The SAP S4 Hana and cloud adoption naturally puts the technology architecture in a sweet spot to be able to pool in data from external sources and build big data capabilities for the analytics team to run meaningful programmes, says Shanai Ghosh, CEO & ED, Edelweiss General Insurance.
Edelweiss General Insurance (EGI) has been in operations for a year and a half now. The company has built a ‘cloud native’ technology infrastructure to enable an agile and scalable open enterprise architecture. A cloud-based IT platform dovetails into having an advanced analytics infrastructure, which is critical for any insurance company.
The SAP HANA database acts as a central repository for all data. The conventional challenge for enterprises has been data residing in siloed locations. Edelweiss General Insurance has avoided that issue by having a seamless IT infrastructure for data management. Even the data layers out of the scope of SAP S4 Hana are pooled into the Hana database. This provides a single source of truth and avoids data integration challenges. This is fundamental to having a robust data analytics programme. Most of the traditional organisations struggle in having uniform data architecture.
The cloud adoption naturally puts the technology architecture in a sweet spot to be able to pool in data from external sources and build big data capabilities for the analytics team to run meaningful programmes. Cloud adoption also allows access to many of the services provided by the cloud service providers (CSPs). The microservices-based API architecture also allows integrating many other data points and interfaces.
Data integrity is also an important element in any data analytics programme. “We have kept checks and validations at the point of data acquisition and ingestion in order to ensure data quality,” says Ghosh.
Analytics has to be embedded into the core business processes and it cannot be an isolated system or program. Like how apps are designed keeping in mind the customer journeys, analytics should be a part of these journeys and should be made useful for the stakeholders in order to make decisions. The executive conviction is indispensable to call out the importance of analytics and not just a ‘nice to have’ program. It should be considered on par to have a core policy administration system and governance to capitalise on the true potential.
The roadmap for analytics is to have a futuristic view of various processes. For e.g. behavioural analytics can be applied in a claims process. In case of an accident, instead of asking the customer to fill a digital form, he can be asked to come over a video call and explain, what transpired during the accident and based on his explanation, gestures and many other factors which can be set. This supported by multiple other algorithms and images/videos of damages/bills, will give a comprehensive view to arrive at a red, amber, green score that will indicate whether it is a straight through process or requires further diligence with straight through claims being paid out instantly. This is the level of analytics automation that EGI is planning to have in the future.