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Deep Dive: How FinTechs, FIs Can Arm Up Against Fraud

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Financial services providers that slack on regulatory compliance and fail to safeguard their operations against money laundering, terrorist financing and other criminal activities may face damaged reputations and significant fines. Compliance failures are prevalent worldwide: Approximately $26 billion worth of fines were levied against banks for AML, KYC and sanctions noncompliance between 2008 and 2018. A report found that the U.S. imposed a full $23.52 billion -- 91 percent -- of those penalties, while European regulators demanded $1.7 billion and the Middle East levied $9.5 million. FinTechs could face these same financial pains as regulators increasingly demand that they follow the compliance rules to which FIs must adhere. The People's Bank of China announced in March that it plans to create rules for regulating and securing the FinTech sector, for example.


Deep Dive: How FinTechs, FIs Can Arm Up Against Fraud

#artificialintelligence

Financial services providers that slack on regulatory compliance and fail to safeguard their operations against money laundering, terrorist financing and other criminal activities may face damaged reputations and significant fines. Compliance failures are prevalent worldwide: Approximately $26 billion worth of fines were levied against banks for AML, KYC and sanctions noncompliance between 2008 and 2018. A report found that the U.S. imposed a full $23.52 billion -- 91 percent -- of those penalties, while European regulators demanded $1.7 billion and the Middle East levied $9.5 million. FinTechs could face these same financial pains as regulators increasingly demand that they follow the compliance rules to which FIs must adhere. The People's Bank of China announced in March that it plans to create rules for regulating and securing the FinTech sector, for example.


Lufax Uses New Data Types and Advanced Fintech to Optimize Wealth Management

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Lufax chief product officer Jeff Li spoke about the roles of data, artificial intelligence, and machine learning in wealth management at the inaugural Greater China Alternative Investments and Alternative Data Conference organized by the Beryl Consulting Group and Global Tone Communication Technology (GTCOM). "Lufax conducts its business completely online. Our interactions with customers are mainly achieved through mobile apps," explained Li. "This makes behavioral data all the more valuable and imperative." Instead of constructing customer profiles through in-person meetings, Lufax leverages behavioral data generated from the use of its platform, as well as official and public data to formulate a multi-dimensional risk profile, where risk attitude, capacity, and appetite combine to inform the determination. The system takes into consideration the biographical, financial, and lifestyle information customers voluntarily enter themselves to understand and anticipate their wants and needs, and project their future investment paths.


Fintech Infographic of the Week: Ethical AI - Fintech Hong Kong

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Artificial intelligence (AI) is set to play a key role in the future of financial services and more broadly in what UBS and the World Economic Forum refer to as the "Fourth Industrial Revolution." The global economy is on the cusp of profound changes driven by "extreme automation" and "extreme connectivity." In this changing economic landscape, AI is expected to be a pervasive feature, allowing to automate some of the skills that formerly only humans possessed. In the financial services industry in particular, there has been a lot of noise around the potential of AI and data supports that investors are excited about the impact the technology could have across the industry. VC-backed fintech AI companies raised approximately US$2.22 billion in funding in 2018, nearly twice as much as 2017's record.



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.


Big Data's Human Element

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The Hong Kong Fintech Week was staged at the Hong Kong Convention and Exhibition Centre, and saw HKUST faculty engaging in lively discussions with senior executives and business leaders on the digital future of the financial services industry. The audience heard three important talks on related themes. First, Professor Mike So, from the Business School's Department of Information Systems, Business Statistics & Operations Management, spoke on the "Use of Smart Data in High Frequency Finance and Risk Management". He began by describing how high-frequency stock trading works. "Once there is a profitable signal from the market, an algorithm is used by high-speed computers to perform trades."