Become a Client
Background Banking

Emerj AI in Banking Vendor Scorecard and Capability Map 2019

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,, 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 Returns – 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?
    • More…
  • 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

Intended Audience:

  • 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:

1. Executive Summary
2. Research Methodology

  • 2.1. Research Goals and Objectives
  • 2.2. Scope of the Report
  • 2.3. Methodology and Information Sources

3. Executive Insights

  • 3.1. Culture of Risk Aversion Hurts Banks’ Ability to Adopt AI
  • 3.2. Bankers Are Aware of AI’s Importance, But Can’t Capitalize
  • 3.3. Customer-Facing AI Will Separate Winners From Losers
  • 3.4. Job Displacement: a Near-Inevitable Reality

4. Analysis: The State of AI in Banking

  • 4.1. Phases of Innovation for AI in Banking
    • Phase 1: Today
      • Risk and Automation: AI Viewed as Just Another Part of IT Infrastructure
    • Phase 2: Near-Term Future (2-5 Years From Now)
      • Improving Efficiency: Banks Will Start Developing a Core Competency in Talent and Data Infrastructure
    • Phase 3: Long-Term Future (6-9 Years From Now)
      • Using AI Offensively: Banks Will Have Basic Data Competency and Can Apply AI to Increase Revenue
  • 4.2. How Bankers Should Assess AI Vendors
  • 4.3. Adoption Challenges
    • Lacking the Culture of Innovation Required to Truly Use AI
    • Data Is Hard to Access
    • ROI Uncertainty
  • 4.4. AI Opportunities Banks Can Capitalize On
    • Existing Data Streams
    • Existing Customer Relationships
    • Access to Capital and Assets

5. Vendor Landscape

  • 5.1. Banking Functions
  • 5.2. Emerj Scores
    • Vendor Scores
      • Expertise and Funding
      • Evidence of Adoption
    • Product Offering Scores
      • Evidence of ROI
      • Ease of Deployment
    • Product/Market Fit Score
    • Overall Score
  • 5.3 The Lens of Incentives
  • 5.4 Ease of Deployment Score Analysis
  • 5.5 Vendor Analysis by Function
    • Fraud and Cybersecurity
      • Vendor Profile: Expert System
      • Vendor Profile: Darktrace
    • Compliance
      • Vendor Profile: Digital Reasoning
      • Vendor Profile: Narrative Science
    • Financing and Loans
      • Vendor Profile: ZestFinance
      • Vendor Profile: Yodlee
    • Risk Management
      • Vendor Profile: Ayasdi
      • Vendor Profile: Kensho
    • Customer Service
      • Vendor Profile: Kasisto
      • Vendor Profile: Finn AI
    • Wealth Management
      • Vendor Profile: Cognitive Scale

6. Five Best Practices For AI ROI in Banking

  • 6.1. Develop Data Infrastructure
  • 6.2. Develop AI Talent and a Culture of Innovation
  • 6.3. Find The Best First-Adoption Areas For Your Bank
  • 6.4. Base Decisions on Priorities and Not On What is Being Hyped In The Press
  • 6.5. Internal Competence Before Customer Interactions

7. Appendix

  • 7.1. Analysts and Team
  • 7.2. Emerj Score Criteria
  • 7.3. Glossary of Terms

8. Emerj Custom Research


Emerj AI in Banking Vendor Scorecard and Capability Map 2019 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.
Emerj AI in Banking Vendor Scorecard and Capability Map 2019 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.
Emerj AI in Banking Vendor Scorecard and Capability Map 2019 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.

Research Advisors:

Emerj AI in Banking Vendor Scorecard and Capability Map 2019

Ian Wilson, former Head of AI at HSBC, presently runs an independent enterprise AI strategy advisory firm.

Emerj AI in Banking Vendor Scorecard and Capability Map 2019

Lee Smallwood is COO of Markets and Securities Services (North America) at Citi. Previously founder of fintech startup Gradible.

Emerj AI in Banking Vendor Scorecard and Capability Map 2019

Dr. Nishant Chandra is Senior Director of Data Products at VISA, and previously served as Data Science Leader at AIG.

BNK-CAP-1 Exec Summary Brief - Sample Image
Learn More, Download the Executive Summary Brief
Submit the form below and your executive summary brief will be sent to your by email:
Message Received

Thank you - your brief is being sent to you by email.

Phone: 1-617-945-8567