Digital Transformation in Insurance Powered by Big Data

Categories: Financial Services

The digital transformation in insurance is picking up momentum.

Insurance has the opportunity to leapfrog the other segments of Financial Services into the digital era. One thing in favor of this opportunity is the advent of wearables and sensors, or the Internet of Things (IoT).  Another driver for change in insurance are the customers: the digitally native Gen Y and the affluent. In a recent survey by Capgemini and Efma, almost half of customers indicated that they would buy insurance from a non-insurance company. That is a powerful force for change in insurance.

IoT is driving a key change – sensors are being embedded in everything around us –  smart homes, buildings, cars, appliances, wearable devices like watches, heart monitors etc. They can collect and transmit data that can be used to improve our lives and our health. For insurers, this brings a new and rich set of data that could be used for personalized risk assessment, dynamic pricing, developing new types of services such as usage based insurance (ubi).

Imagine a pipe bursting in your apartment while you are away. Your smart monitoring system, which includes smoke detection, burglar alarm and water sensors sends an alert to your monitoring service. They have been recommended by your insurance broker, to lower your premiums. They are part of a connected ecosystem of your insurance provider. They have a list of approved plumbers in your area, they send you a quote to your phone, you approve it with a tap on the screen. By the time you are home, everything is back to normal, because the damage was minimal and your cleaning service was alerted to come in right after the plumber.

Now, that’s an experience that can create loyalty and motivate customers to buy more services. The opportunities are endless and ever evolving.

InsurTech Examples

Digital Insurance may be the new frontier for FinTech startups, which some call InsurTech. They are driving innovation with services that are simple, intuitive, fast, convenient and are delivered through digital channels: one startup is selling “pay-per-mile” policies, another  is able to offer cheaper insurance for new drivers by using telematics to assess risk and to influence driver behavior.

In the life insurance space a new trend is to sell “episodic” or “just-in-time” insurance. One startup offers on-demand travel insurance that lasts from takeoff until landing. You can use their app to apply while you wait for the plane to board and the underwriting takes seconds.

Digital Insurance Capabilities

In order to capture these new opportunities insurers need to develop capabilities in four main areas:

  • Customer insights: create a 360 degree view from multiple sources: policy and claims, telematics, social media, website traffic, clickstream, GPS, call center, email, chat etc.
  • Improve products and services: Insurance companies will need to improve quality of service and at the same time reduce the cost to serve. IoT is also driving a fundamental change in how insurance companies can use sensor data to create and improve products as well as services – especially for Usage Based Insurance (UBI).
  • Lower business risk: new digital channels add new vulnerabilities. Insurers need to expand their fraud prevention and cyber security capabilities to cover more sophisticated, digital threats. For example, identify key patterns from free-form text, combined with GPS data, in real-time, to detect and prevent claim fraud. Many cyber attacks do not conform to existing patterns, so it’s important to be able to have a comprehensive baseline of network data and log data, to detect exceptions and Advanced Persistent Threats (APT).
  • Modernize IT architecture: in order to support the new business goals enumerated above, insurers need to take advantage of new and untapped data sources, especially unstructured data, through modernizing their architecture based on big data technologies.

Cloudera can help in all these areas by providing an Enterprise Data Hub (EDH) as the foundation for consolidated data management. EDH makes all types of data available for analysis, in real-time and securing the data at Petabytes scale.

Customer Insights and Usage Based Insurance

Traditional insurers, who have historically competed on general pricing or via broad, expensive marketing campaigns, want to differentiate their coverage options by customizing plans based on information collected about the individual’s lifestyle, health patterns, habits, and preferences.

Let’s talk about one of Cloudera’s key customer – a large US based insurance provider.  This insurer has more than 80 years of policy data. From a business perspective, the insurer wanted to create a 360 degree view of their customers and be able to analyze all of the data, current and historical, across all 50 states.

As the insurer began to transition its historical and current policy data into online records and attempt to run programs that correlated such external data as traffic patterns, socioeconomic studies, and weather information, the IT department found that the systems would not scale to process such volume of data and the variety of formats from diverse sources.

For instance, they could look at data from a single U.S. state at a time—with each state’s analysis requiring about a day to process—but could not run analytics on all 50 states at once. Although new data systems were being put in place to capture and prepare data for reporting and business intelligence, they were primarily aligned to marginally improve on old approaches to data management, which separated data types and workloads into distinct silos.

The insurer brought together customer account information, public economic and social studies, and telemetric sensor data in its initial Apache Hadoop cluster. Some of these data sources had never been brought together before, and much of the historical data, which was newly digitized, could not be analyzed in tandem with external sources prior to landing in Hadoop.

Today, the company’s Enterprise Data Hub is integrated with its incumbent mainframes and data warehouses—it was designed specifically to complement, not replace, existing infrastructure.

Now that it can run descriptive models across historical data from all 50 states using Apache Hive—open-source software that makes transformation and analysis of complex, multi-structured data scalable in Hadoop—the insurer is experiencing an average 7500% speed-up on analytics and seeing even better results with Apache Impala.

Another positive outcome was the development of a Usage Based Insurance offering. By tapping into the sensor data from 1 Million of connected cars, combined with policy and claim data, they are able to understand risk and incentivize drivers at an individual level.

Security and Governance

When you consolidate all your data into an Enterprise Data Hub it’s important to secure it, protect it, partition it and be able to perform audits and searches.

Cloudera’s solution offers enterprise grade data security and governance at Petabytes scale for your Hadoop environment.

Cloudera Navigator is the first fully integrated data security and governance application for Hadoop-based systems. It provides data lineage and discoverability and policy-based management of sensitive data.

Cloudera Navigator encrypts data at rest and in motion and, with its Navigator Key Trustee Server, encryption keys are separated from the encrypted data, ensuring that sensitive data is still protected if unauthorized users gain access to the storage media.

This feature is also useful in a hybrid cloud scenario, where part of your data may reside in a cloud provider data center.

Clearly the analytics opportunities that big data provides for insurance provides are endless.  I would love to continue the conversation.  If you are attending Strata + Hadoop World in New York, please visit us at our booth.  We will have Financial Services experts that can answer any of your questions. To learn more about Cloudera solutions for Insurance, click here.


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