Know about the Future of Artificial Intelligence in Banking industry in detail in new Research

The Future of Artificial Intelligence in Banking", report examines the most significant uses of AI in retail banking, in both front-office and back-office implementations. Artificial intelligence (AI) has reached the stage where it is sufficiently advanced and affordable to warrant practical implementation in financial services. Banks are busy exploring ways in which they can harness the power of AI to streamline internal processes and improve the customer experience. This report will explore what AI applications are relevant in banking at this time, examine where AI is already making an impact, and offer recommendations on how banks should proceed.
The report offers insight into -
The particular manifestations of AI that have the most relevance for banking.
How leading banks are already implanting AI-based solutions.
The factors banks need to address when introducing AI applications.

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AI encompasses a wide range of technologies, including robotic process automation, natural language processing, advanced data analytics, and image analytics. Use of these technologies will help banks improve both front-office and back-office processes. Customer-facing uses of AI include chatbots that improve communication between banks and their customers, advanced analytics that can offer proactive advice to consumers and take simple financial decisions on their behalf, and facial recognition that improves onboarding and makes it easier for consumers to log into their accounts. Back-office AI implementations include algorithms that can identify and block cases of fraud and money laundering, and analysis of non-traditional data to assess the creditworthiness of borrowers who lack standard credit records. The reports have also focused on the markets restraint facts which can actually slow down the demand of global Artificial Intelligence in Banking market and hamper the regional economy. Whereas, the opportunity for its future growth is also mentioned for the customers so that they can easily understand the market scenario.

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In the end, the report includes global Artificial Intelligence in Banking new project SWOT analysis, investment feasibility analysis, investment return analysis, and development analysis. The report also presents a round-up of vulnerabilities which companies operating in the market must avoid in order to enjoy sustainable growth through the course of the forecast period.
Table of Contents
EXECUTIVE SUMMARY
Market summary
Key findings
Critical success factors
AI WILL TRANSFORM RETAIL BANKING
What is AI?
What impact will AI have on banks?
Which AI applications are relevant for banking?
RPA
NLP
Advanced data analytics
Image analytics
ML and deep learning
AI WILL IMPACT BANKING IN SEVERAL WAYS
Customer-facing implementations
Chatbots and virtual assistants
PFM
Identity verification using biometric data or document scanning
Back-office implementations
Anti-money laundering and fraud detection
Underwriting and credit assessment
RECOMMENDATIONS FOR IMPLEMENTING AI
Improve data quality
Partner with fintech specialists
Plan for potential execution risks
Malfunctions and lack of efficacy
Algorithm bias
Lack of transparency
Data privacy issues
APPENDIX
Abbreviations and acronyms
Bibliography
Further reading

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