Data Driven Insurance Transformation

Insurers are re-shaping their roles and value propositions with customers in mind, transforming into data driven, value-based entities.

(Image credit: Pan Yunbo.)

Rapid technological advances and changing customer behaviors has accelerated the rate of change and disruption in many industries. COVID-19 has further accentuated the pace of disruption. Insurance companies need to be ready to face these new challenges as well as opportunities.

Insurers have always been data savvy, but they will have to move faster than ever to keep pace with competitors and other industries in the modern environment. In addition, the volume and velocity of data to deal with will be much higher than ever, forcing insurers to further invest in their capabilities to store and compute their data assets.

The journey begins with solving for data silos that have been created over decades and inhibits Insurers from harnessing the value of data. While solving for data silos, it’s important to keep in mind that multiple legacy systems may elongate the transformation to data on cloud journey. Hence insurers need to accelerate the migration through automation to achieve speed to value and reduce cost associated with maintaining multiple systems.

Below are the key business imperatives that a modern-day insurer needs to enable to stay ahead of competitors.

One thing is certain, the insurance sector of the future will look very different to how it does today. And this shift has already started to happen across the Insurance value chain. Insurers are increasingly re-shaping their roles and value propositions with customers in mind. They are transforming from purely insuring risks to being a data driven, value-based insurers.

Data on Cloud is driving force behind much of this change and presents a solution for insurers.

Opportunities for Data-driven Insurers Across the Value Chain

For insurers who are weaponizing data, there lies tremendous opportunities build differentiated capabilities on newer products, underwriting and risk management capabilities, claims and distribution which will help them being more customer centric and leapfrog competitors.

List of key use cases across the insurance value chain that can be enabled:

3.0 Key decisions that impact the Data Cloud Strategy

While Section 1.0 describes the imperatives and Section 2.0 shows the opportunities across value chain, this section emphasizes on the key decisions that are critical to defining the overall data & analytics roadmap for an insurer.


4.0 Why Snowflake Data Cloud Platform?

To conclude as a summary of above Sections, it is evident that insurers needs to think long term while choosing data cloud platform, it is preferred to choose cloud vendor agnostic capabilities, scalable, secure and at the same time very cost effective.

Snowflake is uniquely positioned for this, it works on any of the major cloud platforms viz, Azure, AWS, GCP. Snowflake is purely SaaS based offering which means zero maintenance cost for insurers. It is multi-cluster; shared data architecture provides required scalability as well as concurrent data sharing/processing by multiple workloads.

Snowflake has also built a strong ecosystem of data integration, Data Security as well as Analytics and BI Partner, that facilitates faster adoption of Cloud Data warehouse as well as accelerated transformation of BI & Analytics to cloud platform.

In summary, Snowflake checks all the boxes for a data-driven insurer’s needs:

Separate Compute and Storage—providing ability to unlimited compute power, isolated workloads while not worrying about storage costs.

Auto Scaling—Snowflake provides auto scale-up and scale-down capabilities based on need of the data workloads. All these is taken care at runtime without need of a manual intervention or any process delays.

Third Party Data Exchange—Snowflake Marketplace has published variety of third-party data assets that are critical for insurance use cases. This provides a seamless integration as well as easy availability of critical data at one place.

Data Sharing—Ability to share data with internal and external stakeholders with right access control mechanisms. Facilitating the common data sharing across insurance enterprises and their partners in some cases.

Data Integration—Snowflake allows various tool sets including its native connectors to integrate data from variety of sources including core insurance products, Mainframe systems etc. It also has built in Snowpipe utility that enables data streaming for insurance data such as IOT, telematics etc.

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Ravindra Salavi // Ravi Salavi leads Data Analytics & AI Solutions for LTI’s Insurance business unit in North America. He has more than 18 years of experience working with insurance companies. Salavi specializes in the Commercial line of business and role of Data Analytics to build risk Insights, profitable underwriting decisions and cost & fraud optimization for claims. He has led various strategic initiatives in business and IT transformation, Digital, AI and Analytics for leading insurers in the NA region.

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