Unlocking the potential of sensor data for insurers

Building tailor-made insurance 2.0 products using data analytics

Sensors can already measure about anything and due to further performance improvement the number of IoT devices is expected to grow to > 20 bln in 2020. Sensor data together with external APIs and cognitive technologies will enable insurers to build next generation tailor-made propositions.

Sensors and Internet of Things

Sensors can measure, pressure, position and motion, vibration, temperature, humidity, chemical concentrations, radiation and many other things. But despite the fact that sensors can already sense almost any physical parameter you’d like to measure, many industries so far have struggled with sensor implementation mainly caused by issues with power (sensors require electricity and batteries die over time), ruggedness and sensor costs. Given the immense potential benefits huge investments are made in further sensor improvements which according Gartner will result in growth of the number of sensors equipped Internet of Things Units from 5 bln in 2015 to over 20 bln in 2020 of which 65% will be consumer related.

Deloitte dutch insurance outlook

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Quantified Self

Quantified Self can be described as self-knowledge through self-tracking with technology. Individuals can already track personalized driving behavior (Telematics) and can quantify biometrics that they never knew existed. More, better and cheaper sensors will make data collection cheaper and more convenient, enabling mass adoption of personalized tracking of health and many types of services.

The potential of data Analytics

The growth of sensor data combined with new (big) data technology developments provide an interesting opportunity for insures to switch from traditional (average statistics) to new (near) real-time, personal usage-based products and services. Application Programming Interfaces (API) make it easier for Insurers to integrate external and relevant (customer) information such as Facebook, Twitter and Weather Data. Using advanced data analytics techniques data from internal- external, structured and unstructured sources can be integrated. Combined with new cognitive technologies the platforms are also able to evolve to self-learning systems. 

Impact on insurers

In the upcoming years sensor data will provide consumers more information about their personal risk profile than ever before, enabling them to make better decisions about what they should, but also what they do not have to insure. When for instance through DNA sequencing an individual learns he / she will most probably not reach the age of 65 this person is no longer interested in traditional pension products but will probably be receptive to products and (insurance related) services in the area of cure or treatments of his disease and beneficiary planning.

The expected near term mass consumer adoption of Telematics, Quantified Self, DNA sequencing and other forms of personal data gathering & analytics will impact insurers in several areas:

  • Shift in information asymmetry: Common risk profiles are at the basis of most current insurance products. Non-shared additional (sensor generated) information on personal risk profiles will create a shift of information asymmetry from insurers to (potential) policyholders. As a consequence insurers could face significant profitability impact as a result of adverse selection issues for current products & portfolios. Insurers should therefore proactively (re)design insurance products and services around new risk pools and / or incorporate additional sensor related risk related information.
  • Technology and data landscape. Insures should adapt their technology and data landscape enabling them to  cope with the large amount of additional (sensor) data, the integration of external data (via API’s) and apply new (big) data technology that can analyses and process these volumes near real-time.
  • Analytical capabilities and people required. Like most companies Insurers face a challenge in upgrading both volume and level of their analytics capabilities to levels required to be successful in this new world of (big) data. One way to address this issue is by creating ‘purple teams’ combining insurance acumen with data analysis, creative / story telling skills and deep technology skills.
  • Analytics eco-system. As there is more analytics knowledge and capabilities outside than inside insurers working with ad hoc or strategic ecosystem partners can help insurers to grow their own capabilities and learn faster in this quickly changing domain. In addition data analytics platforms like Kaggle can help them solve (complex) business problems and / or get access to skills or capacity. 

More information on unlocking sensor potential through data analytics?

Want to know how insurers can benefit from the potential of sensors by using data analytics? Please contact Frank Bovee via or (+31)06 8333 9412 or contact Joep Dekkers via or via (+31)06 1258 1595. 

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