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Separating Hype from ROI: A Banking AI Deep-Dive

This presentation was given at BankAI 2019 in Chicago, and is based on data from our complete AI banking landscape report:
https://emerj.com/report/ai-in-banking-vendor-scorecard/

Learn from our best market research interviews on the Emerj AI in Banking podcast:
https://emerj.com/ai-in-banking-podcast/

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Separating Hype from ROI: A Banking AI Deep-Dive

  1. 1. Separating Hype from ROI: A Banking AI Deep Dive Daniel Faggella CEO at Emerj Artificial Intelligence Research
  2. 2. Presentation Outline ● Background in brief ● Research overview ● An overview of AI investments and banking AI initiatives ● (Takeaway 1 + 2) ● Vendor geo analysis ● An overview of AI claims and hype ● (Takeaway 3) ● /end
  3. 3. At Emerj, we have a singular focus: Mapping the applications of AI to help leaders execute on winning AI strategies. Global organizations trust us to support their AI goals and strategies with critical data and insight (World Bank, global healthcare firms, etc). Presenting our AI Research at United Nations HQ, NYC Emerj Artificial Intelligence Research
  4. 4. emerj.com @danfaggella Emerj Research Services
  5. 5. emerj.com @danfaggella
  6. 6. Research Overview ● 6 months of research ● ~80 AI in banking vendor companies ● ~50 AI use-cases within global banks ● 80+ pages of insight, graphs, analysis ● 48+ executive and researcher interviews ● Research advisors for this report include two AI PhDs, and AI experts, and leaders from:
  7. 7. What are the data, talent, and money requirements for the application? Ease of Deployment The particular ability granted to a business through the use of an AI technology or tool (Ex: Conversational interfaces) How credible is the ‘AI talent’ in a company? Expertise and Funding The business department or divisions into which the AI capability is being applied. Does this application deliver a financial return, or is it speculative? Evidence of Returns The kind of technical AI approach is behind the product offering (Ex: Natural language processing). AI Approach Capability Functions Type of BankingTT AI Vendor Segmentation What is the extent of real-world product adoption for each AI technology and vendor? Evidence of Adoption Ex: Retail banking, investment banking, commercial banking Type of Banking
  8. 8. emerj.com @danfaggella (Claimed AI initiatives of top banks)
  9. 9. emerj.com @danfaggella (Actual funds raised by banking AI vendor function)
  10. 10. ● Banking communications and press releases show conversational interfaces accounting for 38.87% of the AI use-cases at banks. ● Emerj's AI in Banking Vendor Scorecard and Capability Map found conversational interface vendors score lowest in terms of funding and the AI talent they employ (2.4 out of 4.0). ● Compliance, Risk Management, Fraud and Cybersecurity AI applications account for the vast majority of banking funds raised by AI startups, despite few claimed use-cases within banks. Misconception
  11. 11. ● There is nothing more hyped in the AI in banking landscape than chatbots. ● Chatbots are easy to deploy in a “sandbox”, and banks want to brag about customer-facing applications. ● This is what we call “The Lens of Incentives”: Enterprises talk about AI applications that make them look good in the eyes of their customers and investors, not the AI applications where they are actually investing in most. Takeaway 1:
  12. 12. ● The low-hanging fruit for near-term AI ROI in banking can be summed up as: Anomaly detection ● Finding stand-out patterns in a sea of noise is the perfect use-case for machine learning. Fraud, cybersecurity and compliance-related tasks fit this bill perfectly, and they are the best-funded AI functions in banking today. ● This is often the best place for a bank to begin an AI initiative, because IT teams, IT budgets, and existing automation initiatives are often strong within the compliance and fraud function. Takeaway 2:
  13. 13. ● 61% of AI vendors are in USA ● UK accounted for 15.5% ● Other countries nominal AI Vendor - Geo Analysis ● Of the $2.5 billion dollars raised by US banking AI vendors ● 56% raised by companies in CA emerj.com @danfaggella
  14. 14. emerj.com @danfaggella (Actual funds raised by banking AI vendor function)
  15. 15. AI Vendor - Geo Analysis emerj.com @danfaggella (Actual funds raised by banking AI vendor function)
  16. 16. ● Newer and smaller AI banking vendors are the most likely to exaggerate their AI claims. ● This is for two primary reasons: ○ Unestablished firms have less to lose by lying and exaggerating ○ Smaller firms with less experience drastically underestimate the barriers to AI adoption in banking ● Lesson: Unless you want to be a guinea pig, work with companies that have a track record and existing use-cases in banking (not in other sectors). Look for firms who have raised $30MM or more). Takeaway 3:
  17. 17. That’s All, Folks Free sample download: www.emerj.com/b1 Research inquiries: research@emerj.com

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