DUBLIN--(BUSINESS WIRE)--The "The Future of Artificial Intelligence in Banking" report has been added to Research and Markets' offering.
The report "The Future of Artificial Intelligence in Banking" examines the most significant uses of AI in retail banking, in both front-office and back-office implementations.
Several aspects of banking are ripe for AI-driven intervention. Many of their data-driven back-office processes are high volume and repetitive in nature, and hence are ideal candidates for intelligent automation. At the front end, with the majority of customer interactions occurring through digital channels, there is also considerable scope for AI to improve the quality of and add value to the user experience.
Key findings include in this report:
- AI encompasses a wide range of technologies, including robotic process automation (RPA), natural language processing (NLP), 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.
Critical success factors
- Improve data quality: AI algorithms depend on access to high quality data to work effectively. Banks must move away from siloed and fragmented databases towards a single view of their customers. This will give the algorithms access to enough data to make effective decisions.
- Collaborate with AI specialists: AI is an incredibly complex field, and banks are best advised to partner with AI specialists. This will enable them to launch AI-based services quicker and cheaper than if they were to develop solutions in-house.
- Address potential execution risks:Banks need to be aware of the possible pitfalls of using AI, such as algorithm bias, a lack of transparency around decision-making, and concerns with data privacy. Steps should be taken to minimize these risks.
Key Topics Covered:
1. EXECUTIVE SUMMARY
1.1. Market summary
1.2. Key findings
1.3. Critical success factors
2. AI WILL TRANSFORM RETAIL BANKING
2.1. What is AI?
2.2. What impact will AI have on banks?
2.3. Which AI applications are relevant for banking?
3. AI WILL IMPACT BANKING IN SEVERAL WAYS
3.1. Customer-facing implementations
3.2. Back-office implementations
4. RECOMMENDATIONS FOR IMPLEMENTING AI
4.1. Improve data quality
4.2. Partner with fintech specialists
4.3. Plan for potential execution risks
- Atom Bank
- Bank of America
- Moneyhub Enterprise
- Starling Bank
For more information about this report visit https://www.researchandmarkets.com/research/f5v6nw/the_future_of