Let us take a step back.
After many years of false promises and mis-starts, Artificial Intelligence (AI) has finally crossed that rubicon of maximum hype in recent years, and has now become a fait accompli.
In plain terms, AI is here to stay.
The ubiquity of computing power in the past two decades has unleashed a proliferation of data at a scale previously unimaginable even in the largest enterprises of the world. Today organizations like Google, Facebook, Amazon et al. generate and consume data at planetary scales, or in the case of countries like China or India, at national scales that dwarf any other nation on the planet.
The only way to process this volume of data and extract any meaningful insight is through Artificial Intelligence technologies. This created a natural opening for increased innovation in various areas of AI, most specifically, the field of Machine Learning. This increased innovation, coupled with the increased volumes of data, and democratization of computing power, unleashed the perfect storm for AI to claim its rightful place in the modern world.
Historically, the financial sector has always been at the forefront of change in human endeavors. Hence, it was natural for the financial sector too, to embrace this new innovation whose time had come. However, like most large modern corporations, embracing change was a leviathan task. They have been slow and lumbering in their evolution to reinvent themselves using the power of AI.
So, what is the power of AI for the finance sector? According to various articles, here are the main AI initiatives being pursued in various segments of the financial sector.
- Trading: Algorithmic Market Trading
- Investment: Robotic Investment Advisory
- Banking: Process Improvement, Fraud Detection & Risk Mitigation, Personalized Banking
- Lending: AI driven Credit Scores
The above list can be broken up into three categories.
The first two, viz. Algorithmic Market Trading and Robotic Investment Advisory are both still aspirational in that, while there are numerous solutions in the market, the results can be ambiguous, and until there is sufficient long term analysis of its benefit, we are still in early days. This is not to say that they are not beneficial or that they will never be. In fact, in time, each of these will perfect themselves to be unimpeachably mainstream. But that is not today, yet.
The next one, viz. Banking has both a direct ‘customer benefit’ aspect, like in Personalized Banking, and a more drier and harder, but no less important, ‘internal improvement’ aspect. It is the second aspect that banks struggle with most due to their lack of speed or sometimes complete inability to manage change effectively. The true potential of Personalized Banking is achieved most when a bank reinvents its customer experience by truly knowing its customers using the large volumes of data in hand. Unfortunately, there is a tendency to chase more gimmicky solutions like chatbot based banking. Once again, like the first category, these will eventually get there. But today, they are a still at the level of a novelty.
The third category, viz. Lending is where AI can truly electrify the sector. Lending is one of the oldest profession, and the right way to lend is not just to have a robust collection mechanism. The right way to lend is to know “magically” who to lend to i.e. who can and will return the money, and who not to lend to. This “magic” is what AI based credit scores have the potential to achieve. We, at CASHe, have taken an initial necessary step in this direction by audaciously lending to salaried millennials solely on our own AI based credit score, that we call SLQ or The Social Loan Quotient.
Hence, just like electricity was once a new technology that the world looked at with hope and expectations, AI today is truly the new electricity for our future world.
(The author is Chief Technology Evangelist at CASHe – India’s most preferred digital lending company for young salaried millennials. CASHe provides immediate short-term personal loans to young professionals based on their social profile, merit and earning potential using its proprietary algorithm-based machine learning platform.)