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Global AI in Financial Services Market Report 2020 - Adoption Statistics, Emerging Patterns, Future Trends

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DUBLIN, March 10, 2020 /PRNewswire/ -- The "Artificial Intelligence: Technology, Applications and Implementation for Financial Services" report has been added to ResearchAndMarkets.com's offering.

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Artificial Intelligence adoption by financial services will be helped by a combination of improving technologies, increased user acceptance/adoption as well as standards and regulatory frameworks that are becoming more attuned to the specific risks and opportunities presented by biometric technologies.

In the first section of this report, the analyst looks at the various elements & scope of Artificial Intelligence with a brief history, the foundations & innovations of AI and their usefulness in financial services industry, the high-level technological functions that allow a firm to take full advantage of the uniqueness, permanence and low circumvention of Artificial Intelligence. Artificial Intelligence systems and AI frameworks related to financial services are also reviewed.

In the second section, in addition to reviewing the current industry adoption with key market drivers & constraints, the analyst also looks at practical examples of financial services firms (Banks, Insurance companies, Fintechs & Assets management firms) that have implemented Artificial Intelligence to deal with specific use cases.

In the third section, the analyst looks at a framework & considerations for building a competent AI system with a practical example. Furthermore, the analyst also reviewed challenges and factors to be considered while evaluating an Artificial Intelligence system.

In the fourth & fifth section, the analyst reviewed various Artificial Intelligence standards and standard-developing committees such as ISO standards and IEEE standards. Furthermore, the analyst captured major Artificial Intelligence laws in Europe, the UK, and the US.

In the sixth & seventh section, the analyst mentioned the most striking future trends of Artificial Intelligence, which will transform the Financial Services Sector. The analyst then looks at the leading Artificial Intelligence solution providers for the implementation of Artificial Intelligence in the financial services sector.

Companies Mentioned

  • Aeye

  • AIBrain

  • AlphaSense

  • Amazon

  • Anki

  • AppZen

  • AXA Life Insurance

  • Basler Versicherungen

  • Bank of America

  • Blue River Tech

  • BNP Paribas

  • Casetext

  • Credit Karma

  • CitiBank

  • Clarifai

  • CloudMinds

  • CognitiveScale

  • DataRobot

  • DataVisor

  • Deepmind

  • Freenome

  • Goldman Sachs

  • Google

  • Graphcore

  • H2O

  • HiSilicon

  • IBM

  • iCarbonX

  • I Know First

  • ING

  • IntelIris AI

  • JPMorgan Chase

  • LendingClub's

  • Lloyds Banking Group

  • Lobster

  • Man AHL

  • MetroMile

  • Microsoft

  • Narrative Science

  • Nauto

  • Neurala

  • Next IT

  • Nvidia Corporation

  • Numerai

  • Omron Adept Technologies

  • OneModel

  • OpenAI

  • Orbital Insight

  • PayPal's

  • Phrasee

  • PNB MetLife

  • Pointr

  • Qualcomm

  • RBC Capital Markets

  • Salesforce

  • SenSat

  • Sherpa

  • Siemens

  • Sift Science

  • Tamr

  • Tempus

  • Tencent

  • The Allstate Corporation

  • The Bank of New York Mellon

  • The Progressive Corporation

  • Twilio

  • UBS

  • Versicherungskammer Bayern

  • ViSenze

  • X.ai

  • Wells Fargo

  • Zebra Medical Vision

  • ZestFinance

  • Zurich UK

Key Topics Covered

1 Definitions of Artificial Intelligence
1.1 Artificial Intelligence in Financial Services
1.2 Artificial Intelligence Technologies
1.3 High-Level Artificial Intelligence Technologies Functions
1.4 Cognitive Computing: The Next Level of Intelligence
1.5 Artificial Intelligence Systems

2 State of the Industry (Adoption Statistics, any Emerging Patterns)
2.1 Key Market Drivers
2.2 Key Market Restraints
2.3 Surveys
2.4 Artificial Intelligence in Traditional Banking
2.5 Artificial Intelligence in Insurance
2.6 Artificial Intelligence in Fintech
2.7 Artificial Intelligence in Asset Management/Investment Banking

3 Framework/Considerations for Use/Evaluation and Implementation
3.1 Artificial Intelligence Framework
3.2 Key Considerations for Building a Responsible AI Framework
3.3 The Challenges of AI
3.4 Artificial Intelligence Development Team
3.5 R & D Strategy for AI Systems Development
3.6 Evaluation

4 Artificial Intelligence Standards
4.1 ISO Standards
4.2 IEEE Standards

5 Artificial Intelligence and the Law
5.1 EU Region
5.2 UK Region
5.3 US Region

6 The Future of Artificial Intelligence

7 Leading Companies Providing Artificial Intelligence Services

Annexure
Annex 1: A Brief History of Artificial Intelligence
Annex 2: List of Sources

Table of Exhibits
1. Elements of AI
2. Artificial Intelligence in Financial Services
3. Artificial Intelligence Technologies
4. Cognitive Computing: The Next Level of Intelligence
5. Framework of Artificial Intelligence Framework
6. AI Framework for Anti-Money Laundering (AML) and Financial Fraud Detection
7. AI Framework for Banking Transactions
8. AI Framework for Loan Automation
9. AI Framework for Online Mobile Banking Fraud Detection
10. AI Framework for Portfolio Management
11. Boston Consulting Group (BCG) - Share of Active Players in AI by Country & Industry
12. AI Adoption & Use Survey
13. The adoption rate of Artificial Intelligence by Industry
14. Artificial Intelligence Projected Revenue
15. Projected AI spending by Industry, 2021
16. AI investment and ROI: Relative landscape of industries
17. Forecast of Global AI-Derived Business Value
18. The Impact of AI on Industry Growth
19. The Impact of AI on Profit by Industry
20. Stages of AI implementation
21. Understanding the Investment into AI in Banking, 2017
22. Digital Banking Report, 2017
23. Most Impactful Trends in the Fintech Industry
24. Artificial Intelligence in Traditional Banking
25. Artificial Intelligence in Asset Management/Investment Banking
26. Artificial Intelligence Framework
27. Sample of an artificial intelligence system framework
28. Key Considerations for Building a Responsible AI Framework
29. The Challenges of AI
30. Artificial Intelligence Development Team
31. R&D Strategy for AI Systems Development

For more information about this report visit https://www.researchandmarkets.com/r/vhfwpr

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