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AI IN THE FINANCIAL SECTOR
- 1. ARTIFICIAL INTELLIGENCEIN THE FINANCIAL SECTOR Azeem Azhar, VP Venture & Foresight Schibsted Media Group @azeem http://azeem.io/s
- 2. Only three ways for humans to get smarter Evolution Genetic engineering Artificial intelligence Inspired by Doug Lenat
- 3. 3 Across the uncanny valley
- 4. AI is an umbrella term AI Machine learning Deep learning NLP Predictive analytics Rule-based systems
- 5. The BLUF Better, cheaper predictions Risk management, trading, advising, KYC, credit assessments Automation of human tasks Customer service, advice, interfaces, back office process Product innovation New products and markets will open up WHAT NEW SOURCE OF ALPHA Judgment Experience, intimacy Agility or monopoly
- 6. Algorithmic improvement DQN DDQN PRIORITISED DUELLING IMPROVEMENT OVER 12 MONTHS Miles Brundage
- 7. Better at video games 7
- 8. Good as human: captioning 8 Complex Tasks: Image Caption Generation http://arxiv.org/abs/1411.4555 “Show and Tell: A Neural Image Caption Generator”
- 10. Major global internet companies release internal machine learning & AI frameworks G, M, A & F: High level MLaas & AIaas Majors move into open source
- 11. 11 Can I compete? AI favours the large $$$$ training cost Improves with scale (data, layers, parameters) Hiring the right talent
- 12. Artificial Intelligence Explodes: New Deal Activity Record For AI Startups
- 13. The AI lock-in loop Inspired by Barney Pell
- 14. FinTech is booming with UK in the lead
- 15. This isn’t new
- 16. 41 startups bringing artificial intelligence to Fintech
- 17. In Q3 2016 VC-backed finch companies raised $2.4B across 178 deals Overall fintech investment reached $2.9B
- 18. BENEFITS Faster actions and decisions (e.g. for fraud detection) Better outcomes (e.g. for portfolio optimisation) Greater efficiency (i.e. better use of highly skilled people or expensive equipment) Lower costs (e.g. reducing labour costs with automated telephone customer service) Greater scale (i.e. performing large-scale tasks impractical to perform manually) Product and service innovation (from adding new features to creating entirely new products)
- 20. “I suspect that it’s going to transform all aspects of the financial industry” Andrew Lo, Director of the Laboratory for Financial Engineering at the MIT Sloan School of Management Euromoney Institutional Investor Thought Leadership survey of 424 senior executives from financial institutions around the world
- 21. Within 15 years, 68%expect to see complete or substantial change to their own jobs. 4/10 fear it will have a negative effect on the structure of the workforce sooner – within the next three years. Euromoney Institutional Investor Thought Leadership survey of 424 senior executives from financial institutions around the world
- 22. LOAN ASSESSMENT RISK MANAGEMENT UP SELL/CROSS SELL FRAUD DETECTION TRADING KYC/AML USE CASES
- 23. Algorithmic trading systems now handle 75 % of the volume of global trades worldwide TRADING
- 24. “In five to ten years, half of all financial advisors will be gone” Ric Edelman, Edelman Financial Services, top financial advisor in US
- 25. Identifies and executes trades entirely on its own AI that runs across on thousands of machines Uses evolutionary computation and deep learning Automatically recognizes changes in the market and adapts HEDGE FUNDS: AIDYIA
- 26. Numerai: collective artificial intelligence to make stock market predictions. Data scientists submitted over 12 billion equity price predictions in less than a year STOCK MARKET PREDICTIONS
- 27. BIOMETRIC BANKING SANTANDER: VOICE PRINT MASTERCARD: SELFIE ID HSBC: FINGERPRINT
- 28. Robots as customer service in retail banks
- 29. Human AI chat bots e.g. Cleo
- 30. Challenges - opportunity identification & ethical execution How to identify opportunities How to build capabilities & culture How to manage business model challenges How to deal with humans How to manage risk in the face of systemic cascades
- 31. @azeem Thank you. subscribe for weekly updates www.exponentialview.co