AI (Artificial Intelligence), often referred to as machine intelligence occasionally, is the simulation of human intellect in machines. It is the intelligence that machines display, as opposed to the inherent knowledge that people exhibit. AI is developing rapidly, from Siri to self-driving cars. Generally speaking, there are just two core concepts in artificial intelligence.

It begins with researching human brains, such as how their mental processes operate, is also beneficial. By using machine learning, those processes are represented. The use of artificial intelligence, there is more to finance than chatbots. The banking industry is only one of the many industries that artificial intelligence has dominated. This investigation's main goal was to understand the effects of AI on contemporary banking.

Every day, artificial intelligence improves and becomes smarter. The application of artificial intelligence in the Indian banking industry, as well as its advantages and difficulties, will be covered in this essay. FinTech advancements made possible by AI, as well as the various ways it might help Indian banks operate more efficiently.

Introduction
AI is a simulation of human intelligence that aids in the development of better computers that can carry out human tasks in an intelligent manner. Similar to a human brain, AI can think and decide more accurately based on the information provided to it. In the current economy, artificial intelligence is currently becoming more prevalent.

It is employed in many different industries, the banking sector being one of them. AI is being used in the banking sector in a highly creative way that saves both time and money. In order to get reliable results, banks use algorithms. These algorithms then aid in improving customer service and driving up sales performance to increase revenues.

For instance, Amelia, a humanoid (robot) assistant, was created by IPsoft, the global leader in enterprise AI. It is the most human-like digital AI partner in the sector. When one first meets her, it will create an impression that she suggests business. She is wearing a white oxford shirt under a blazer, has light hair, and is appropriately attired.

Amelia is the only AI on the market, according to the business, who claims that this is due to her capacity to learn, interact, and advance over time. More than 100 dialects' words and phrases can be taught to Amelia to understand. She provides real business support, such as reduced operating expenses, enhanced customer satisfaction, and improved employee competency.

Evolution
The history of AI extends back to the 1950s, when Alan Turing released a paper on the potential for machines with real intelligence, even if we have only lately witnessed its implementation. The term "artificial intelligence" had just been coined; yet, until the late 1990s, no actual applications of the theory or technique had been made.

The pace of artificial intelligence only increased after 2011, when big tech companies like Facebook, IBM, Microsoft, and Google began using AI and machine learning for commercial purposes.

Artificial Intelligence Industry In India - The Current Status

The Economic Times reported in October that "Startups witness 108% rise in investment in India in 2018." The news report also noted that among industry sectors, artificial intelligence was one of the domains that had the quickest adoption.

There are currently roughly 400 startups working in the fields of AI and machine learning. Private investors alone have made about $150 million dollars in India's AI industry, and this sum has been increasing since 2016. India has experienced progress, but in terms of investment, it lags far behind nations like the US and China. India will rely on AI for its economic growth and the betterment of its citizenry's quality of life due to its abundant STEM talent and expanding youth population.

In order to better service customers, a number of start-ups with headquarters in places like Bengaluru, New Delhi, Mumbai, and Hyderabad use artificial intelligence. Their product line includes everything from multilingual chat bots to automated consumer data research and online shopping support. The businesses have been engaged in projects related to e-commerce, healthcare, edtech, finance, and other fields. Although still young, these companies' success has been encouraging.

AI in financial services

Additionally, there have been a number of advancements made in the financial sector's asset management, hiring, and customer service processes. For instance, stock investing and finance nowadays rely heavily on technical expertise and good fortune. But in the future, we will be able to manage money in a very different way thanks to algorithms, crowdsourced data, and sentiment analysis.

Future Aspects
The AI revolution has not just affected the banking and finance industries; it has also had an impact on a number of other industries. The robotic (automated) administration of anaesthesia for common procedures, which helps reduce costs, increased patient support, and the launch of self-driving cars are some of the highlights of the sector. All of these would enable the businesses to replace arduous and dull tasks like back-end testing and form filling.

Why AI in Banking Industry?

• Enormous challenges in the banking sector.
• Thrust for a process-driven operation.
• Initiate self-service in the branches.
• Customer desire to deliver different personalized solutions.
• Build functional efficiencies.
• Escalating the productivity of employees.
• To support focus on productivity and efficiency.
• Visualization to extend human function with the use of robotics tools.
• To minimize the chances of fraud and scam.
• Manage an immense volume of data at record speed and gain valuable insights.
• To carry out effective decision-making.

Indian Banks And The Technology

Another important aspect in the adoption of new technologies in the Indian banking sector is the Reserve Bank of India's pragmatic stance. The RBI has recently adopted a cautious but practical approach to embracing new technologies, frequently forcing banks to adopt new technologies through regulation, wherever it has seen potential to improve customer experience and efficiency using a particular technology.

