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JP Morgan: Expanding Machine Learning Capabilities in the Financial Services Arena
Mike
Posted on November 13, 2018 at 7:59 pm
Brief overview of JP Morgan's adoption of machine learning into its day-to-day operations

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On November 15, 2018, Mike commented on Lemonade reinvents the insurance industry with machine learning :

Awesome research on Lemonade; it’s definitely got some potential to revolutionize the way insurance companies do business. I will say, however, that I am wary about its expansion, especially outside of homeowner’s insurance. Insurance carriers underwrite some pretty complicated policies; homeowner’s insurance is a relatively simple line of business relative to other lines like medical malpractice/worker’s compensation/etc. and has a significant amount of data points to use, given the fact the policy is renewed every year. Does the machine learning have the ability to write more complicated insurance with significantly less data? Furthermore, insurance companies invest heavily in actuarial sciences and predictive data, so I wonder whether they will opt to use this type of technology in-house rather than go with Lemonade.

On November 15, 2018, Mike commented on 3D Printing…we should ‘Just Do It’! :

Terrific post! 3D printing brings a whole new dimension to retail. Given the ability to mass customize, I wonder if Nike should first experiment with using their 3D-printed products on the mass general population rather than using their typical R&D process of utilizing elite athletes. This may be more effective because more time and experience integrating 3D printing into the process will be required to draw any conclusions.

On November 15, 2018, Mike commented on Adidas’s Race to be #1 in 3D Printing :

This is a fantastic concept and I think this is how broader retail will be shaped in the future and the impact on store inventory cannot be understated. It eliminates waste almost entirely. Those who adapt last will be losers in the retail game; in-store 3D printing virtually eliminates out-of-stock issues. Retailers will also have less trouble predicting the upcoming trends and will be able to adjust the purchase of goods accordingly.

On November 15, 2018, Mike commented on Open Innovation at NASA: Impact in Culture :

To answer the question “can standard and open innovation processes coexist in the same organization?” I would argue that NASA is probably one of the best examples of doing so over the last 100 years. Early space flight required intense abidance by physics-driven rules all while innovating new technology that would do so (and become a huge part of the recent technological revolution). I think NASA should looks to its past to understand that they were once the masters of open innovation, whether they know it or not.

On November 15, 2018, Mike commented on Block by Block: Harnessing Open Innovation at The LEGO Group :

I liked your article, but disagree with the continued push for “over-innovation” — I fear that Lego may be over-thinking what made it great in the first place. As the world has gone almost completely online, I think Lego’s value proposition to parents is that it is totally offline; it builds skills that “screen” toys cannot. I think Lego should keep their products physical and incorporate ways to use innovation to source their product ideas.

On November 15, 2018, Mike commented on Sales=MC2: Salesforce’s Attempt to Democratize Artificial Intelligence :

Awesome post! I agree that far and away, Salesforce’s biggest advantage is it’s unique access to the best pool of sales data from which to generate predictions — but the skeptic in me doesn’t see the translation into “democratizing” artificial intelligence; rather, I simply see Salesforce as running intense data analytics (already its core business) and packaging the “artificial intelligence” buzzword as a new product. It seems like there’s a long way to go towards making AI truly available for all.