Artificial Intelligence (AI) In BFSI Market Latest Trend, Growth, Size, Application & Forecast 2024 | Google, IBM, Microsoft, Amazon, SAP, Oracle, Baidu, Salesforce, Digital Reasoning, Intel, Ipsoft

Banks cover more than 50% of the artificial intelligence (AI) in BFSI market. The banks are teaming up with the fintech companies to develop advanced products and improve the customer services. They are relying more on machine learning algorithms for the risk management and fraud detection. Furthermore, the adoption of the digital banking solutions and supportive government initiatives launched by the government to promote the digital banking also fosters the artificial intelligence (AI) in BFSI market growth.

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The customer service is the dominating application of the artificial intelligence (AI) in BFSI market with over 45% share in the revenue in 2017. The integration of the conversational AI solution and chatbot among the financial institutes is propelling the growth. Furthermore, the use of advanced analytical tools by the banks, insurance, and wealth management companies to analyze the credit rating, risk profiling, and analyzing the customer behavior to provide personalized products and services also supports the technology in fintech growth.

Machine learning technology accounts for approximately 40% share in the artificial intelligence (AI) in BFSI market. The integration of the intelligent algorithms for risk mitigation and compliance, anti-money laundering, and fraud detection applications is the primary factor that augments the demand for the technology. Natural Language Processing (NLP) is also used widely in the BFSI sector in the customer contact center to analyze the customers' voice and solve their queries. Financial institutions are also utilizing NLP for back-office applications & operations and text-mining.

Embarking on its AI and automation journey in September 2017, State Bank of India unveiled its first AI-powered chat & voice assistant, named as SBI’s Intelligent Assistant or SIA. The chatbot reportedly aids customers with everyday banking tasks just like a bank representative and has a remarkable capacity to handle close to 10,000 enquiries per second or 864 million in a day. Arguably, the deployment of an AI-based solution of this scale is cited to be first of its kind in the banking segment of the global artificial intelligence (AI) in BFSI market. With an astonishing customer strength of around 420 million, State Bank of India’s latest move towards integrating AI is being viewed as a major leap of faith for India’s banking sector.

Regarded as one of the world’s largest banks, the U.S. based JPMorgan Chase has recently launched a digital platform that analyzes legal documents and extracts the relevant data. The AI-based invention, named as Contract Intelligence (COiN) platform, is an outcome of the initial implementation through machine learning technology and has an exceptional ability to revise approximately 12,000 annual sales agreements within minutes. The platform is being aptly termed as revolutionary across artificial intelligence (AI) in BFSI market given the fact that it effectively eliminates the need to manually review the said number of sales agreements which generally takes around 360,000 hours.

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The artificial intelligence (AI) in BFSI market is characterized by the presence of a large number of AI and fintech companies. Several new players are entering the market to take the advantage of the myriad growth opportunities offered by the market. The prominent players of the AI solutions in the BFSI sector are Salesforce, Google, IBM, Microsoft, Amazon, SAP, Oracle, Baidu, Digital Reasoning, Intel, Ipsoft, and Palantir.

Glimpse of Table of Content (ToC)

Chapter 3. Artificial intelligence (AI) in BFSI market Insights
3.1. Introduction
3.2. Industry segmentation
3.3. Industry landscape, 2013-2024
3.4. Industry ecosystem analysis
3.5. artificial intelligence (AI) in BFSI market evolution
3.6. Market news
3.7. Investment landscape
3.7.1. AI investment
3.7.1.1. Americas
3.7.1.2. EMEA
3.7.1.3. Asia Pacific
3.7.2. Fintech investment
3.7.2.1. Americas
3.7.2.2. EMEA
3.7.2.3. Asia Pacific
3.8. Regulatory landscape
3.8.1. Health Insurance Portability and Accountability Act (HIPAA)
3.8.2. Payment Card Industry Data Security Standard (PCI DSS)
3.8.3. North American Electric Reliability Corp. (NERC) Standards
3.8.4. Federal Information Security Management Act (FISMA)
3.8.5. The Gramma-Leach-Bliley Act (GLB) Act of 1999
3.8.6. Sarbanes-Oxley Act of 2002
3.8.7. General Data Protection Regulation (GDPR)
3.8.8. Alternative Investment Fund Managers Directive (AIFMD)
3.8.9. Anti-Money Laundering Directive 2015/849/EU (AMLD)
3.8.10. Dodd–Frank Wall Street Reform and Consumer Protection Act
3.8.11. European Market Infrastructure Regulation (EMIR)
3.8.12. Foreign Account Tax Compliance Act (FATCA)
3.8.13. Markets in Financial Instruments Directive (MIFID)
3.9. Use cases
3.9.1. Algorithmic trading
3.9.2. Anti-money laundering (AML) pattern detection
3.9.3. Customer service
3.9.4. Fraud detection
3.9.5. Insurance & loan underwriting
3.9.6. Portfolio management
3.10. Industry impact forces
3.10.1. Growth drivers
3.10.1.1. Exponentially growing digital data
3.10.1.2. Rising investment in AI
3.10.1.3. Increasing partnership between financial institutes and fintech companies
3.10.1.4. Growing need to provide enhanced customer experience
3.10.2. Artificial intelligence (AI) in BFSI market pitfalls & challenges
3.10.2.1. Data safety & security
3.10.2.2. Black box effect
3.11. Growth potential analysis
3.12. Porter's analysis
3.13. PESTEL analysis

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