When analyzing company investments it is useful to group investors to understand industry patterns. The image below shows such a grouping for some recent invesments in the FinTech-space.
![](http://leobosankic.com/wp-content/uploads/2021/02/image-2.png)
The company clusters are immediately visible.
Whereas useful, these relationships only capture the most basic data: companyA invests in companyB. More realistically, however, such investments happen in a context; for instance, the above image does not capture the fact that the investors and companies have implict relationships with each other. The image below takes these implict relationships into account:
![](http://leobosankic.com/wp-content/uploads/2021/02/image-3.png)
Using Neo4J to analyze groups in this version shows different groups
![](http://leobosankic.com/wp-content/uploads/2021/02/image-4-1024x743.png)
As an example consider Google and Amazon. In the basic version they were not connected…
![](http://leobosankic.com/wp-content/uploads/2021/02/image-5.png)
… however, Neo4J’s grouping algorithm put them into the same bucket
![](http://leobosankic.com/wp-content/uploads/2021/02/image-6.png)
When we drill down we see why this grouping makes sense:
![](http://leobosankic.com/wp-content/uploads/2021/02/image-7.png)
Google and Amazon are both active in the insurance industry. It is worth noting, that this relationship is not explicit but rather through respective partnerships and sub-companies:
Google own Verily which in turn has launched Coefficient Insurance Company, a company in the insurance industry. Amazon, on the other side, has partnered with Acko, also a company in the insurance industry.