For major insurer Allianz Benelux, graphs are at the core of its data strategy, positioning them for the future and allowing them to be truly customer-centric

The Challenge

One of Allianz Group’s most successful data-driven operations is Allianz Benelux data office. Allianz Benelux has an estimated annual turnover of €4bn. Having gone through a long series of mergers and acquisitions, however, its customer data has become dispersed and incomplete, a situation which can lead to operational inefficiencies and ineffective customer service. As the company’s chief data and analytics officer, Sudaman Thoppan Mohanchandralal, puts it, “We need to secure customers from risk, not just today but into the future. We can only do that by having full insight into the risk environment and with an ability to predict it for our customers.”

Dr. Jan Doumen, head of the School of Expertise of the data office, and strategic theme lead for Customer & Broker Information and Insights, adds: “The best way to understand your customers and the risks they are exposed to on a daily basis is by storing, analyzing and visualizing them through connected data. Graph technology does this at scale, which means we no longer have to rely only on highly demanding, traditional relational technologies.”

For example, as a truly customer-centric insurer, Allianz takes a zero-tolerance stance on fraud. Historically, building internal visualizations of suspicious behaviors with relational technology had been far too demanding. Fraud countermeasures, such as network tracking, were simply too difficult to build in a relational database. Sudaman calls this inefficient process a “2 by 2” approach, where SQL database-style tables with rows and columns don’t inherently offer the deep, contextual data connections fraud detection and prevention requires. It does not allow them to extract warm data.

Graph technologies allow spotting potentially fraudulent activity in Allianz’s ecosystem by visually revealing the fraudster’s concealed illicit connections. Bringing all the customer data into a graph database also allows Allianz Benelux to reveal the true risk exposures and detect uncovered risks or overlapping coverages, in particular in a motor or household context.

The Solution

After an extensive market evaluation, Allianz Benelux decided to make Neo4j its primary graph platform, due to its scalability, elasticity, enterprise readiness and market dominance.

“We were impressed with the solid graph theory that underpins the product,” Sudaman confirms. “We also soon saw that it was the only truly enterprise grade graph software we could find on the market.”

“When we were showing Neo4j internally, this graph-based way of discussing problems was immediately meaningful to colleagues, and we almost instantly had buy-in,” Jan adds.

Jan describes the help Neo4j offers. “When you’re trying to think about your customer, if you start with their location and their house, the address that they live in and the other people that appear to also be living in that address, you start to quickly build a picture of the kind of relationships this particular person has with other people.”

“When we were able to get to a level with Neo4j to show colleagues this very 360-degree view of a customer, it was so much easier for them to understand rather than through a table with rows and columns. This obviously will enable them to personalize their services towards our customers.”

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