This is especially true during the governorships of Raghuram Rajan and his successor Urjit Patel. The aggressive promotion of new technology use by RBI goes beyond simply developing regulatory frameworks. To make things simpler and more efficient, it has utilised a combination of legislation, evangelism, and even collaboration with the industry.

One example is the establishment of the National Payment Corporation of India (NPCI), which has greatly reduced the cost of electronic transactions. The regulator also has an academic/research division called the Institute of Development and Research in Banking Technology (IDRBT), which is always researching the advantages and disadvantages of emerging technological fields. The fact that both of these organisations have been actively involved in blockchain proof of concept testing is no accident.

The situation with India is pretty unusual. India is undoubtedly a centre for technology. India is a significant location for technology outsourcing and the home of companies with a sizable global market share in core banking. Infosys and TCS, two of the top three providers of core banking solutions, have their corporate offices in India. Recently, there has been a lot of activity in the fintech sector in India as well.

The nation has developed into one of the world's fintech hubs. While banks and fintechs have had a tense relationship in many developed markets, India's most forward-thinking banks, including ICICI Bank, Axis Bank, and HDFC Bank, have actively reached out to fintechs. These banks have organised contests and hackathons to find the best innovations, and occasionally they have even shared their APIs with these fintechs.

The largest bank in India, SBI, announced BankChain on February 8. The National Payments Corporation of India (NPCI), an organisation founded by Indian banks to assist retail payments, is one of the consortium's 30+ members. SBI, the nation's largest lender, is its leader. Simply put, BankChain is a group of banks interested in developing and utilising blockchain technology. In order to develop these solutions, BankChain is assisted by startup Primechain Technologies from Pune. It currently has 8 active projects and 37 members.

Review of literature
In their study "Machine Intelligence vs. Human Judgment in New Venture Finance," Christian Catalini, Chris Foster, and Ramana Nanda (2018) found that machine learning models that were trained to imitate human assessors outperformed models that were only designed to optimise financial success. When choosing from a common out-of-sample applicant pool, they discovered that:

1. Models trained to mimic human picks performed well out-of-sample, suggesting that humans had a predictable pattern of early-stage investing that could be identified and replicated, and
2. Models trained to maximise success outperformed "mimic human models" when choosing from the same applicant pool.
3. comparing the focus of the two models suggests that the differences arose in part due to human heuristics systematically under-emphasizing more ‗cognitively demanding 'elements of the applications. Their findings have important implications for the selection and financing of high potential ideas, and more broadly for how Artificial Intelligence can help humans screen and evaluate information in an era of increasing information overload.

Jewandah S. (2018, July) examines the areas in which machine intelligence is being introduced in banks and applications of AI in significant commercial banks in India in her research paper, "How Artificial Intelligence is altering the banking sector - A case study of top four Commercial Indian Banks."

Traditional banking is improving, and banks are increasingly implementing cutting-edge technologies like blockchain, cloud computing, and AI. However, banks have not yet reached the stage of the AI revolution, and the human touch is still crucial. The Indian banking industry is learning how to employ AI in a way that will soon improve customer service and the way that banks operate.

The effects of AI on business are covered by Andrew Ng (2016) in his research paper, "What artificial intelligence can do and can't do right now." He talks about the age of automation and how machine learning and robotics are changing the way businesses operate. A and B must be carefully chosen for AI work, and the AI must be given the necessary data to determine the A–B link. Creatively choosing A and B has already transformed many different sectors. It is prepared to transform many more.

In their study article Optimizing portfolio creation using artificial intelligence, Chan Kok Thim and Eric Seah (2011) aim to increase the usefulness of Artificial Intelligence by applying Neural Network (NN) in the real market. In order to replicate and enhance portfolio development, this paper summarised the standard Markowitz Theory's Efficient Frontier. It also built up a neural system heuristic to help readers better understand how Artificial Intelligence can develop ideal portfolio capacity and provide yields to all levels of financial specialists.

According to Ryoji Kashiwagi's 2005 study "Utilization of Artificial Intelligence in Finance," man-made artificial intelligence is currently entering its third boom stage in history as a result of a scientific development called profound learning. Artificial intelligence is employed in a variety of structures, including the financial sector. Financial institutions should employ human consciousness more efficiently by using techniques like open innovation.

Artificial Intelligence Technology In Banking And Finance
Personalized Financial Services
As automated financial counsellors and planners offer their knowledge in making financial decisions, personalised connect will reach new heights. They provide recommendations on equities and bonds after analysing market sentiment in relation to the user's financial objectives and personal portfolio.

Smart Wallets
With major businesses like Google, Apple, Paypal, and others jumping on the bandwagon and creating their own payment gateways, digital wallets are being heralded as the wave of the future for conventional payment methods. This lessens reliance on actual money, extending the use of money to higher levels.

Underwriting
The insurance industry is likewise experiencing a storm as they transition to consistent automation. The businesses are given more detailed information to support their decisions by using AI tools that automate the underwriting process.

