The problem Cassandra solves

Financial companies have been running credit risk models since decades and they are pretty good at it. But in this decade we are seeing new categories of risk which are becoming more important, like reputational risk. Entities are growing more and more complex today than ever, interconnected with a lot of other entities and to derive meaning from such a huge, complicated MESS of data is becoming more and more difficult.

We built a solution that lets you leverage reliable public data regarding the entity and derive risk models from the same. The solution prototype that we built uses a mechanism of anchoring links of the entity from Wikipdia, DBpedia and LEI. Using the information we derive an entitities aliases, subsidiries and the way it is strutctured.

All to ALRT you when in it is the right time!

Challenges we ran into

We ran into several issues while attempting to use React Native for our product and so we had to move to a React Web App. We found it difficult to implement the logic through the required functional components aside from various other errors that were difficult to identify.

The architecture was really difficult to figure out as it was really complicated in terms of companents, however finaly we ended sepaprating the API and the data aggregator