How Fintech is Reshaping Banking
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Presented on September 14, 2018 at the Taiwan Academy of Banking and Finance in Taipei.
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How Fintech is Reshaping Banking
- 1. How Fintech is reshaping banking
- 2. “I want to to go on Vacation" Can we fly using our points? Which destinations have non-stop flights or a promotion? Traveller ratings? Which payment method has the best ForEx rates? What’s my trip budget?
- 3. ”ALEXA: I Want to go on vacation”
- 4. FIVE TRENDS which are reshaping banking E-KYC MOBILE FIRST BIG Data machine Learning & AI CROSS-VERTICAL INTEGRATION
- 5. MORE IMPORTANT: HOW THEY ALL WORK TOGETHER IN THE FUTURE
- 6. For each trend, let’s talk about… Action Plan What is it? Examples
- 7. 1. E-KYC What is it? Electronic process in which a business identifies and verifies the identity of its clients. E-KYC procedures must have the same standards as the KYC procedures usually conducted where the relationship is established face-to-face. Example of E-KYC currently used: Biometrics (facial recognition), Voice control (Siri, Google Home), Finger Print.
- 8. 1. E-KYC Examples Facial Recognition VoiceFinger Print
- 9. 1. E-KYC Action Plan • Learn how APIs and biometrics work and know what is available. • Try yourself: every possible API and biometric option as a customer • Keep track of new technologies that are being tested so you're ready to implement. Watch other markets. • Engage with the regulatory sandbox to test new solutions
- 10. 2. Mobile First What is it? • It's not about the device, it's about the data! • Rethink the user experience for mobile https://www.vasco.com/solutions/banking-cyber-security/mobile-banking-security.html
- 11. 2. Mobile First Examples
- 12. 2. Mobile First Action Plan • Design for the smallest screen and work your way up. • Understand data privacy laws and play by the rules. • Test and use voice-activated, QR Code, and other biometric mobile options. • Learn about every data source which the phone generates. Geolocation, device data, etc.
- 13. 3. Big Data Structured Data Unstructured Data +Credit Bureau Data Loan Payment History Credit Card Transactions Accounting Records What is it? Location data Search history Social posting Video viewing habits Natural Language
- 15. 3. Big Data Starbucks Rewards 13 million customers 17 million App active users USING INFORMATION TO OPEN STORES AND CONVERT CUSTOMERS FROM DISLOYAL TO LOYAL Identify and link the customers with the products Identify and analyse traffic data Test and roll out targeted data-driven initiatives 11 major KPI for manager Better understanding the purchasing behaviour Targeted advertising and discounts Examples
- 16. 3. Big Data Action Plan Ensure you get a return on your investment (ROI) through A/B testing: - Tailored discounts, Promotions and Coupons - Relevant Loyalty offers Reconsider which analytics and data visualization tools you should use. For example, we see a shift in banks from SAS to R. Stop yourself from over-using the excel graph buttons. You need to "up your game" with a data visualization approach.
- 17. 4. Machine learning & AI What is it? Machine Learning Artificial Intelligence Expert System s A U TO N O M O U S “HUMAN-LIKE” Diagnostics Decision Automation and Prediction Human Surrogate Rule Automation Customer Segmentation Game AI Recommendation Engines Identity & Fraud Detection Playing Go Market forecasting News generation Chat bots Personal Assistants “Hey Siri” Self driving car Drug interactions RULES & INTERFACE
- 18. 4. Machine learning & AI Value of big data to finance: observations on an internet credit Service Company in China https://jfin-swufe.springeropen.com/articles/10.1186/s40854-015-0017-2 Examples
- 19. 4. Machine learning & AI RISK MODELSFRAUD MODELSMARKETING MODELS Better segment scoring Supplement existing scorecard approaches Prevention: Real-time analysis of transaction with immediate fraud score and rejection Detection: Identifying unusual transactions of customers and taking steps to block further fraud attempts. Online: recommend effective online content based on factors such as risk profiles and geographic region. Targeting: Automated search for audience by AI (search sites that match the desired target market and ad content). Examples
- 20. 4. Machine learning & AI Examples Marketing emails Track Wildlife Reduce customer’s home energy consumption Co-working with Google home Get market information To trial an AI-powered chatbot on the 111 non-emergency helpline Pre-packaged machine learning algorithms Its core services built on machine learning Luvo: Natural language processing AI bot
- 21. 4. Machine learning & AI Action Plan • Start with descriptive statistics & graphics • Look to other industries for examples and inspiration • AI is a cool buzz word, but "stay in your lane" with Machine Learning most of the time
- 22. 4. Cross-vertical integration What is it?
- 23. 4. Cross-vertical integration Examples
- 24. 4. Cross-vertical integration Action Plan • Think outside the box; a FinTech career step might be in e- commerce or in marketing due to rich exposure to data • Test out every app you can; shopping, transport, travel, and know how they work. • Build corporate partnerships which are are data gold mines • Watch consumer, e-commerce and marketing trends; now they more easily integrate into retail banking and wealth management
- 25. Now, back to ALEXA E-KYC MOBILE FIRST BIG Data ML & AI CROSS-VERTICAL • Biometrics: Fingerprint, voiceprint, scan ID • Mobile as the gateway to voice activated user experience • Omni channel interaction drives user experience and data capture • Cross-vertical integaration brings the volume and velocity of data which is required • Once you have big data, by definition, you must process it with ML and AI • Back to the mobile and voice activated device, your intelligence is now actionable.
- 26. "Alexa, I want to to go on Vacation"
- 27. Alexa says: “One option is to go to Bangkok next month: • You have enough miles on Eva air for your ticket. • The AirBnB which you rated highly has availability. • Your credit card has enough spending limit. • You can travel over the public holiday weekend, taking one day of annual leave for the four day trip.” You say, “But Alexa I wanted to go to the beach!” Alexa reponds… “The weather next month at the beaches in Thailand will be very hot. • If you wait two months, you can use your air miles to go to Krabi, when the weather is better. • You haven’t been to Krabi in the past, so I suggest three choices based on your past accomodation ratings and reviews.”
- 29. Contact Michelle Katics CEO, PortfolioQuest & BankersLab michelle@portfolio-quest.com +65 86503580 www.FinTalent.com
- 30. Thank You