15 Mar The Mobile India & AI-aided Banking Experience in 2019
Urban India has always led the mobile revolution in the country but rural India – the real Bharat – is now close behind. Since 2015, rural India constituting 40-50 percent of the user base has brought 100 million more people online. In 2013, smartphone penetration in India stood at 6.3 percent, which grew to 23.8 percent by the end of 2018 aided largely by the low mobile tariffs of market disruptor Reliance Jio.
An InMobi report projects that 60 percent of the country’s population would have smartphones with fast and reliable data connectivity by 2025. Latest technology offerings like big data, artificial intelligence (AI), internet of things (IoT) and blockchain will help further drive mobile usage amongst the Indian population. AI-based technologies like ‘vernacular voice bots’ are expected to break the literacy barrier and make non-English speaking people go mobile with utility services. This digital transformation is expected to revolutionalize the manner in which various industries work.
AI adoption in India is presently at an inflection point what with it being the fastest growing economy in the world with the second largest population, thus promising torrential growth. The government has outlined priority sectors of the economy in the National Strategy for Artificial Intelligence and has chosen a tri-pronged strategy – undertaking exploratory proof-of-concept AI projects in vital sectors, crafting a national policy for building a vibrant AI ecosystem and collaborating with experts and stakeholders.
India is riding high on the digitally ready wave with the government aggressively pursuing the Digital India program that includes a set of APIs that address identity, payment, and consent, collectively known as ‘India Stack’. The vision is to thrust presence-less, paper-less, cash-less and consent-based service delivery that can be leveraged by an ecosystem of businesses.
The AI strategy for India published by National Institute for Transforming India (NITI) Aayog is comprehensive and addresses the scale, challenges, needs and aspirations unique to India. Cloud infrastructure and rapid deployment of intelligent cloud services will play a key role in driving AI adoption in the country.
Amongst diverse industries in India, the banking and financial services sector is expected to benefit the most out of incorporating AI systems a few years from now. Analysts claim that AI will save the banking industry more than $1 trillion by 2030.
Banks want to personalize services to customers and improve customer satisfaction, and in that quest has thus become one of the first large scale adopters of AI. According to Accenture’s recent Accenture Banking Technology Vision 2018 report, 83 percent of Indian bankers believe that AI will work alongside humans in the next two years — a higher than the global average of 79 percent.
The basic applications of AI include minimising human error and creating accurate solutions for the customers; bringing in smarter chat-bots for customer service; personalising services for individuals; placing an AI robot for self-service at banks; increasing efficiency of back-office operations; lessening fraud and security risks and collating surveys and feedback to assist in financial decisions.
The State Bank of India, the largest bank in India, last year conducted “Code for Bank” hackathon to encourage developers to build solutions leveraging futuristic technologies such as AI and Blockchain into the banking sector. Private banks like HDFC Bank and ICICI Bank have already introduced chat-bots for customers’ service. Some have even gone ahead with placing robots for customers’ service. Last year, Canara Bank installed Mitra and Candi robots at some of its offices.
Banks are sitting on a treasure chest of customer data, which is a great advantage compared to some of today’s digital disruptors. As the financial services sector is turning to insight-driven sales strategies, Machine Learning (ML), a subset of AI, is a big help to improve effectiveness in sales. Predictive and prescriptive analytics could help identify purchasing patterns or forecast customer habits and behavior.
UBS research amongst 86 banks says AI could boost banks’ revenues by 3.4 percent and cut costs by 3.9 percent over the next three years. According to Tabb, of 200 global tier-I and tier-II banks, more than 83 percent have evaluated AI and machine learning and 67 percent have actively deployed them. A major driver for banks to focus more on AI is that it can unlock a potential value of about $200 billion in banking sales and marketing alone, according to McKinsey. In an example of using AI in analytics, a bank had commissioned an analytics solution firm to end the migration of high-value mortgage customers to rivals. The company compared the attributes of loyal customers with those that had churned and identified over 100 factors related to a customer, product and transactional data. The data was fed into a predictive modeling tool that uses neural networking techniques to predict churn behavior. The number of factors was reduced to around ten and the model was applied to all mortgage customers, ranking them in order of their likelihood to leave. Based on this ranking, the bank launched a targeted marketing campaign, which cut the churn percentage by nearly half.
Banks can also rely on third-party solutions to tap sales growth potential offered by ML technologies. Third-party insight-driven digital sales and engagement tools use AI and predictive analytics to show, for example, if a customer is planning to buy a house or needs a consumer credit. These tools collect, aggregate and analyze non-traditional data and other information, like geolocation, patterns, social media interactions or even the weather.
The implementation of a premium technology like AI in developing India has a lot of challenges ranging from the lack of authentic and quality data to India’s diverse language set. These impediments need to be addressed by the government and industry to maximize AI benefits in the banking and financial services sector of a technology progressive world. And this matters most because of the scale of opportunity waiting, as can be seen in an Accenture report which states that, “93 percent bankers in India said they increasingly use data to drive critical and automated decision-making. Adoption of AI has the potential to add nearly $1 trillion to the Indian economy in 2035.”