FinTech 15.S08.02. Deep Learning

Required Readings

1. ‘Artificial intelligence and machine learning in financial services’ Financial Stability Board (November 1, 2017) (Pages 3–23, Executive Summary & Sections 1–3)
2. ‘The Growing Impact of AI in Financial Services: Six Examples’ Arthur Bachinskiy, Medium (February 21 2019)

Questions

1. What are artificial intelligence, machine learning, and deep learning? How do these enhanced tools of pattern recognition and decision making relate to financial services?
2. What is natural language possessing? How has it already enhanced user interfaces (UI) and user experiences (UX) in finance? How might chatbots, conversational interfaces and voice assistants transform UI & UX in the future?
3. What sectors within the financial services sector has seen the most adoption of AI & machine learning? How can it be used to enhance compliance systems, customer interfaces, risk management, underwriting and investment strategies?

Big data is a term for which there is no single, consistent definition, but the term is used broadly to describe the storage and analysis of large and/or complicated data sets using a variety of techniques including AI. 

Machine learning may be defined as a method of designing a sequence of actions to solve a problem, known as algorithms, which optimise automatically through experience and with limited or no human intervention.

Overview

• AI, Machine Learning, & Deep Learning
• Natural Language Processing
• AI within FinTech History
• AI & Machine Learning – Finance
• Natural Language Processing - Finance

Alternative Data

• Bank, Checking, Employment, Income, Insurance, Tenant, Utilities
• Cash Flow Underwriting
• Consumption and Purchase Transactional Data
• App Usage, Browsing History, Email Receipt, Geolocation, Social Media Data,
• Educational Background, Employer, Occupation, Work History

Natural Language Possessing

• Computer Input, Interpretation and Output of Human Language
• Natural Language Understanding and Natural Language Generation
• Audio, Image, Text and Video including Spoken, Written or Gestured
• Content Generation, Content Summarization, Information Retrieval, Intent Parsing, Sentiment Analysis, Speech Generation, Speech, Recognition and Translation
• Chatbots, Conversational Interfaces and Voice Assistants

Natural Language Possessing - Finance

• Customer Services
• Chatbots, Conversational Interfaces and Voice Assistants
• Process Automation
• Sentiment Analysis

FinTech 15.S08.01. Technological Trends

Trends:

1. AI
2. Open banking
3. Blockchain

Intermediates Money and Risk

Data

• Investing, Market Making, Marketing, Risk Management & Underwriting

Funding & Risk Management

• Balance Sheet & Capital
• Marketplace & Securitizations
• Derivatives, Guarantees & Reinsurance

Risks

• Credit; Funding; Liquidity; Market (Basis, Price, Rate, Spread, Volatility)
• Model; Operational; Reputational / Compliance
• Accidents; Health; Life Events; Natural Disasters; Weather

User Experience & User Interface

FinTech - Finance’s Fertile Ground

• Digitalization of Money, Securities and Credit

• Vast and Expanding Amounts of Customer Data

• Rapid Expansion of Computational & Analytical Power

• Reliance on Multiple Systems of Ledgers

• Wide Public Acceptance of New Tech

• Legacy Customer Interface and Processing Systems

• Infrastructure Systems’ Costs and Counterparty Risks

• Economic Rents and Centralized Concentrated Risks

 FinTech – Disruptive Potential

• AI for Managing Risks & Targeting Products

• Updated Customer User Interface and Robo Advice

• Greater Financial Inclusion & Tailored Services

• ‘Internet of Value’: Movement of Value & Micro Payments

• Streamlined Accounting, Clearing, Compliance & Processing Systems

• Some Revenue Models shift to Data in exchange for Free Services

• Efficiencies & Tighter Margins in Financial Sector 

AI and Machine Learning - Finance

• Asset Management

• Call Centers, Chatbots, Robo-Advising & Virtual Assistants

• Credit (& Insurance) Allocation, Extension, Pricing & Scoring

• Fraud Detection & Prevention

• Regulatory – Anti Money Laundering, Anti Manipulation

• Risk Management & Underwriting

• Robotic Process Automation

• Trading 

Open API & Open Banking

• Open Application Program Interfaces (Open API) allow outside Developers access to and an ability to Integrate Permissioned Customer Data into Third Party Applications

• Open Banking initiatives facilitate or mandate Open API for Non-banks to Share Permissioned Bank Customer Data

• Policy Trade-offs of Promoting Competition & Innovation, Limiting Cybersecurity Risks, and Maintaining Privacy & Consumer Protections

• EU Payment System Directive (PSD2), UK Open Banking Initiative, etc.

• Plus Screen Scraping, Reverse Engineering & Robotic Process Automation

Blockchain Tech Potential Uses

• Speculative Investing

• Crowdfunding through Initial Coin Offerings

• Tokens for Exchanges, Gaming, Gambling, DeFi & File Sharing

• Tokenized Fiat (Stable Value Coins), Securities & Assets

• Payment Systems

• Trade Finance & Supply Chain Management

• Clearing, Settlement & Processing

• Central Bank Digital Currencies & Payment Initiatives

• Digital ID & MIT Diploma

• Medical Records, Property Records, Internet of Things, Voting … 

FinTech – The Actors

• Big Finance: Like Fortresses w/ Moats, Towers & Sovereign Affiliations

• Towers: 1) Payments, 2) Balance Sheets, 3) Data, 4) Corporate Structure

• Big Tech DNA Loop (BIS): 1) Data, 2) Networks, 3) Activities

• Start-ups: 1) Disruptive Innovators, 2) Flexibility, 3) Asymmetric Risk Takers

• Official Sector: Goals: 1) Innovation, 2) Inclusion, 3) Financial Stability, 4) Investor &        Consumer Protection & 5) Guarding against Illicit Activities 

Study Questions:

• What are the major technological trends materially influencing the provision of financial services?
• How is the competitive landscape shaping adoption of these new technologies around the globe?
• How are FinTech start-ups and Big Tech firms competing and cooperating with incumbents from big finance? How has Big Finance reacted?
• What do you wish to achieve in this Fintech course?