In the post-COVID era, financial institutions across the world are figuring out ways in which they can leverage Artificial Intelligence. The sector has been fortunate thanks to the regulatory onslaught post the 2008 economic crisis, as a result of which banks are well equipped to weather the COVID-19 storm as well as aid economic recovery. Care Ratings is one of the leading credit rating agencies in India.
In a conversation with W.Media, A Shiju Rawther, Chief Information Officer, Care Ratings outlined his views on usage of AI in the BFSI sector.
Shiju has had a steady career growth in reputed organization like IIFL Finance Limited and others. Shiju has been recognized as one of the Most Innovative CIO’s in India.
How is Artificial Intelligence being used in the BFSI sector ?
The BFSI industry has always seemed to be one of the most developed and willing to invest in new technologies. It’s no wonder that AI has quickly become one of the technical pillars on which the entire modern financial market is built.
Not everyone is aware that AI is not only leading analytical solution, but also a way to change the way customers interact with services provided by the financial industry. Let’s take a closer look at this extraordinary relationship, its impact on the way we use banks, and on issues such as fraud detection and compliance regulations.
Artificial Intelligence is used in many Fintech solutions. It’s a cure for the daily challenges faced by many businesses like customer experience personalization and loyalty building, to strictly technical financial features such as anomaly detection or fraud prevention.
AI has been talked about for some time now. Will there be more meaningful adoption now?
The beginnings of AI in the industry, however, were not so simple. The first attempts to improve the operation of banks using computers were made in the 1950s. The story started with the simplest and most obvious solutions: accountants wanted to use computers to make calculations much faster and more accurately than real people could.
However, it turned out that their use might not be so easy since the machines themselves were not as powerful as they are now. Despite this fact, Bayesian statistics, which is used in machine learning even today, was implemented to expand algorithms enabling processing actions such as stock market predictions, loan repayments or calculation of probabilities regarding auditing.
In the early 90s, AI and machine learning appeared on Wall Street along with the first hedge funds – but there was still no significant breakthrough. It appeared only with the increased availability of data, generally with the spread of the internet. Since then, there has been an extremely rapid evolution of operating systems, taking advantage of the increasing capabilities of machines.
Nowadays AI basically affects every area of a bank’s or financial services institution operations as well as the work of departments that we often forget about in the context of using technology in the financial sector, such as corporate core aspects, including even human resource team work.
What kind of work is going on in the same?
With plenty of post-recession anti-banking sentiment still lingering, it’s common to see fintech and traditional banks framed in oppositional terms. There’s some truth to that, especially with disruption-minded digital-only banks, but technological innovations have transformed banking of all stripes — and nowhere is that clearer than with AI.
AI has impacted every process of banking — front, middle and back. That means even if you know nothing about the way your financial institution uses, say, complex machine learning to fend off money launderers or sift through mountains of data for fraud-related anomalies, you’ve probably at least interacted with its customer service chatbot, which runs on AI.
Within AI, are there any particular areas of focus?
My sense is that innovation towards customer experience will be one of the key areas. Customers increasingly expect tailored products and services delivered to them in real time, in tune with their moods and behaviors. To do this, banks will need to fuse artificial intelligence (AI) and human judgement to turn the troves of customer data they possess into actionable insights that help customers improve their financial well-being.
As we enter a new decade, the banking sector faces a pivotal moment, with digitisation transforming business models and processes in new and greater ways. In coming days, BFSI segments must innovate and invest in advanced technologies to remain in the market. It is no longer a question of achieving a competitive advantage. Its table stakes.
In the future, the banks that survive and thrive will use these advanced technologies to make the transition from delivering financial services to enabling financial betterment. To this end, we see several priority areas on which banks should focus their efforts, to succeed in the next decade.
Banks will need to become more like partners to their clients, using AI and analytics to make helpful nudges and interventions to encourage healthy spending habits and make recommendations on how to reach life goals sooner. Adopting this approach will require banks to restructure services and products around the short and long-term impact of financial decisions, helping customers to make more purposeful investments and purchases.
