Wealth management in an era of robots, regulation, and new money

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By redirecting focus, wealth managers can successfully respond to challenges brought on by digital disruption, demographic shifts, and tighter regulation. Wealth managers have seen their fair share of ups and downs in recent years, and while challenges remain, advisers can drive business and growth by paying attention to demographic segmentation, how investors are using technology, and changes in regulation. In this episode of the McKinsey Podcast, Simon London first speaks with PriceMetrix chief customer officer Patrick Kennedy and McKinsey partner Jill Zucker about the North American wealth-management industry; he follows that with a discussion with senior partner Joe Ngai, on the industry in China. Simon London: Welcome to the McKinsey Podcast with me, Simon London. Today, we're going to be talking about financial advice and the people who provide it: financial advisers, or as they're sometimes known, wealth managers. Wealth management is a very big business--and also a business facing a number of challenges, such as new technology, changing demographics, and tighter regulation in a lot of countries. A little later, we're going to be getting a perspective on China. But we're going to start here in North America. For the first part of the conversation, I'm joined on the line by Jill Zucker, a McKinsey partner based in New York, and Patrick Kennedy, who's based in Toronto. Pat is chief customer officer for PriceMetrix, which provides data and analytics to the wealth-management industry.


"FinTech and AI: Myths and Realities" by CreditEase MD at Tie Inflect 2018, San Francisco Bay Area

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These include H20.ai - an open source machine learning One; Active.ai - a conversational AI platform used by over five large Ms. Patwardhan shared her perspective from her past experiences in Facial recognition is the face of future for video banking. Not in the database yet was the verdict! Ms. Patwardhan highlighted that biometrics and digital identity can "One rolls its eyes cutely while greeting customers and the other "Has anyone watched Black Mirror?" she asked. "AI will continue to grow and have many positive


How to build trust in AI with blockchain technology - IBM Field Notes Blog

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Machine learning and AI are all about data. We give AI-powered systems massive amounts of data to ingest and analyze, and then we trust the results. But I want to know how we can ensure the integrity of those systems, from the algorithms to the data sources. I believe the issue of data integrity is a huge challenge for the AI community, both for users and developers. And I don't think we're looking at it closely enough.


Global Big Data Conference

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Since the beginning of modern times, each industrial revolution was driven by different automation. While factory machines and fossil fuels drove the previous industrial revolutions, the on-going automation revolution is based on data-driven artificial intelligence (AI). Understanding its impact and what will be required to support the AI-driven automation revolution is a fundamental necessity. So, as we evaluate the impact and the support needed to harness this automation revolution, it seems that at the center of this revolution is the growing need for computing power. There are indicators that raw computing power is on its way to replacing fossil fuels and will be the most valued fuel in the rapidly emerging intelligence age.


The Double-Edged Sword of Artificial Intelligence

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In 1942, science fiction author Isaac Asimov introduced the world to his three laws of robotics. An incredibly prescient visionary, Asimov started the world thinking about the potential challenges sentient technology might present the world of humanity. In LinkedIn's Financial Services/Fintech survey of more than 1,000 professionals from the broader FI/Fintech space, it is clear that the threats and opportunities associated with A.I. have never been more present conceptually than they are today. When you look at some of the organizations making big bets on A.I. today, the online lists always include technology majors, but we don't yet see banks investing anywhere near the scale of Microsoft, Google, Apple, Alibaba, Baidu and others. Industrial players like Boeing and Tesla are making big bets on A.I., so it is reasonable to expect that we should see big investments coming through financial services also.