Financial Services


Automation, AI are upending jobs at Canada's big banks

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A customer uses a teller at the redesigned TD Bank branch inside the TD Centre in downtown Toronto. Technology advances are upending tens of thousands of jobs across the global financial sector, including at Canada's big banks. As global banks unveiled plans to slash tens of thousands of jobs this year, those in Canada held staffing levels fairly steady. But that doesn't mean this country has been immune to the forces of automation and artificial intelligence that are reshaping banking around the world. Beneath the surface, there are tectonic shifts under way in the nature of work and the kinds of skills Canada's banks need.


Artificial intelligence can improve sales by four times compared to some human employees

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CATONSVILLE, MD, September 23, 2019 - Chatbots, which use artificial intelligence to simulate human conversation through voice commands or text chats, incur almost zero marginal costs and can outsell some human employees by four times, so why aren't they used more often? According to new research, the main contributor is customer pushback. The machines don't have "bad days" and never get frustrated or tired like humans, and they can save money for consumers, but new research in the INFORMS journal Marketing Science says if customers know about the chatbot before purchasing, sales rates decline by more than 79.7%. The study authors, Xueming Luo and Siliang Tong (both of Temple University), Zheng Fang of Sichuan University, and Zhe Qu of Fudan University, targeted 6,000 customers from a financial services company. They were randomly assigned to either humans or chatbots, and disclosure of the bots varied from not telling the consumer at all, to telling them at the beginning of the conversation or after the conversation, or telling them after they'd purchased something.


The FCA and the Bank of England find that two-thirds of UK banks and financial service firms use machine learning

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Machine learning technology is poised to be huge thing in financial services. In fact, two-thirds of UK-based firms are already using it. That is according to two of the UK's top financial regulators. The Financial Conduct Authority (FCA) and the Bank of England have taken a deep dive into how the financial services industry in the country is using machine learning. The research is based on a survey sent out to 300 firms, including banks, credit brokers, e-money institutions, financial market infrastructure firms, investment managers, insurers, non-bank lenders and principal trading firms.


Personetics' AI-Powered Engagement Platform for Small and Medium Businesses Adopted By Leading Banks

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Personetics is the leading provider of customer-facing AI solutions for financial services and the company behind the industry's first Self-Driving Finance platform. Harnessing the power of AI, Personetics' Self-Driving Finance solutions are used by the world's largest financial institutions to transform digital banking into the center of the customer's financial life – providing real-time personalized insight and advice, automating financial decisions, and simplifying day-to-day money management. Serving over 65 million bank customers worldwide, Personetics has the largest direct customer impact of any AI solution provider in banking today. Personetics customers include 6 of the top 12 banks in North America and Europe and other leading banks throughout the world. Led by a team of seasoned FinTech entrepreneurs with a proven track record, Personetics is a rapidly growing company with offices in New York, London, Paris, Singapore, and Tel Aviv.


AI or Die: 4 Ways Model Governance Can Help You Win at Digital Transformation - Banking Exchange

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We've all heard it before: "Win or go home." Whether in business or on the playing field, the pressure to win is intense. And in today's financial services industry, the winner can literally take all. As banks struggle to adapt in the throes of digital disruption, executives find themselves squeezed to use artificial intelligence (AI) or machine learning (ML) models to power their digital transformation initiatives forward. The industry's use of computational finance models to make decisions is nothing new.


How artificial intelligence makes financial services institutions more efficient

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The financial landscape has been rapidly evolving with the rise of financial technology (fintech) companies and startups that are more agile and technologically advanced. This has led financial services institutions (FSIs) to revise their business models and evaluate how they can integrate technology into their operations. Robotic process automation (RPA) is no longer a foreign term in the financial field. Pairing RPA with artificial intelligence (AI) creates intelligent process automation (IPA) that works as a catalyst in digital transformation in FSIs. Like many other industries, the financial field is heavily reliant on documents and legacy systems.


Kaleidofin: Can a disruptive fin-tech company create a mass-market for savings and investment in India?

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This article was first published on the Impact Money Blog. The Impact Money Blog sat down with Puneet Gupta to find out why he left Dvara Trust (formerly known as IFMR Trust), a group he co-founded in 2007, to start Kaleidofin, an ambitious fintech company that wants to make savings and investment convenient for millions of customers at the base of the economic pyramid. Puneet Gupta, a veteran social entrepreneur in the field of microfinance, knows the poor would be better off saving rather than borrowing to achieve their financial goals. Although microfinance has been credited with improving the lives of hundreds of millions of people in the developing world, the industry has grappled with the ethics of indebting the most economically vulnerable. This is particularly true in India, which experienced a regulatory backlash over this issue in 2010 that threw the industry into turmoil.


Machine learning mostly used to fight fraud among UK financial firms

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Machine learning technology is poised to be huge thing in financial services. In fact, two-thirds of UK-based firms are already using it. That is according to two of the UK's top financial regulators. The Financial Conduct Authority (FCA) and the Bank of England have taken a deep dive into how the financial services industry in the country is using machine learning. The research is based on a survey sent out to 300 firms, including banks, credit brokers, e-money institutions, financial market infrastructure firms, investment managers, insurers, non-bank lenders and principal trading firms.


Machine learning in UK financial services

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In the financial services industry, the application of machine learning (ML) methods has the potential to improve outcomes for both businesses and consumers. In recent years, improved software and hardware as well as increasing volumes of data have accelerated the pace of ML development. The UK financial sector is beginning to take advantage of this. The promise of ML is to make financial services and markets more efficient, accessible and tailored to consumer needs. At the same time, existing risks may be amplified if governance and controls do not keep pace with technological developments.


AI: Understanding bias and opportunities in financial services

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It is undeniable that our lives have been made better by artificial intelligence (AI). AI technology allow us to get almost anything, anytime, anywhere in the world at the click of a button; prevent disease epidemics and keep them from spiralling out of control, and generally just make day-to-day life a bit easier by helping us to save energy, book a babysitter, manage our cash and our health all at a very low cost. AI's penetration into systems and processes in virtually all sectors of business and life has been rapid and global. The speed and scale at which AI is proliferating does however raise the question of how at-risk we may be that the AI we are building for good can also be introducing damaging bias at scale. In this two-part series, I explore the issues with AI constructs, the good bad and the ugly and how we can think about shaping a future through AI in financial services that helps lift people up rather than scaling problems up.