In the short time span of being widely accepted, Artificial Intelligence has managed to leave its footprint in almost all the industry verticals. From self-driving cars to personalized recommendations, be it in movies, songs, or even better, in fashion, the scope of AI knows no bounds. Seldom has the world seen such fast-paced evolution of a particular piece of technology. And to think, this prowess was obscured for years due to reasons like lack of funds and vested interests.
The banking industry has undergone massive changes over the years. Ledgers and cash transactions involving physical currency were carried out in bank premises itself in the initial stages of banking. In the modern banking system about 20% of all global transactions are cashless. How did you pay for the Uber you took to work today? Surely, a very small number of you would’ve paid by cash. With digital transactions being the newest thing, the young generation particularly is seldom seen withdrawing cash or only occasionally seen at the bank to report any kind of issues. This is because, the banks have also stepped up their game. They are constantly striving to provide glitch-free, reliable and hassle-free services to their customers. Well they’re trying to mostly. But if you can quickly calculate the number of trips you’ve taken to your bank during last one year and compare to what you used to take a decade ago, it will reveal the truth. From upgrading their servers, improving user experiences, designing schemes and plans of investments to save taxes, and above all, the introduction of net and mobile banking, the relationship of the customers with their banks has improved by leaps and bounds over the years.
AI works well with massive amounts of data. As a famous saying goes, “A machine learning algorithm is only as good as the data used to train it.” The more data a company has, the merrier. Banks tend to have a lot of data on their customers. A bank is capable of estimating the net worth of an individual by analyzing their spending patterns, inclination to pay loans, bills, rent etc. None of the data they hold is synthetic, which makes up for excellent use cases i.e. study of individuals by only monitoring their transaction histories. Not only individuals, a bank is capable of summarizing a company’s equity by analyzing its assets, capital and returns over investment. For improvement of their savings schemes and policies, they require little or no market survey which puts them at an advantage. Only thing which is of any worth to them is the study of data.
An industry big-gun JP Morgan Chase is investing billions of dollars on COiN (Contract Intelligence) to review commercial agreements. Commercial agreements contain legal terms and are often discussed between lawyers. Using this platform, the firm expects to extract only the important points and clauses mutually agreed upon by both parties and point out any discrepancy if present. Otherwise, reading and understanding a single document of this sort manually takes hours. Another hot-shot Wells Fargo has set up an AI team to increase connectivity for the company’s payments efforts, accelerate opportunities with artificial intelligence, in order to strengthen its digital offerings and provide more personalized customer service through its bankers and online. Similarly, Bank of America has invested in a live chatbot named Erica primarily for engaging with customers. It uses a mix of predictive analytics and cognitive messaging to answer queries and troubleshoot problems.
In Indian banking also, the scenario is changing fast. HDFC bank, one of the largest Indian banking corporation in the private sector, has developed IRA – an interactive humanoid who can guide you to navigate through its branch and provide answers to frequently asked questions by customers with the help of EVA – the virtual chat assistant. On the HDFC website also, the visitors are greeted by EVA. State Bank of India, the largest bank in India has also been shifting towards digitalization. They hosted a “Code for Bank” hackathon in the past year where young developers were encouraged to build futuristic solutions leveraging modern tools of AI and Blockchain.
A lot of research and study is also going on in the area of Risk analysis, Fraud detection and management, algorithmic trading, providing business insights etc. Machine Learning algorithms are proving to be efficient in risk analysis. Risk analysis forms an integral part of banking and it takes into account the previous records of an individual. Machine Learning is good in these types of tasks. It can analyze huge volumes of data, learns over time and is less prone to error.
Credit card frauds, identification of fraudulent transactions, security of lockers, cashless transactions are all coming under the canopy of AI. Today the agencies providing platforms for digital transactions are interacting with the data of the banks i.e. customers at real time. It is extremely necessary to ensure that there is no data leakage and the platform has all the measures of cybersecurity in place. While it is humanly impossible to monitor each transaction, AI is the key to ensure this. A lot of R&D is in progress to study the interdependence of AI and cybersecurity which has already shown a lot of progress but not so much as to earn unanimous trust.
Similarly algorithmic trading – an automated version of buying and selling shares by companies – works on a set of parameters and hence is dependent on bookkeeping records. It makes use of a number of other heuristics like time, market conditions, and funds at disposal. So machine learning comes in handy in these kinds of tasks.
It is being said that AI will wipe out quite a few jobs. The ones who are saying so are clearly missing out on the bigger picture. While it’s true that the routine jobs will be automated, a lot of other types of jobs type will be created that will require alternate skillsets. So it’s time to consider reskilling and upskilling in order to be ready for the sword that hangs upon us. AI is here to augment our intelligence rather than diminish it. So it is time now we embrace it with open arms and let it weave its magic on the world of banking and finance among other things.