Drew Aldrich at AXA and I have spent a lot of time thinking about how new devices, software and technologies can aggregate data in new and interesting ways.
But the promise of data often lags behind the actuality of its applicable use. Too often we get pitched by companies claiming to use new data sets and machine learning to do X, Y and Z, when in reality they are businesses that have stumbled into some weird and narrow type of data they are trying to come up with ways to use.
This is especially true in the Alternative Lending, Insurance, and Hiring spaces. In those industries we’ve found most companies have pursued efficient customer acquisition over materially improved underwriting and or analysis.
But despite our disappointment to date, we are not lacking in optimism. And so, with the help of a team at the Cornell Venture Capital club, we have worked to aggregated a variety of interesting data sets with applicable uses, companies using those data sets, and the types of industries we are most excited about that would benefit most from implementing these use cases.
We also have done our best to predict implications and how the lay of the land will evolve over time.
Some key findings are as follows:
(1) Innovation 1.0 in Alternative Lending was in finding better ways to acquire a customer more efficient customer acquisitionly. Innovation 2.0 in Alternative Lending is in using new “previously unobservable data sets to materially improve the underwriting process and allowing for access to credit in provide credit in previously underserved, or unserved markets.” Insurance will likely follow this pattern as well.
(2) Companies like MetroMile and PlaceIQ use dynamic data sets that are evolving in real time to price in a dynamicn elastic rather than, as opposed to static ,static, manner.
(3) The startups who will earn the biggest outcomes are those that can (1) offer a better produce product via improved underwriting (2) invest capital in acquiring a customer base and (3) reach scale where to drive down their cost of capital comes down. Companies incapable of doing all three of these things should raise less capital so that they can one day become acquired. Technology solves point (1) and large capital investments solve for (2). (2) solves for (3).
(4) Incumbents are less afraid of startups being the source of disruption, and are more afraid of their rivals acquiring technology and in doing so, gaining an edge over a traditionally commoditized market. Companies in this space who raise less capital may receive capital efficient and lucrative outcomes in the 8 and 9 figures.
(5) The incumbents most protected are those who have built in high switching costs to their products.
And here is the research report we put together for it!
We hope you enjoy, and happy to hear your feedback.