How Legacy Banks can Become First Movers in AI
Fintech is becoming increasingly well-capitalised and now has access to better tech capabilities
Banks in India have a rare window of opportunity to lead the charge in embracing Artificial Intelligence (AI) in order to create more value for their customers and shareholders. However, in order to do so successfully, they must pay closer attention to developing a holistic AI strategy.
AI is already transforming nearly all industries the world over. It will potentially contribute $15.7 trillion to the world economy by 2030, says PwC, adding that 45 per cent of total economic gains by 2030 will come from product enhancements, stimulating consumer demand. This is because AI will drive greater product variety, with increased personalisation, attractiveness and affordability over time.
Banking is no exception, and consultancy firm McKinsey has estimated that AI technologies could potentially deliver up to $1 trillion of additional value to global banks each year, corresponding to over 15 per cent of their annual revenues. Of this figure, a whopping $625 Billion will be generated by enhanced marketing and sales, while risk will generate $373 Billion.
Last year, a global survey on AI in Financial Services global was conducted by Cambridge Judge Business School and the World Economic Forum, co-sponsored by EY. It found that 85 per cent of all survey respondents currently use at least some form of AI. More crucially, 77 per cent respondents anticipated that within the next two years (by 2022), AI will possess high or very high overall importance to their businesses. By that time frame, nearly two-thirds (64 per cent) of respondents expect to be “mass adopters” of AI — using it for revenue generation, process automation, risk management, customer service and client acquisition — compared with just 16 per cent currently.
While comparable data on Indian banks is hard to come by, there is no doubt that several of them are actively working on various AI applications and projects. In many ways, they are also competing with fintech startups, and even Big Tech companies for AI dominance in banking.
Leveraging AI the Fintech Way
It is important to note here that fintech is increasingly well-capitalised and along with Big Tech have better tech capabilities, besides being far too nimble-footed than traditional banks. However, traditional banks also start with a big advantage at least over the fintech companies. The success of any modern AI initiative depends overwhelmingly on availability of high-quality data, and banks have been accumulating huge volumes of data about their customers and their transactions over several decades now.
Still, the big challenge for them is to find a way to consolidate this data and make it usable for relevant AI or analytics models. Banks must also heed the fact that AI presents to them a formidably huge number of use cases or applications, and these cut across opportunities for generating more revenues or for cutting costs. As per EY, both incumbent banks and fintech are aiming to leverage the technology to execute new business models, deliver new products and services, and improve and streamline existing processes.
For banks in India struggling with stressed assets, using AI for risk management, including fraud detection, is perhaps one of the critical drivers for adoption. The technology can be intelligently applied to detect and prevent money-laundering schemes or credit card fraud. Advanced AI models can detect and prevent future defaults. Further, it can be applied to de-bias the credit decisions (or credit underwriting) to improve both speed and accuracy.
In the United States of America, USAA is a Fortune 500 bank that is using AI to analyse how and where its customers used its apps, and typical behaviour that customers display when interacting with them. The bank analyses patterns in order to detect any potential anomalies. Through these fraud prevention methods, USAA is saving its customers on average around $100 million a year, besides being able to actively monitor fraud in real time.
Other high-value AI applications include hyper-personalising the online or in-app experience for each customer individually, with AI serving them with personalized financial advice or guidance or new product recommendations. Another big area of opportunity lies in enhancing the customer service experience, whether through reduced call centre waiting times, or by allowing automated transactions through voice recognition algorithms. Imagine your bank using AI-enabled real-time voice recognition to detect an irate or confused customer and directing her to a more experienced human representative!
Need for a Comprehensive AI Strategy
The real challenge then is to put together a comprehensive AI vision and strategy that identifies the most critical and impactful applications or use cases, and also assesses the current strengths and weaknesses of the bank in building those applications. As I mentioned earlier, availability of decades of customer and transactional data is a huge leg up for traditional banks. On the other hand, they will find challenges in extracting this data spread across multiple systems, consolidating it. Another big challenge is about building internal organization-wide consensus on pushing full speed ahead on the AI vision and strategy.
Just how seriously should banks pursue a first mover advantage in AI? McKinsey sounds the warning bells, stating that banks that fail to make AI central to their core strategy and operations will risk being overtaken by competition and deserted by their customers.
The flip side is even more compelling for banks; AI will help them improve profitability, retain customers and compete better in an ever-changing business environment. The time to get started is now.
The author is CEO and Co-Founder, Signzy
DISCLAIMER: Views expressed are the author's own, and Outlook Money does not necessarily subscribe to them. Outlook Money shall not be responsible for any damage caused to any person/organisation directly or indirectly.