Welcome to FINTECH Circle's AI Webinar Series focused on artificial intelligence and the future of AI in finance. As part of FINTECH Circle's book range we have released The AI Book, published by Wiley in June 2020. In this webinar FINTECH Circle's CEO Susanne Chishti will be joined by leading AI experts from Moody's to discuss how AI and innovative technologies empower ESG goals and which innovative finance tools are available to benefit small and large corporations. The webinar will focus on: - How can AI, Fintech and related technologies enhance ESG data, processes, frameworks and governance - Where are opportunities for ESG data and tools innovation alongside industry 4.0 - What's Moody's role in developing AI and Fintech innovation Our invited guests are: - Martina Macpherson, Senior Vice President, ESG & Engagement Strategy, Moody's - James Henley, Associate Managing Director, Moody's Investors Service - Ashit Talukder, Head of AI/ML, Moody's We look forward to having you join us for an inspirational conversation!

Following the publication of best-selling titles, The FINTECH Book, The INSURTECH Book, The WEALTHTECH Book and The PAYTECH Book, we are pleased to announce the release of the latest instalment in the series: The AI Book. The AI Book is the result of globally crowdsourcing the most cutting-edge artificial intelligence knowledge, led by FINTECH Circle. After the initial call for potential co-authors of the book was released and shared across the wider fintech community, 170 potential contributors submitted proposals with a diverse range of industry expertise. After shortlisting writers, these successful AI entrepreneurs, fintech professionals, thought leaders and investors went on to write chapters for The AI Book, the latest edition of The FINTECH Book Series published by WILEY. Susanne Chishti, the CEO and Founder of FINTECH Circle, selected three AI and technology leaders to join her on the editorial side – a powerful all-women team consisting of Ivana Bartoletti (Technical Director at Deloitte, author and Co-founder of the Women Leading in AI network), Anne Leslie (Senior Managing Consultant at IBM), and Shân M. Millie (Founder at Bright Blue Hare, Founding Associate of London Market Growth and Business Performance Specialists at GreenKite).

Finance may well be a test for the trust consumers place in Artificial Intelligence. Data is essential for the AI industry to flourish but what steps do financial services need to take to ensure customers trust the sector to innovate through AI? And what is the tradeoff between consumer benefits and privacy? E-commerce, PSD2 and the rapid increase of smartphone ownership mean consumers demand efficient services alongside strong security and privacy protections. This chapter will focus on the key issues of transparency and trust, and will outline what digital ethics mean for the financial sector.

Cultural adaptation is the step zero of digital transformation. Encouraging an entrepreneurial spirit by dedicating internal groups to find digital solutions has become the new normal for financial institutions. Banks are striving to become technology companies by automating back office work flows and increasing customer satisfaction with low friction interfaces and lower cost services. Incumbent intrepreneurs look to transformation trends that will keep banks future proofed while challengers and tech giants move in on a fintech market where banks have lost a quarter of the payments franchise to new players. Data has fuelled the growth of fintech with open banking starting to take a lead role in developing game changers such as AI and cloud.

The use of Artificial Intelligence (AI) in the areas of predicting legal and judiciary decisions based on criteria such as penal codes, state laws and legal precedent is rapidly evolving. Predictions that legal case management software will be using AI techniques for case-based reasoning are increasingly prominent. AI Deep Learning Platforms used in legal practices will have capabilities to carry out client management and updates as well as legal service alerts management. Platforms will allow lawyers to monitor the progress of matters, resource commitments, and budget status in real time on a case-by-case basis. For lawyers, it may provide a gateway to access firm's prior workflows.

The convergence of three emergent technologies: Intelligent Learning Systems (AI, ML), Quantum Computing (QC) and Distributed Ledgers (DLT) will likely have a transforming impact on our society and shape the future of Information Technology. What will be the direction of future AI, ML technology initiatives in the financial industry, in a broad spectrum of research, development & commercialisation efforts for ML, AI and DLT in the quantum domain? As an example, quantum computing is finding a vital application in providing speed-ups in ML, critical in our "big data" world. This will have a profound impact on Investment Portfolio Management, High Frequency Trading, Loan Origination and processing, Fraud Detection, Risk Modelling and calculating credit ratings. Future use cases that can leverage these three technologies include a secure and transparent distributed personal financial data (PII) marketplace, and a secondary mortgage platform with a tokenised exchange combining DLT, post-QC cryptographic algorithms and deep learning technologies.

One of the most significant sources of income in retail banking comes from lending, but that does not come without risk and time-consuming activities. In traditional retail banking specific processes need to be followed to make sure new business is acquired at acceptable risks levels set by each organization. Starting with the Financial Services Representative, passing to the underwriter, and ending in retail operations, all stakeholders play a critical role in getting a new deal mitigating risks. AI – Artificial Intelligence – could help not only to streamline this process but also to help gather crucial information in case no historical credit information is found. AI can highly increase successful lending in sales and from a credit management perspective by correlating a number of different indicators from account transactions, bill payments regularity, the average time between deposits and withdraws, variance and trend on month-end balances, along with behaviour from good or defaulted credit clients.

Artificial Intelligence is becoming more commonly used in a variety of fintech applications. Our infographic highlights how often a financial services customer can interact with A.I. during everyday routines. It is possible to encounter artificial intelligence in numerous ways while carrying out single tasks, such as using predictive text while talking to a virtual assistant that understands requests and connects with other third party platforms. While customers and employees enjoy increased convenience A.I. is also enabling bank grade security to protect our digital identities and finances. To access secure accounts many organisations apply 2 factor logins using a password, pin or device with biometrics such as voice and facial recognition.

There have been amazing leaps in AI technology within the Fintech sector over the past few decades. Early evidence on this came in 1960's when research was largely focused on Bayesian statistics to predict, audit stock markets, to 1980's-90's when Expert Systems were commercialised. Today, firms are building AI-powered products in order to generate cognitive investment insights, for those who want to participate in the market and take control of their finances, without walking into a branch or contacting an agent. In banking, financial services and insurance (BFSI), an industry overwhelmingly saturated with competition, customer service is one true key differentiator. From voice-based interactions to virtual agents, robo-advisory and intelligent portfolio management for smart decision making are some of the challenges the industry is tackling to not only help customers better manage their money, but also innovate in the process to enable firms for revenue growth and employment.

The traditional insurance business model is going to fundamentally and permanently change from what was invented in the Lloyd's coffee shop in 1668 and which has been the basis of insurance ever since: Risk Mitigation via Indemnity and minimising interactions with customers. The next 10 years will see unprecedented change in the insurance industry. Traditional insurance companies selling and servicing the old style product model are being replaced by IT enabled, risk management companies selling profitable, long term contracts for valuable services delivered as RMAAS (risk management as a service). The experience of other industries offers a stark warning to the insurance industry: banks suffering death by a thousand cuts from tech companies in payments, cards, lending and now open banking, show the way it will go. Even software is sprinting to a cloud based, software as a service (SAAS) model.