Why This Report Matters:
- Fortune 500s and venture capitalists are now pouring money into banking AI applications, providing an opportunity for banking firms to potentially get an edge in efficiency or effectiveness over industry giants like Wells Fargo, J.P. Morgan, etc
- Banks face major disruption from fintech innovators and technology giants – and AI will be critical for banks to leverage their strengths and their balance sheets to compete on efficiency and customer experience
- Knowing the full range of possible AI use-cases – and the requirements and ROI-potential of each – allows leaders to select areas of opportunity for near-term gain
What’s Included in This Market Research Report?
- Emerj AI Capability Map of over 70 AI banking vendor company applications (including Ayasdi, CognitiveScale, Aeri.io, and more)
- Vendor Overview and Ranking – Comparisons and scorecards for leading technology vendors serving the banking industry
- An analysis of over 45 internal AI use-cases of top banks in the US and Europe (including JPMorgan Chase, Bank of America, ING, and more)
- A ranking and filtering of AI use-cases based on our Emerj AI Vendor Scorecards, including:
- Evidence of ROI – Does this application deliver a financial return, or is it speculative?
- Ease of Deployment – What are the data, talent, and money requirements?
- Level of Adoption – How many banks purchased or piloted this application type?
- Survey responses, interviews, perspectives from dozens of banking business leaders and AI vendor company leaders
- Executive Insights – An overall analysis of the AI in banking landscape, and current trends across banking functions (Customer service, lending, fraud, etc)
- Top 5 Strategic Recommendations – Critical near-term action items for banking leaders looking to gain a competitive advantage with AI
- Business, marketing, and technology leaders in mid-sized and large banks
- Executives and product marketers at leading technology AI vendors serving the banking industry
- Investors in artificial intelligence, including venture capital and private equity firms
Critical Questions That This Report Answers:
- What artificial intelligence (AI) applications and use-cases are delivering ROI now for the banking industry at banks like HSBC and Lloyd’s Banking Group?
- How are back-end banking processes (lending, fraud) and front-end processes (customer service, sales) being transformed or automated at large companies today?
- Which AI applications will define the winners and the losers in the banking industry in the next 5 years?
- Who are the leading AI vendors serving the banking industry? What are the strengths, weaknesses and case implementations for each of these vendors?
Table of Contents:
|– Study Goals and Objectives||Review of the core value of the report|
|– Intended Audiences||Specific takeaways for different reader groups, including investors, banking technology leaders, and more|
|– Scope of Report||What is and is not included in terms of insights and information sources|
|– Methodology and Information Sources||Full listing of primary and secondary sources, and research process review|
|– Respondent Breakdown||Summary of respondent and vendor geo-locations, and implications for the report as a whole|
|– Analyst’s Credentials||Research background, areas of expertise|
|– Emerj Custom Research||Review of Emerj’s market research capabilities and service range|
|– Related Emerj Research Reports and Products||List of related reports and market research products|
|– AI Application||How are global banks like HSBC and Bank of America using AI applications today?|
|– AI Budgets and Resource Allocation||What budget and resources are being devoted to AI applications today?|
|– Challenges||What are the key challenges behind implementing AI in banking?|
|– AI Capability Map and Scorecards||A full breakdown of over 100 AI applications by broad capability areas|
|– Vendor Application Map||A full landscape of over 75 AI banking vendors across fraud, claims, and more|
|– Banking Company AI Adoption Map||A full landscape of over 45 representative use-cases within the largest global banks|
|Vendor Assessment – AI for Banking:|
|– Current ROI Index Analysis||Scoring AI vendors, applications and capabilities on current evidence of return on investment with existing applications|
|– Accessibility Index Analysis||Scoring AI vendors, applications and capabilities on the time, talent, and data requirements for the application|
|– Credibility Index Analysis||Scoring AI vendors, applications and capabilities based on the likelihood that these firms are lying about using AI in their solution|
|– Maturity Index Analysis||Scoring AI capabilities on penetration into the banking sector|
|– Decisiveness Index Analysis||Scoring AI capabilities on their likelihood of providing competitive advantages to adopters|
Daniel Faggella is the Founder and CEO at Emerj. Called upon by the United Nations, World Bank, INTERPOL, and many global enterprises, Daniel is a sought-after expert on the competitive strategy implications of AI for business and government leaders.
Raghav Bharadwaj serves as Finance Analyst at Emerj, covering banking, investing, and insurance. Raghav has previous research experience at recognized firms such as Frost & Sullivan and Infiniti Research.
Dr. Germán Sanchis-Trilles is Technical Advisor at Emerj, where he helps to assess and categorize AI applications and vendor firms. Germán received his PhD in computer science at the Universitat Politècnica de València, with a research focus in natural language processing.
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