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January 24, 2018

IoT Platforms Emerge For Insurers

George Leopold

The insurance industry is accelerating deployment of Internet of Things platforms as a way of connecting with insured assets ranging from vehicles, property and even individual policyholders.

In an IoT case study, a telematics vendor worked with Cloudera and other data platform vendors over the last two years to develop a secure next-generation platform that captures data generated by IoT sensors. It then integrates data with insurers’ claims process.

Following about six months of beta testing, Octo Telematics said it released a commercial version of its next-general platform in July 2017. It is currently migrating most of its existing customers to the IoT-based insurance framework.

The platform runs on Cloudera’s (NYSE: CLDR) enterprise suite, which includes data security, governance, and workload management functionality.

The case study revealed that the key considerations for insurers were security and accommodating a growing number of different data sets. “With the growth of IoT and an order of magnitude increase in the number and types of connected sensors, Octo Telematics foresaw that the current platform would become an increasing constraint on the company’s growth ambitions,” noted Charles Juniper, a financial services analyst with case study publisher Ovum Consulting.

Vehicle, property and personal data collected in the database “needed to be closely coupled to the incident response and claims processes if an insurer was to offer policyholders a fully integrated IoT insurance proposition,” the study noted. The lack of integration prompted Octo Telematics to work with Cloudera, Software AG (ETR: SOW), Salesforce.com (NYSE: CRM), SAS and SAP (NYSE: SAP).

The core technology from Cloudera includes Apache HBase and Impala used to analyze inbound sensor event streams. Octo also is using Apache Spark to handle huge IoT data volumes along with its multiple computing clusters and a distributed data set structure to train and test machine learning models. “These models allow Octo Telematics and its insurance customers to better understand, model and price risk,” Ovum reported.

Meanwhile, the platform’s distributed computing model enabled Octo’s customers to run the platform on-premises or across private and public clouds. In one scenario, the new platform could use public cloud computing services to test new pricing algorithms or to develop new risk models.

Those risk models are increasingly being used to reduce losses associated with fraudulent insurance claims, which according to industry estimates cost insurers an estimated $32 billion annually.

Meanwhile, Octo Telematics said it is working with insurance software vendors to develop connectors that would facilitate direct integration between its IoT platform and insurers’ in-house claims processing systems.

The vendor’s new configuration provides enough computing power to support up to 20 million simultaneous IoT sensor devices, or about four times the total deployed so far. “As the number of sensors approaches this limit, it will only require the addition of further cloud-based compute and storage resources to accommodate the growth,” the case study noted.

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