Voice Assisted Banking
As technology enables users to access banking services with voice commands and touch screens, physical presence is gradually vanishing. Natural language processing technology can process queries to provide information, respond to inquiries, and link consumers to different financial services. As a result, efficiency is systematised, reducing human error.

Customer support
We are getting closer to the time when computers might handle the majority of customer support inquiries as speech processing and natural language processing technology advance. Customers would be happier as a result of the end of line waiting.

Digitalization instead of branch lines
The lengthy process of banking has historically been hampered by long lines and slow service. Even opening a bank account was seen negatively because frantic customers would run from one piece of paperwork to the next. Documentation digitization reduces this discomfort and builds a robust platform for connecting customers and service providers.

Blockchain hastening payments
The digital revolution, particularly social media and mobile, is driving a significant shift in the buying habits and preferences of the consumer base that banks service. There is a rising need for more choice and control in how people interact with banks. Slow payment processes will be a thing of the past thanks to Blockchain, which is slated to introduce the benefit of real-time payment processing, accelerating the payment process and boosting support and satisfaction.

Artificial Intelligence Banking in India
The global investment in AI applications reached USD 5.1 billion (EUR 4.3 billion) in 2016, according to the PwC FinTech Trends Report (India) 2017. Not only PNB, but also other Indian banks including SBI, HDFC, ICICI, HSBC, and Axis banks have embraced AI.

State Bank of India (SBI)
For developers, startups, and students to develop creative concepts and solutions for the banking industry that focus on technologies like predictive analytics, fintech/blockchain, digital payments, IoT, AI, machine learning, BOTS, and robotic process automation, SBI launched a national hackathon called "Code For Bank." The bank presently employs an AI-based solution created by Chapdex, the winning team from its first hackathon, which records consumer facial expressions and aids in analysing customer behaviour.

HDFC Bank
Eva (Electronic Virtual Assistance), an AI-based chatbot developed by Bengaluru-based Senseforth, has answered over 2.7 million customer questions, engaged with over 530,000 different users, and carried over 1.2 million conversations. In the first few days after its launch, the device, which can respond to queries in less than 0.4 seconds, has already answered more than 100,000 inquiries from hundreds of users in 17 different countries. Additionally, the bank is testing with an in-store robot programme called IRA (Intelligent Robotic Assistant).

ICICI Bank
Over 200 business operations across a number of ICICI Bank functions now use software robotics. The bank refers to this technology as "robotic software," and it claims to be the first in the nation and one of the few in the world to use it to automate and carry out time-consuming, repetitive, and high-volume business processes.

Axis Bank
Recently, Axis Bank released a conversational banking app with AI and NLP (Natural Language Processing) capabilities to assist customers with financial and non-financial activities, respond to frequently asked questions, and contact the bank for loans.

The Challenges Facing India's AI Development:

1. Up until now, consumer goods have been the main focus of AI-based applications, which have been predominantly driven by the private sector. Government policymakers must pay attention because of the technology's expanding scope and repercussions.
    
2. India should take into account the public and commercial funding strategies for AI research that have been proven successful in the United States, China, South Korea, and other countries.
    
3. The sequential structure of education and employment is no longer relevant in the current economic climate since jobs are changing quickly and skills are becoming less and less valued over the course of a few years.

Artificial Intelligence In Modern Day Banking
In order to compete in a future replete with cutting edge technology, banks must wait to embark on their artificial intelligence adventure.

Drive thru Banking:
Allows you to conduct banking transactions while still in the automobile. The customer can transact through a window in one of the lanes. For drive-through banking, a voice AI system is being developed to take the position of people. In July 2018, Clinc, an Ann Arbor-based business that has created voice-powered artificial intelligence platforms for banking in 2015. Its conversational AI innovation can identify orders even from people with strong accents or language hurdles and can rectify the conversation as needed.

Bank Stations:
Artificial intelligence is a tool that banks can use in their front, middle, and back offices. The bank stations are a network of self-service terminals that offer customers a variety of value-based online services, such as online bill payment and online government services. The use of big data in banks is revolutionising the sector and has become the industry norm. The banking industry is using the data to enhance client connections, and AI is assisting in structuring and sorting the data. The future of banking will use artificial intelligence to cater to millennial customers.

Passbook updation Kaisok:
Over the past few years, the Indian banking sector has changed from being driven by people to being managed by machines. The automatic kiosk for printing passbooks allows users to print their passbooks. Large-scale installations of this facility have been made by Indian banks including SBI and Bank of Baroda.

They have set up self-service passbook kiosks so that users can print their own passbooks. For instance, Swayam, a passbook printing kiosk from Indian Bank SBI, uses barcode technology to make it simple for users to update their passbooks. Banks have been hiring, but as the front-end talent is highlighted, the skill sets that are needed are shifting.

