Here we discuss the issues surrounding well-known Bavarian insurance giant die Bayerische using graph database technology to address and to provide consistent information on customers and contracts.
Graph databases have a growing reputation in the financial services sector. That’s because unlike most other ways of looking at data, graph databases are designed to model and uncover relationships, which means they can uncover patterns difficult to detect using traditional representations such as tables – and analysts forecast wide take up as a result.
There are a huge number of important applications that require the high performance and focus on relationships graph databases offer, while graph databases can use relationship structures to identify fraudulent transactions. One example of a financial services company needing a high-performant database to manage a large amount of connected information is Munich-based insurance leader die Bayerische.
For a century and a half, its comprehensive range of insurance and financial solutions have been a favorite among savvy customers in both its native state of Bavaria and beyond. With a brand promise of ‘Insurance with the Reinheitsgebot’ (the famous mark of quality for German beer), the aim has always been to maintain competitive advantage through superior services – and key to its latest push on this front is to have inventory database information available at all customer contact points.
For insurance companies like die Bayerische, a heavily heterogeneous system landscape for managing insurance contracts is simply a fact of life. There’s always going to be a multiplicity of back-end data systems that need to be maintained; after all, pension insurance or disability insurance persist for multiple decades. The penalty is the on-going effort needed to provide information on customers and contracts in a consistent internal business user interface.
To manage this situation better, this major European financial services operator decided to build a new, Internet-based field staff system in order to improve availability and performance of customer information at the point of sale – with graph database technology soon emerging as the ideal data engine to power it all.
A compact data network
To meet its needs, customer data needed to be replicated from different host systems and regularly synchronised which would result in a standardised data framework that would provide die Bayerische’s knowledge workers with a single version of the truth, the Holy Grail of all BI (Business Intelligence). The problem, however, was that traditional relational databases were not going to provide all the functionality required. Why? Because the sheer volume of data was too large, while running endless JOIN operations for queries was going to be too computationally expensive.
An alternative database system was therefore required – and as the VAA (Voting Advice Application) model used in many insurance products is similar to a graph database way of representing complex data, the use of a graph database was an obvious next step. A graph database can very quickly capture the work of an insurance company, plus its component data model’s richness and flexibility facilitates discussions between developer and business user.
One of the challenges that had to be faced early on was adequately representing the quantity of products and formats in the customer’s extensive financial product database. The flexibility of the basic graph model quickly resolved this issue of volume, however.
The end result of a rapid iteration cycle for the firm is a new application, Bay4all, that’s helping insurance advisors, call center employees and insurance brokers alike to access all relevant customer and contract data with good performance levels. Now in full production, approximately 400 team members at the German insurance leader are already using the new information system.
This new field staff solution delivers information speed, availability and consistency; when querying now, response times are on average between one and two seconds, delighting both customers and the staff helping them.
The insurance company's inventory systems are also synchronising with the graph database, while great data buffering means die Bayerische teams can access the system at any time, plus it can be restarted at short notice in the event of an error.
Flexibility and scalability
Experiences like die Bayerische’s and many others underline how large the potential contribution of the graph approach is for any high-performance database need in the financial sector – a sector where information needs to be available at any time at all customer contact points and offering high performance, flexibility and scalability.
By Emil Eifrem, co-founder and CEO of Neo Technology.