Transmorphosizing Banking Through Artificial Intelligence

Banking is re-inventing itself as it always has

“Help us build the kind of bank you want to use” – That’s what Monzo says to its customers. Monzo is a UK based banking app with no usage fees, no branches, no mortgages and zero charges for spending abroad. While few of the banks in the UK might have a similar offer, but where Monzo has gained grounds is how it emotionally connects to its users. It auto-budgets your expenses, highlights where you are spending more, helps in finding the best deal e.g. it puts the money in the best savings accounts. They have formed a partnership with Google and Amazon to ensure real-time banking. For generations of users who spend a considerable amount of their time on their smartphones, it’s more than a conventional bank. Not surprising, they are termed as the new “wonder kid” in the banking industry and are aiming to have a billion-user base in next 5 years (ref: www.thegaurdian.com).

Seems like a fiction isn’t it. Not quite, because innovation has been the constant change in the Banking sector. History presents us numerous pieces of evidence in the form of

• Giovanni di Medici setting up first credit banking systems in Renaissance Europe where charging interests was considered as a sin
• The Dutch East India company trading in Tulips as stocks
• The bond markets fueling the Rothschild to become one of the richest and influential family
• The evolution of e-Wallets, UPIs, e-Money transfers giving a new definition to funds re-allocation

While the initial transitions required a couple centuries, the later took few decades. The rate at which better technologies and techniques are being made available, innovations are hitting us at a faster pace than previously imagined. The change is already here to be seen

• From physical branch-based model to mobile platforms
• Human interactions with virtual interface like chat-bots/virtual assistants
• Single player bank to multiple players who are traditionally not banks e.g. blockchain
• Inclusion of social risks along with traditional-risk analysis
• Mass market products to hyper-personalized products in real time

With Fintech startups gaining greater prominence and technology behemoths such as Facebook, Amazon possessing in-direct challenges to the traditional banking systems, competition in this sector is going to get more serious. In the Indian context, with non-traditional players like PayTM and Reliance making in-roads, the baking landscape might undergo a complete transformation.

Why is it happening now and what changed?

Two key factors – Creation and Consumption. While “Creation” is being driven by mining better insights through “data democratization” enabled on Big Data platforms, the “Consumption” has increased through relevant and accurate outcomes on these data catalyzed through “Machine Learning and more recently Artificial Intelligence”.

Artificial Intelligence(AI) has accelerated the rate of innovations in the last couple of years like “fire” in human evolution. Its ability to mimic human brain has led to identifying patterns and insights which were historically impossible or took a long time to manifest. e.g. while matching an image it tries to think like a human, using processes like Convolution Neural Networks, unlike some pre-defined algorithms which were tediously trained to function within some mathematical boundaries. AI is extending traditional Analytics to look beyond just numbers and statistics. It is revolutionizing the concept of “sensing” than “predicting”. These technologies are not new. While AI existed since 1950, the adoption has been high in recent times due to the availability of huge computing power, big data and reduced cost of implementation.

AI has already been adopted across several use cases like:

• Identifying Frauds with better accuracies
• Cross Selling and Up Selling using Chatbots/Virtual Assistance
• AI-assisted portfolio management
• IoT to better manage marketing across multi-customer touch points
• Process automation like Contract Optimization

But are these actions sufficient for survival?

Unfortunately, history has been etched with battles between unconventional domains. Instances like the downfall of Kodak when they delayed the adoption of digital cameras or Airlines which has been impacted hugely by “video conferencing” technologies, or Amazon kindle impacting publication houses. Innovation is essential and at a faster pace. The marketplace has seen the entry of unconventional players like:

• Reliance Jio: They already have the huge customer base over 120 M and this customer reach may increase exponential possessing threat to conventional bankers
• PayTM: It has expanded from a wallet to marketplace with a customer base of 200 M. With humongous gamut of offers in their kitty and a favorable customer perception, they have already started putting a dent in the online transactions & payment market
• In global markets: Jawbone and Amex have developed fitness + payment tracker “UP4”, thus helping payment channels as a natural extension of human everyday life or Westpac coming up with Geo-location specific marketing
• P2P lenders and their alarming growth rate of 300% in the last couple of years

Banking needs to leapfrog from the traditional way of doing things to new ways of thinking.

Can Banking be done differently to “thrive than just survive”?

With AI getting more “Context-Aware” and frameworks like Ubiquitous Computing gaining prominence, “Cyber-Physical” systems will become a reality or has become one as discussed in the “UP4” examples. Banking cannot just survive on innovation/automation alone, it needs to “Transform”. Bankers need fiction writers, the futurist who can dream of future. All we can say is there needs to be a “Trans-Morphosis”, from natural genetic change to a non-predefined transition.

If we re-visualize the opportunities through the prism of “Trans-Morphosis” few of those things can be done differently:

• Stopping a fraud before it happens- Like Manufacturing can we develop on the lines of “Preventive Maintenance” to sense trends before the “Boiler” fails
• Incentivizing customers for having a high credit score – Like Insurance sector, where better drivers are awarded “No Claim” bonuses
• Transforming Virtual Assistants to be Virtual Mentors – Help customers, not just with the best offers but suggestions to fulfill their dreams e.g. help to maximize savings for the down payment of a car by liquidating portion of existing saving portfolios like SIP, Mutual funds etc. seamlessly

These are just a few possibilities. Just think of additional opportunities like

• Shared Risk Platform across multi-partners or other banks – like blockchain, where risks are shared among multiple stakeholders. A recent defaulter with good credit history applies for a loan. His current requirement can be funded by multiple banking partners each sharing a portion of the risk. The risk value, loan amount and lending time/rates can be evaluated through AI to mitigate risk and help customers with better experience while ensuring he is still the part of the banking system
• Understand customer needs in real time based on what preferences influenced by one’s social setting e.g. what others who can influence him/her are spending on. Our decisions may be correlated by some facts but we humans may not behave rationally. So rather than predicting, since the possibilities through AI

What this decade is seeing is data-based decision making moving from being a decision aid to being the decision engine to almost being the decision maker.

To conclude “Data is the new nuclear fuel and AI is the reactor”. If controlled and curated we can fulfill numerous next-gen possibilities.