The New AI Banking Economy
Despite being one of the oldest institutions known to man, banks have remained an ever-present and functional part of human society. This long-standing presence can be attributed to the adaptation of traditional banks to the latest technological advancements. Banks have continuously found a way to reinvent how they serve their customers as seen in the 1960s with the introduction of ATMs, in the 1970s with the adoption of electronic, card-based payments, and the 2000s with the widespread use of 24/7 online banking. More recently in the 2010s, the mobile-based “banking on the go” has further demonstrated how banks are tapping into the sophisticated technologies being developed. With the rest of the modern world now being shaped by Artificial Intelligence, traditional banking must rise to the occasion once more and show intuition to tap into the strong potential of AI. The adoption of AI to banking will serve as more than just fuel to boost productivity. AI is an industry disruptor whose capacity to redefine the banking sector will be seen in the coming years as unique value is unlocked for the businesses and customers that utilize it. As you read this, AI is equipping many financial institutions with the know-how to change how they work, how they build unique products and services, and how they redefine customer experiences. AI’s role in the banking sector today is both extensive (with growing involvement in several phases of the banking ecosystem) and intensive (with the possibility to make banks much “smarter”). AI stands as an important trend that will transform the banking industry in the future.
The projections around the adoption of AI within the banking industry estimate an annual incremental value of $1 trillion. The number of reports, discussions, and articles centered around AI and the financial services industry are growing in number and it’s easy to see why. Consider, for example, that the estimated potential cost savings for banks from AI applications are projected to be $447 billion by 2023. This figure is from a 2019 Autonomous NEXT report from Business Insider Intelligence which further breaks down this value to be $199B, $217B, and $31B across the front office, middle office, and back-office respectively.
According to an OpenText survey of financial services professionals, 80% of banks recognize the transformative potential of AI and machine learning. It also appears that strategies are being formulated and deployed by banks towards adopting AI. This is backed by the data from a UBS Evidence Lab report in which 75% of respondents at banks with at least $100 billion in assets state that they are already deploying AI strategies. Also, 46% of respondents at banks with less than $100 billion in assets report that they are implementing AI strategies. AI use cases in banking operations are already springing up and gaining solid footing. The most mature of these include the use of chatbots in the front office and anti-payment fraud in the middle office.
The capacity of AI to process data and extract insight from a large amount of data is well-documented. This ability, along with other features of AI, can be deployed in any of over 25 use cases in the banking industry to:
1. Personalize services to customers and employees thus increasing revenue
2. Improve efficiency and cut down on costs through more automation, smaller error rates, and greater resource utilization
3. Discover hidden and new opportunities
In a larger perspective, disruptive AI technologies significantly raise the capacity of a bank to accomplish the following four crucial goals:
1. Improved profits
2. Personalization at Scale
3. Unique omni-channel experiences
4. Fast innovation cycles
It’s a dog-eat-dog world and any bank that lags in transitioning to an AI-first operations policy will find itself out of the pack and struggling for relevance and customers in the new AI-powered world.