Fintech News: August 26th, 2016

This week in fintech: a futuristic theme. Bots threaten thousands of banking jobs, big data’s impact on the customer experience, to license (or not to license) a neo-bank, and growing complexity of the robo-advisor product suite. These columnists share their visions of technology’s impact for the long haul.

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How Many Banking Jobs Will Bots Kill? (American Banker)

Bots will eliminate many of the mind-numbing jobs in finance, especially in operations, wealth management, algo trading and risk management. While the short-term prospect is scary (lost jobs,) in the longer-term, it will free up more laborers to do more intellectually stimulating work. According to the banks, at least.

Big Data Is Useless Without A Big Strategy (American Banker)

Banks, who traditionally used analytics for reporting purposes only, are cozying up to the data-driven customer experience. Still, they are vastly understaffed in their data science departments, who decide exactly how they use their data effectively. One goal for the long-term: identify the customers who are profitable, and figure out how to retain them.

Fintech’s license to fail (Bloomberg)

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Banks’ net interest margins have fallen fast. (Source: Bloomberg)

British neo-banks want to control their own “pipes,” secure their own deposits and determine their own growth. Most importantly, they need a tight grip on their customer data to cross-sell new products. But registering as a bank has its pitfalls; it takes huge scale (more fundraising) to become profitable, and regulation slows down product development. While many startups are dying to get a banking license, some of those who have one are already seeking to get rid of it.

What data feeds your robo-advisor? (Daily Fintech)

Right now, most robo-advisors only use primary data sources: stock and ETF fundamentals. However, as their product matures, they may begin to integrate higher-level data, like P/E ratios, volatility measures, earnings estimates and sentiment data. As the robo-advisor grows more complex, it will begin using all of these forms of data at once, eventually looking more like a quant-based hedge fund than a target-date fund.

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