Our customer in this success story is a large German insurance company.
The (sub)business of the client
The user of the system, an insurance company employee wants to create or manage insurance contracts, record a claim, etc.
The initial situation in 2014
A customer calls and is called, for example, "Müller" (frequent name) or "Marco di Angelo" (name for which it is unclear how it was stored in the database). The employee carries out a name search, which takes a long time with the classic relational database used here. Too long.
This is due to the access rules and the amount of data that are valid here: An employee of an agency is only allowed to "see" a customer with whom the agency has already had contact, i.e. an offer or a contract has already been created by the agency. This prevents "customer fishing".
In the relational database, there were about 120 million contracts or offers, about 20 million customers and 10,000 agency users distributed among about 200 agencies. If you try to do this in a single database query in a classic, relational database, the world stops here for a moment. And the earth warms up a little.
The solution February 2015
The world had continued to turn.
- We developed an application for the backend (server) that stores the data in a graph database. This makes it easy to determine the connection between agency employees and customers
- In addition, a fast open source search engine (integrated in the graph database) is used to find customers.
The success June 2015
The graph database access times are about 200 times faster in extreme cases (12 minutes for the relational database vs. 3 seconds for the graph database)
Key to success
- Use the latest technology
- Sharp analysis of the problem
- Optimization of the design for the problem
These are all the values that have turned small garage stalls into big companies.
We would be happy to advise you personally - just contact us!
*Companies anonymized for reasons of customer protection and confidentiality agreements.