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.


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)

Screen Shot 2016-08-26 at 10.16.20 AM

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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