Artificial intelligence & Machine learning role in financial services
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The document discusses the significant role of artificial intelligence (AI) and machine learning (ML) in the financial services sector, highlighting their capabilities in fraud detection, risk management, and business optimization. It emphasizes the importance of financial data analysis for improving efficiency, customer satisfaction, and security while presenting various use cases for AI and ML applications in finance. The author concludes that while AI and ML technologies have high potential for transforming the industry, they are still in early stages and should complement, rather than replace, human efforts in the workplace.
Artificial intelligence & Machine learning role in financial services
- 1. Artificial Intelligence & Machine Learning role in Financial Services PRUDHVI PARNE 3RD INTERNATIONAL CONFERENCE ON MACHINE LEARNING & APPLICATIONS (CMLA 2021) SEPTEMBER 25 ~26, TORONTO, CANADA
- 2. ABOUT ME: Profession: Solution Architect and Team Leader Background: Computer Science, Information Technology and Financial Technology Academic: MS in Computer Science from University of Louisiana, Lafayette : https://www.linkedin.com/in/prudhviparne
- 3. Contents Introduction Artificial Intelligence in Finance Importance of Financial Data Risk Management AI and ML business Applications and use cases Summary
- 4. Introduction A few years back, people dreamt about machines to clear up troubles faster than humans. Now we can see how AI is ruling all the industries which include education, banking, transportation, etc. in a unique manner. Financial services are the economical backbone of any nation in the world. There are billions of financial transactions which are taking place and all this data is considered as a gold mine for many different organizations. AI has the ability to process this data, can also detect frauds, identify possible attacks. In this presentation, we discuss the role and impacts of AI & ML in Financial Sector.
- 5. AI in Finance BFSI as it is commonly stands for Banking, Securities, Finance, and Insurance These are the core systems of the financial sector and vast amounts of data generated by them AI helps the financial sector by reducing the number of manual errors by consistently developing decision-making processes . Machine learning capabilities efficiently utilize AI to identify future opportunities by understanding the data and transactions Helps to develop better strategies to improve the business prospects, Helps to develop autonomous response capabilities to improve the communications with the customers.
- 6. Importance of Financial Data Data analysis - The development of data analysis capabilities are very important to all industries improves efficiency and develop better customer satisfaction identify new opportunities improve reachability identify the products that can be developed and sustained in a longer run improve the security measures One of the key benefits of AI & ML is, its capable to help industries by analyzing the data efficiently and improves the business prospects.
- 7. Importance of Financial Data Financial sectors holds lot of sensitivity information, which makes it one of the primary targets by attackers Attackers try to gain access to the infrastructure and the core systems AI can efficiently identify the possible attacks by understanding the signatures, patterns, anomalies, and many other identifiers can be used to detect abnormal activities in the network It can also alert the security team on possible intrusion attempts carried out. With AI & ML, we can also review historical information to identify the difference in the activities can efficiently identify anomalies in the transactions also analyzes the activities of the customers which may develop into risk. We can proactively identify possible solutions that can be effectively utilized to reduce these security risks
- 8. Tools for Financial Sector The financial sectors offer multiple products to the customers with different benefits Implementation of AI & ML technologies can enable the organization to improve the business prospects by identifying the prospective customers worldwide providing proposals for individual tailor-made products developing communication with the clients through automated processes implementation of Chatbots in sales and services Banks can develop best business solutions with AI powered data analysis By Predicting the customer needs and providing instant services
- 9. AI and ML based business use cases Front Office Customer Service Sale and Marketing Wealth Advisory & Financial Assistance Mid Office Risk Assessment Fraud detection/AML Credit Scoring Back Office Settlements processing Cash & liquidity management Reconciliation
- 10. Risk Management The financial sector is full of risks due to the nature of activities carried out. Risk management is one of the critical activities in the financial sector Identifying the triggers that may increase the risks for an organization is one of the key activities. Artificial intelligence and machine learning can detect activities beyond the acceptable range of the organization. AI & ML can reduce exposure to higher risks which improves the performance of the organization. AI has the ability to inspect the live transactions data, learn from the live feed, analyze the available information, identify and detect anomalies that can promote risks, and it develops appropriate alert mechanisms. With this, we create preventive measures effectively, manage the risks and develop better profitability.
- 11. Efficient and Effective Utilization of AI Consistency & Authenticity Consistent utilization of AI & ML capabilities reduce the number of Manual jobs but provide consistency in the information and its authenticity Profitability – AI improves the opportunities for the organization to improve the business prospects and develop better profitability By identification of future requirements of the customers By understanding the needs of the customers When we provide what customer needs, customers base increase and organization grows Security With AI based risk management process to detect risks at the earliest age, we can effectively manage the security.
- 12. Benefactors of AI & ML BLOCKCHAIN TECHNOLOGIES What is Blockchain technologies - is growing list of records and they are linked together with cryptography. Primary use of blockchain as distributed ledger for cryptocurrencies such as bitcoin. Blockchain and AI make a powerful pair, both have evolved into leading technologies that power innovation across every industry. AI Powered Blockchain technologies provide high security features improves decision making process and capabilities Coin Genius is an AI driven crypto currency trading platform It provides AI based scoring systems and advanced forecasting to its customers
- 13. AI and ML based Applications (1) “Trading Robots” on Market sway analysis Market sway analysis includes assessing the impact of an association's trading on market costs and guide them. Machine learning can be used to make 'trading robots’, helps customers with constant market changes and provides future predictions. Firms are exploring utilizing AI tools to evaluate the market effect of a given business. AI and machine learning can supplement traditional market sway models.
- 14. AI and ML based Applications (2) Insurance Domain AI and machine learning applications can significantly increase some protection area capacities, such as endorsing and preparing claims. Machine learning procedures can decide repair costs and naturally sort the seriousness of vehicle mishap harm AI helps to reduce claims preparing times and functional expenses. Insurance agencies are additionally investigating to use AI and machine learning based remote sensors/devices to observe customer driving patterns.
- 15. AI and ML based Applications (3) Credit Scoring Applications By utilizing machine learning, we can accelerate loaning decisions while possibly restricting gradual danger. Apart from customer credit scores - banks and moneylenders are progressively evaluating customer spending behavior, online media movement, cell phone use, various bills, and digital footprints etc. Applying machine learning algorithms to this star grouping of new information has empowered the evaluation of subjective factors like customer conduct and pay. With the intention to speeding the loaning process and the decision.
- 16. Summary Artificial Intelligence and Machine Learning are groundbreaking technologies that are still in their primary stages of development and adoption. They have very high capabilities and if they are implemented correctly can change the very way of the finance sector. All the big financial organizations are investing heavily in these technologies because the return on investments is very high. There is still some time required for these technologies to mature and recognize their utmost potential. AI & ML are not meant to replace employees but to make the lives of employees easy. The management needs to come up with the best combination of human and artificial intelligence for the development of any industry
- 17. Thank You!