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Study on Artificial Intelligence (AI) in Banking and Financial Services

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Study on Artificial Intelligence (AI) in Banking and Financial Services (MBA Finance)

Introduction

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are capable of performing tasks that typically require human intelligence. These tasks can include reasoning, learning, problem-solving, perception, language understanding, and decision-making. “Artificial Intelligence is defined as the ability of a machine to perform cognitive functions we associate with human minds, such as perceiving, reasoning, learning, interacting with the environment, problem solving, and even exercising creativity”. However, Artificial Intelligence (AI) is actually a combination of advanced computational technologies in varying degrees of maturity.

There are also a range of improvements in the way communications, customer support, and recruiting and asset management take place throughout financial sector. Today, for example, stock investing and finance is all about technical skills and divine luck. Yet in the future, with the aid of sentiment analysis, crowdsourced data and algorithms, we will be able to handle money in a much different way. Artificial Intelligence (AI) has had a significant impact on the financial services industry, transforming how financial institutions operate, make decisions, and engage with customers. Major Areas of Artificial Intelligence can be used in banking and financial services are.

1. Customer Service and Chatbots: Chatbots powered by AI provide automated customer support, answer queries, and assist with basic transactions. They can offer 24/7 service and improve customer satisfaction.
2. Personalized Financial Advice: AI-driven robo-advisors offer personalized investment advice based on individual risk profiles and financial goals. They manage portfolios, rebalance investments, and optimize tax strategies.
3. Algorithmic Trading: AI algorithms analyze market data in real time to execute trades with speed and accuracy. These algorithms can identify patterns, trends, and anomalies that human traders might miss.
4. Risk Assessment and Management: AI is used to assess credit risk, detect fraudulent activities, and prevent financial crimes. Machine learning models can analyze large volumes of transaction data to identify unusual patterns and potential risks.
5. Fraud Detection and Prevention: AI algorithms can analyze customer behavior and transaction patterns to detect fraudulent activities in real time, helping to prevent unauthorized transactions.
6. Credit Scoring: AI models analyze a wide range of data, including alternative data sources, to assess creditworthiness and provide more accurate credit scores for individuals and businesses.
7. Quantitative Analysis: AI helps in quantitative analysis by processing vast amounts of financial data to identify correlations, generate trading signals, and develop investment strategies.
8. Portfolio Management: AI-powered tools assist portfolio managers in making informed decisions by analyzing market data and suggesting optimal investment moves.
Regulatory Compliance: AI can assist in monitoring transactions to ensure compliance with regulations like Anti-Money Laundering (AML) and Know Your Customer (KYC) requirements.
9. Predictive Analytics: AI models can predict market trends, customer behavior, and potential financial crises by analyzing historical data and external factors.
10. Fraud Prevention in Payments: AI analyzes payment data to identify and prevent fraudulent transactions in real time, protecting both customers and financial institutions.
11. Algorithmic Lending: AI-driven lending platforms assess borrower creditworthiness and determine loan terms based on vast amounts of data, enabling faster loan approvals.
12. Market Sentiment Analysis: AI analyzes news articles, social media, and other sources to gauge market sentiment and predict market movements.
13. High-Frequency Trading: AI algorithms execute high-frequency trades based on real-time market data and predefined criteria, aiming to take advantage of minute price fluctuations.
14. Blockchain and Cryptocurrencies: AI can enhance security and transparency in blockchain networks, optimize cryptocurrency trading strategies, and analyze market trends.

As AI continues to advance, financial institutions are becoming more efficient, customer-centric, and competitive. However, challenges related to data privacy, bias, regulation, and the need for human oversight also need to be carefully addressed to ensure the responsible and effective use of AI in financial services.

Objective of study

• To study Artificial Intelligence (AI) concepts and areas of implementations
• To know major areas of Artificial Intelligence can be used in banking and financial services
• To know different AI application in banking and financial services
• To study about Artificial Intelligence - AI in banking and financial services in perceptions of clients or consumers.
• To study about banking and financial services for using Artificial Intelligence is to offer customized product.

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This MBA project can be used for following universities

• Sikkim Manipal University, SMU - Gangtok, Sikkim
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• SCDL - Pune, Maharashtra Welingkar - Mumbai, Maharashtra
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• Osmania University- Hyderabad, Aandhra Pradesh Anna University Chennai - Tamil Nadu
• Yashwantrao Chawan Maharashtra Open University, YCMOU - Nasik, Maharashtra
• University of Mumbai - Mumbai, Maharashtra
• Dr. B.R.Ambedkar Open University - Hyderabad, Aandhra Pradesh
• Maulana Azad National Urdu University - Hyderabad, Aandhra Pradesh
• Netaji Subhas Open University - Kolkata, West Bengal
• Delhi University - New Delhi, Delhi
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• Maharishi Dayanand University - Rohtak, Haryana
• Andhra University - Visakhapatnam, Aandhra Pradesh
• Dr. Babasaheb Ambedkar Open University - Ahmedabad, Gujarat
• SNDT – Women’s University - Mumbai, Maharashtra
• Alagappa University - Karaikudi, Tamil Nadu M.P.
• Bhoj(Open) University - Bhopal, Madhya Pradesh

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