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Role of Artificial Intelligence in Providing Customer Services with Special Reference to SBI and HDFC Bank

Technology has changed the operating psychology of the businesses over the last couple of years. There is a growing need and demand to use Artificial Intelligence (AI) and the Indian banking Sector is gradually shifting itself towards using AI. Banks are exploring and implementing technology in various ways. Artificial Intelligence is getting better and smarter day by day. The adoption of AI in banking has grown a lot than other sectors. This is happened because banking sector still has lot of human intervention in the operations. Indian banking sector is exploring the ways to enhance customer services with the help of Artificial Intelligence. This paper is about how Artificial Intelligence (AI) is used by Indian banks with reference to SBI and HDFC Bank to improvise customer services in future.


A. Introduction:
Technology is the cornerstone of India's banking sector. Indian banks may have embarked on their technological journey only in the mid-to late 1990s, they have more than made up for this relatively late start. The banking sector has deployed the latest technologies from core banking and payment systems to risk management and, more recently, digital strategies.Artificial Intelligence (AI) has been around for decades, ever since John McCarthy defined it as "the science and engineering of making intelligent machines". Due to its high potential, its adoption is being treated as the fourth industrial revolution. As with any major advancement in technology, it brings with it a spectrum of opportunities as well as challenges. Several applications have been developed or under development with potential to improve the quality of life significantly. But it is only lately that AI technology has undergone rapid evolution and raised significant interest among the banking sector. Artificial Intelligence is the theory and development of computer systems which can perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.The Indian banking sector is adopting AI quite aggressively. According to Fintech India report by PwC in 2017, the global spending in AI applications touched $5.1 billion, up from $4 billion in 2015. There is a keen interest in the Indian banking sector as well. Natural Language Processing, Natural Language Generation, Machine Learning (such as Neural networks/deep learning), and Computer Vision have been adopted by the sector. The banking industry has found the use of AI in the area of Customer Interface: Banks are using virtual customer assistance to provide resolution to their queries and for this Chatbot is being used on platforms such as mobile applications and websites, as well as social media platforms such as Facebook Messenger, Telegram, WhatsApp and Twitter. Customer Insights and Personalization: AI has the potential to provide customers with personalized engagement services through the use of AI algorithms. The technology observes clients" behavior patterns based on digital profiles and transactional history it suggests products which are tailored to meet their requirements. By using emotional Analytics for Social Enterprises, it is possible to gain better insights into the emotional and cognitive state of clients. From the video and audio inputs, the application will help microfinance advisors better understand the topics that would cause users to engage or disengage during the microfinance process. Business and Strategy Insights: With the availability of large amount of data with banks, AI can enable better understanding. Such analysis can facilitate deeper and realtime insights into internal operations and external market dynamics, informing potential strategies across various departments. Deeper insights into customer data, for example, can facilitate marketing and portfolio strategies. It can also be used for digital payments. Facilitating Backend Processes: AI is being utilized to assist with backend office operations that often involve high volume, rules based and highly organized and systematic work. AI technologies can be used to perform "intelligent automation" like automating the writing of investment/earning reports, or extracting functional information from relevant financial documents. Credit Scoring and Loan Decisions: AI is used by lenders to calculate credit scores and develop credit profiles. Firms can make fast credit decisions by analyzing individual"s banking transactions, their past decisions, their spending and earning habits and, familial history, mobile data etc. Fraud Detection and Risk Management: AI is used to monitor and prevent various instances of fraud, money laundering, malpractice and the detection of potential risks.

Government Initiatives
In India, the government is investing heavily in AI. The finance minister in her budget speech of 2019 emphasized on development of new-age skills like Artificial Intelligence (AI), Internet of Things, Big Data, 3D Printing, Virtual Reality and Robotics. The 2018 budget allocated $480 Mn (Rs. 3,703 Crore) to the Digital India programme, effectively doubling its past investment. These initiatives are seen in the form of joint projects, internal programs, and the AI Task Force. While most of these initiatives concern a broader implementation of AI, there are several initiatives specific to, and others that indirectly affect the banking and finance industry. The Banking sector cannot stay aloof from technology if it intends to be updated and competitive for providing prompt services to its customers. AI is used to provide personalize financial services, smart wallets, underwriting, voice assisted banking, application to assist in lending decisions, customer support and digitization. It covers usage of AI and its implication on the top banks in India. AI has assisted in detection of frauds, reduction in cost and increase in revenue, making customer experience better. It was identified that SBI, HDFC, ICICI and Axis Bank have entered the digital era through chatbots and usage of robotic software. 10.4301/S1807 1775201815004 This paper covers evolution of AI from its inception to till date. Late fifties and early sixties focused on development of general techniques which could be applied in several domains which weren"t that successful till late eighties. With the increase in storage capacity and computational ability of computers, AI has progressed since the last decade. Eminent scholars have raised concerns like existential threat, safety, slowdown in the growth of economy, unemployment etc. The international scenario of application of AI was studied via sectoral analysis of healthcare, education, cyber security, law, finance, information browsing, transport, virtual assistants, ecommerce, customer care, energy etc. Policy documents framed by US, UK, Japan, Singapore and even China was studied. The report concluded with AI developments in India. Various startup companies are providing AI expertise in sectors likehealthcare, e-commerce, finance etc. IT majors like TCS, IBM and Infosys are contributing to AI development. India has huge knowledge resources, however issues of infrastructure development, policy & regulations, research & development, and human resource development needs to be addressed in collaboration with government and corporates.

