![Insurance agent examining car damage Insurance agent examining car damage](https://www.sas.com/no_no/industry/insurance/technology/iot-analytics/_jcr_content/par/styledcontainer_ced3/image.img.jpg/1540841091815.jpg)
Industry Applications
IoT Analytics for Insurance
Gaining a bigger advantage from big data streaming from IoT.
Business Challenges
Over the last few years, the insurance industry has seen significant disruption and innovation. Major investments have been made in digital initiatives, but the most dramatic changes relate to the Internet of Things. IoT has started to radically disrupt the traditional insurance business model and modernize processes, especially in the area of risk assessment. And smart home devices, wearables and driverless cars will usher in a shift toward a new type of customer relationship where insurance becomes less reactive and more preventive. The winners will be organizations that overcome today’s obstacles to embrace change and capitalize on uncertainty.
How IoT Analytics From SAS Can Help
SAS can help you better understand your customers and how their needs change over time, as well as uncover profitable revenue streams that can differentiate your business. Analytics, including artificial intelligence (AI) applied to IoT data, derives value from vast amounts of IoT data, providing insights you can act on. With IoT solutions from SAS, you can develop an effective IoT strategy that includes AI in a variety of critical areas, including:
- Risk analysis. Assess risk with greater precision, create new pricing policies and estimate claim reserves using different data types from IoT devices with embedded AI.
- Social media data analysis. Deliver personalized offerings that will transform the customer experience.
- Telematics. Rapidly test and deploy powerful AI-based models that can identify new risk factors and create new pricing models from telematics and other IoT data.
- Customer experience. Perform real-time customer pricing, offer health and well-being services, and manage customer mortality risk.
- Claims processing. Drive further evolution in claims processing by aiming toward active loss prevention through:
- In-vehicle sensor data analysis, which provides warnings of dangerous driving patterns.
- Weather sensor data analysis, which complements underwriting and loss prevention.
- Drone data and aerial imagery analysis, which can be used for property inspection in the event of a damage claim.
Why choose SAS® for IoT analytics?
SAS has the experience and expertise in advanced analytics, extensive analytics IP for insurance, and the ability to unify diverse, open source technology environments to help you reduce risk, ensure business continuity and accelerate time to value. With IoT analytics solutions from SAS, you can:
- Reduce costs and increase efficiency by collecting, managing and analyzing data where it lives.
- Make more confident decisions using insights based on all available data, including IoT data at rest, in motion and everywhere in between.
- Boost the productivity of your data analytics teams by enabling developers and partners to build and expand on sophisticated models to get highly accurate results – using a single, collaborative environment.
- Uncover new IoT market opportunities resulting from changing conditions by tapping into the full potential of all your data.
- Gain real-time insight into your customers and how their needs change over time so you can deliver a personalized customer experience.
- Streamline and automate processes across your IoT infrastructure for both incremental and long-term business gains.
Related Video
SAS IoT Analytics Solutions for Insurance
- SAS® Analytics for IoTDrive innovation, efficiencies and results by putting IoT analytics in users' hands – from predictive maintenance at scale to superior process optimization and quality, flood prediction and preparedness, energy cost optimization and beyond.
- SAS® Event Stream ProcessingUse machine learning and streaming analytics to uncover insights at the edge and make real-time, intelligent decisions in the cloud.