Chatbot-The Intelligent Banking Assistant:
Virtual assistants, often known as chatbots, are innovative tools created to make it easier for people to engage with computers. The front-desk environments at banks are being replaced with chatbots, an example of AI in banking. These AI-driven robots provide customers highly advanced digitalized and interactive experiences. SBI, an Indian bank, has introduced SIA (SBI Intelligent Assistant), a chatbot that assists customers with routine financial transactions in a manner similar to that of bank employees. Additionally, it answers NRI customers' queries in a timely manner in the SBI gateway chat box.

Cash Deposit Machine:
Cash can be deposited at any time using the self-service cash deposit machines. The inconvenience of waiting in line to deposit cash at banks is resolved by this option. The quickest and most dependable way to make a cash deposit is through a bank. This service, where the account balance is immediately credited, is provided by both state-owned and commercial banks. For each successful transaction, the customer will obtain a transaction receipt. Using this device, payments can also be made to other accounts.

ATM Machine Helpline:
In case of an emergency, these helplines are available in ATMs to assist clients in getting in touch with their respective banks. Even ATMs now feature artificial intelligence. ATMs now feature the following segment types: Face recognition for security and bettering the user experience, machine learning for ATM cybersecurity, automated ATM cameras, preventative maintenance of ATMs, and anticipating ATM cash demand are some examples of further applications for machine learning.

Mobile Banking:
Globally, mobile devices are getting smarter. Since mobile banking is heavily reliant on millions of people, AI-powered banking mobile apps are highly appealing to them. Customers transitioned to mobile banking with ease. Having a personal virtual assistant, whether it be Alexa from Amazon or Siri from Apple, is quite appealing.

It has received widespread approval and acclaim from users all over the world. The client's needs can be easily satisfied by mobile apps. Intelligent apps can monitor a user's actions and provide them with personalised advice on how to save costs and save money.

These days, every bank provides these text and mobile banking services. The usage of mobile banking has made routine tasks, such as payments and money transfers, more convenient. Customers can do better financial planning, can get smart financial advisory, can do efficient and quicker transactions with the advent of artificial intelligence in mobile banking.

Blockchain Technology and Banking:
Blockchain is distributed, decentralized and digital ledger. It is digital information (block) stored on public database (chain). Blockchain is used to store encrypted data and Artificial Intelligence is the brain or engine to enable decision making and assists in analysis of data collected.

Most often it is argued that blockchain technology is only beneficial for cryptocurrency industry but that is not true. Blockchain technology visions to solve multiple issues related to digital transactions such as data security, fraud prevention etc. Blockchain is the future of inter-bank transactions, cross border remittances, crypto banking, record storing, KYC, loan syndication, increased transparency to name a few.

Analysis and Findings
Based on information gathered from 112 respondents, this analysis. The majority of respondents, who are in their mid-20s, 30s, and 40s, are those who are most affected by artificial intelligence in the banking sector. They also feel that AI is beneficial and friendly, and they periodically watch for the introduction of new developments in the field. 80 out of 112 people, or 71.4%, believe that using artificial intelligence in banking is advantageous.

27 out of the 112 respondents, or 24.1%, are unsure whether using artificial intelligence in banking is advantageous. 5.5%, or 5 out of 112 respondents, do not believe it to be at all beneficial. 99 out of 112 people, or 58.9%, use automated financial advisors to make investments in the market. 64.3% i.e. 72 people out of 112 agree that after implementing artificial intelligence in banking system has improved speed of services. 13.4% i.e. 15 people out of 112 are not sure that it has improved or not. 22.3% i.e. 25 people don't agree that it has any impact on fast services.

Most of the respondents prefer smart wallets over cash transaction which means people are taking benefits of artificial intelligence. As online fraud is a major issue now days people can easily hack into your account, 81.4% respondents believe that artificial intelligence can double the security system in banks. 18.6% people do not fully trust the machines, they need a little bit of human touch and prefer visiting the banks in traditional ways.

Conclusion
Artificial intelligence (AI) is driving a sea change in the financial industry and the world of banking is changing quicker than ever. In the banking industry, many AI technologies have been used in areas like core banking, operational performance, customer service, and analytics.

For AI, banking now encompasses a whole new universe of contemporary banks rather than simply physical locations. Modern banks' provision of new banking services aids in their expansion and growth. Increased cost effectiveness, increased banking system penetration, and the ability to conduct low-value transactions are all made feasible by technology. The growth and development of banks are multiplied when technology is used effectively.

Because of this, more customers are drawn to the use of artificial intelligence, and it is helping the banks to grow more. Banks can apply AI to improve the client experience by empowering frictionless, round the clock client association - however AI in banking applications isn't simply restricted to retail banking services. The back and middle office of investment banking and all other money related supervisions are gaining by AI.

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