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Fintech in 2017: Risk management takes center stage

A day in the life of the gentleman banker was once described by the 3-6-3 rule – accept deposits at three percent, loan money at six percent and tee off at the golf course at 3 p.m. The financial services industry can rightfully state that it has come a long way since then. It has implemented technological innovation and managed risk in a constantly changing economic environment over several decades. The gentleman banker has since evolved into a sophisticated financial risk manager who works within a complex framework of rules and regulations with tens of trillions of dollars of assets under management. 

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Topics: big data, banking, AML, fintech, regtech, regulation, machine learning, money laundering, risk management

The NoSQL Ecoystem: A C-Level Guide

As a C-level executive, it’s becoming clear to me that NoSQL databases and Machine Learning toolsets like Spark are going to play an increasingly big role in data-driven business models, low-latency architecture & rapid application development (projects that can be done in 8-12 weeks not years).

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Topics: Spark, analytics, Hadoop, big data, advanced analytics, NoSQL, analytics as a service, Big Data Prescriptions, business perspective solutions

The Sand Hill IoT 50 Needle Movers

In this summer’s blockbuster movie “Edge of Tomorrow,” a PR executive played by Tom Cruise goes through innumerable time loops to become a soldier by being reborn every time he is killed. In the context of software startups, successful products are built through repeated testing and improvement. Those that can do the most iterations without dying become the needle-movers.

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Topics: Sand Hill IoT 50, analytics, 2015, wearable computing, big data, instrumentation, predictive analytics, IoT, Internet of Things