40 different personalities or entities, or it was the bank with schizophrenia. As it turned out, it was the bank.
We have always organized around productivity inside banks. That has to change with processing power doubling every 18 months, and even more so when we get to quantum computing. At the moment, the differential is 500 million times faster for quantum. Once this starts moving into the mainstream, it will transform how we look at money and risk. Both are at the very core of banking. And this is why banking has to change.
At DBS, we were the first bank globally to put machine learning into core banking. When we first presented to the Board that we were going to look at machine learning, they said “No, that is only done in medical.” Then when I moved from banking to the world’s second largest life insurance company, and proposed to use machine learning, they said “No, that is only done in banking.”
For me, the only responsible answer is “no” if you do not understand the technology and you do not understand the capabilities. So I think that the model for adoption inside financial institutions has to move on from the traditional way where you used to buy a technology, tried to implement it and then your learning would be that it failed. We have to flip that model into a sequence of learning, venturing, capital. We actually need to understand technologies at a board level, and at the ExCo level and at the operational levels. Then we can actually start understanding how to best use technology to work within our institutions. We need to work cross functionally, across silos, because doing it in one place actually does not make any sense if there are other parts of the process that are still manual.
Inside the banking sector, we need to get back to very fundamental principles, which is how most new technology is designed. And to do that, we need to understand some pretty basic physics. There are Newton’s three laws of physics.
The first is inertia. It says that institutions will continue on their current path unless you apply an external force. The second is that all change will be opposed, which means that having resistance is a natural part of everything we do in the physical world. It is also a natural part of what happens in banking. Resistance is often good because it creates debate, and then enables you to make better decisions. The third is that force equals mass times acceleration. Mega banks have a huge mass, and we are asking them to accelerate. So you are either going to have to apply a huge force, or you are going to have to reduce mass. Most banks are coming to the conclusion that they set up a separate digital bank.
I think it is inevitable that Japan will follow the same route that Singapore and Hong Kong have taken before and look at digital banking licenses. That is to look at how you actually change mass to enable acceleration, because that acceleration point drives consumer adoption, which in turn drives far better economics into banking, and that is better for the economy overall.
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