It's time for the financial sector to embrace an AI-led future

The exponential improvement in the price performance of the digital and machine learning infrastructure is a key driver of adoption (Image: Shutterstock (For illustrative purposes only)

The age of uncertainty and technological disruption is upon us. Like other sectors, the financial services industry too is struggling to deal with its impact. Geopolitical uncertainties with regard to North Korea, Brexit, the increase in protectionism, along with operational challenges that include increasing customer demands, new expectations from digital, the rise of the millennial consumer are contributing to the sense of unease. Fortunately, there is a silver lining. Artificial Intelligence (AI) has the potential to have a positive revenue and cost side impact for banks —from developing intelligent digital assistants, providing seamless services and building data models, acting on lending decisions and enhancing security with advanced recognition techniques.

The exponential improvement in the price performance of the digital and machine learning infrastructure is a key driver of adoption. A recently conducted study on the impact of AI and the current levels of AI maturity in companies highlighted several interesting facts. Titled 'Amplifying Human Potential: Towards Purposeful Artificial Intelligence', the report states that AI adoption is fast increasing, with 56 percent of financial enterprises reporting that they were using AI in the past one to three years. By 2020, enterprises can expect to see AI contributing to a 39 percent average increase in revenue along with a 37 percent average cut in operating costs. For financial services firms, it was seen that they invested much more in AI than other enterprises, with the actual figures amounting to $14.6 million versus an average $6.7 million for all respondents.

However, in terms of AI maturity, the financial services sector ranked third from the bottom. The study pointed to the hesitancy in sharing customer’s personal data and the cost of technology as the factors that were hindering AI maturity. This is a matter of concern considering the overall positive outlook AI has from the entire industry. And while it is possible for service providers to supply cost-effective transformation solutions for banks, which would include modernization of phased mainframes, meaningful solutions for issues pertaining to privacy protection as well as meeting the needs of cyber security.

With the AI wave, opportunities will open up for talented workers in the banking sector to engage their skills in different areas, especially with regard to innovation and creativity. Certain roles such as risk management, inclusive growth, creation of new products and services and differentiating experiences, will always require human skills. Organisations will have to pitch in by investing in training workers in new paradigms and deploying employees displaced by AI to fill such newly created roles.

In the banking sector, the onus is on customer service—customers being the fulcrum of any bank —and AI can be the much needed solution to be a fore runner in this area. For instance, facial recognition technology software can be a faster and far more accurate tool for authenticating users—10 to 15 times more accurate than human beings. Similarly, AI technology can respond at a greater speed to emails from customers than service agents. It also enhances customer delight through better accuracy, swiftness and even a certain degree of intimacy.

Several banks are currently deploying AI to their advantage. For instance, Goldman Sachs’ AI-based financial research platform, Kensho, can be questioned using natural language. And, Santander in the United Kingdom deploys AI to offer voice activated payments. Sweden’s Swedbank has its Nina Web assistant, which achieves a 78 percent first contact resolution; whereas RBS uses Luvo, an AI customer service assistance system.

Robots in customer service are already in vogue in Japan, where a shrinking workforce is driving the need to explore newer avenues. Pepper, used by Mizuho Financial Group Inc, interacts with humans by providing customer information and by playing games and multimedia. Nao, a humanoid robot, deployed by the Mitsubishi UFJ Financial Group can greet customers and answer enquires. Customers, who are bored with the routine banking chores, enjoy the interaction with such newer forms of artificial intelligence.

Large commercial banks have several back-office processes that AI’s operating models are transforming. Operations such as reconciliation, consolidation and credit risk management, can be completed with robotic process automation (RPA), which along with machine learning can be fully automated. Banking functions that are central to operations such as the quarterly closing and reporting of earnings can be accomplished in real time with AI, allowing for greater accuracy and quicker adjustments.

A case in point is the Machine Learning program called COIN (Contract Intelligence) used by JPMorgan Chase & Co, one of the biggest banks in the United States. The AI program takes just a few seconds to review commercial loan agreements as compared to the 360,000 hours each year that a team of lawyers and loan officers would take to complete.

Banks seeking to use AI have yet another incentive of providing millennials and the upcoming Gen Z with easily accessibly services. Digitally native millennials and Gen Z, who will soon form the majority percentage of the banking sector’s customers, will demand services that can match the advanced technological levels they are familiar with, and AI, with its advanced capabilities, is the right choice. Given its extensive potential and immense possibilities, AI is without doubt the next wave of technology that will revolutionize the financial sector.