Robotic Process Automation -A Study Of The Impact On Customer Experience In Retail Banking Industry
Karippur Nanda Kumar & Pushpa Rani Balaramachandran, S P Jain School of Global Management, Journal of Internet Banking and Commerce, December 2018, vol. 23, no. 3 The paper discusses challenges retail banking industry has faced due to disruptive technology such as intelligent automation and competition from Fintech startups. It emphasizes on usage of Robotic Process Automation (RPA)to maintain competitive advantage and increase profitability, thereby improving efficiency, accuracy, 24/7 operations, reduce cost and offering innovative services and better experience to customers. The relationship of four independent factors ie Security and Privacy; Reliability; Usefulness and Human-like interaction were studied with dependent variable i.e. RPA in order to identify the usage of RPA in retail banking industry. to the self-service mode. Chatbots will not replace customer executives but will complement them, providing customers with a richer experience. The bank intends to provide a uniform experience to app operated, or the internet or social media or walk-in branch customers. It focuses on providing a platform-led approach. The emphasis is not on product-specific or channel-led or segment-led approach, but it should be subsets of a platform-led approach. The bank engaged with at least 25 fintech companies for AI and marketing to risk analytics and payments as it intends to move from a multichannel to an omnichannel experience. It also experimented with holographic conversations which it discontinued due to poor customer acceptance. Smartwatch banking could not scale up because the watch itself did not do well. Bank is bullish on the smartwatch as a potential banking interface as it will communicate on its own and multiple things can be connected to watch even if the smartphone is at home as it doesn't have to be paired with it. A report from Accenture Plc estimates competition from digital players could erode as much as one-third of traditional retail bank revenues by 2020, hence it puts pressing needs on banks to outperform the competitors. ICICI Bank is working on IoT and machine learning in matters concerning HR. In September 2016, the bank announced the deployment of software robotics in over 200 business processes, including agribusiness, trade, and foreign exchange, apart from retail banking and HR. The investment in these processes led to reduce response time by 60 per cent and increase accuracy to 100 per cent. Many fintech companies are working on improvising chatbots that will be able to comprehend regional languages as well as the Hindi-English combination.

C. Research Gaps:
The banking sector has grown leaps and bounds in terms of technological development and use of artificial intelligence. However, not much research evidence is seen in the usage of humanoid robots in the sector. More research is required in the activities which the robot can undertake as presently it only focuses on handling customer basic queries. The present research has laid emphasis only on the implementation of AI for various services but there is need to have more research on customer satisfaction. There is tremendous scope to cover the challenges faced by banks in providing such services, and how cost effective and competitive has it proved to the bank. The entire scope of AI has been only on providing basic information to clients on primary banking products, but which other services can it cover is something which needs much research.

D. Scope of the Study:
Study is restricted to HDFC Bank and SBI only in Mumbai region. Study of AI is limited to customer services only. E. Objectives of the Study: 1) To study the methodology of adoption of AI in banks.
2) To understand challenges faced by banks while adoption of AI.
3) To understand how AI helped banks in betterment of customer services of HDFC and SBI as well as customer feedback on the same.

F. Research Methodology:
Research is based on exploratory research. Present study is based on primary as well as secondary data. Primary data is collected from customers of top two commercial banks i.e. HDFC bank and SBI consisting of questions related to improvement in customer services through AI, challenges faced and customers" feedback. 50 customers of each bank were surveyed to collect data on awareness, usage and

SBI -Usage Occupation wise
Service Business Student Others   6. Banks need to put efforts in increasing the volume of transactions through this app as regular users are equally concerned about data safety, account hacking and other online frauds, impairing the usage of the app to its potential.

I. Conclusion
There are huge investments from the banking industry in AI implementation. However, the sector has challenges in terms of awareness, acceptance of new technology, issues with security and data threat. Banks need to promote these products and should have strong policies in place to enable its optimum usage.

J.
Scope for Further Research The paper covered the customer satisfaction in the usage of few AI services of two banks. AI is not restricted only to app services, feeback of chatbots, humanoid robots" implementation in banks is yet to be measured as it is in early stages of implementation.