Key Insurance Technology Trends and Digital Transformation

Historically, the insurance industry has not been known for the rapid adoption of new technologies. However, today, both leading insurance companies and emerging startups have become much more policyholder-centric, catering to the unique needs, behaviors, and preferences of consumers rather than offering a one-size-fits-all approach.

In addition to more personalized offerings, insurtech businesses are exploring new ways to deliver solutions by partnering with non-insurance brands. They are also implementing machine learning techniques and using IoT and drone support to speed up insurance decision-making. This shift increasingly positions insurance as a proactive method for mitigating risks.

In this article, we’ll discuss the most influential trends in the development of insurtech that will change – or have already changed – insurance products with a focus on a digital-first worldview.

Embedded insurance

Embedded insurance allows non-insurance companies – such as travel agencies, car dealerships, and electronics retailers – to offer insurance policies directly at the point of sale. This approach makes insurance more accessible by partnering with both offline services and digital brands that reach a wide audience, allowing insurers to expand their customer base by offering protection precisely when consumers need it.

Moreover, many customers feel more comfortable purchasing insurance as a value-added service from a trusted brand with which they already have an existing relationship.

Embedded insurance can cover a variety of scenarios, including travel insurance, protection for electronics, car insurance activated immediately after purchase, and ride-sharing coverage through services like Uber and Lyft. Insurtech companies can also partner with online marketplaces to offer customers protection for goods against loss or damage during transportation.

The Internet of Things

The Internet of Things (IoT) refers to a range of devices with sensors and software that connect and exchange data with other devices and systems via the Internet or other computer networks in real time. Examples include connected vehicles, smart home sensors, cameras, and wearable devices.

In automotive insurance, IoT-connected sensors can be used to verify the safe operation of the insured vehicle, reducing the risk of costly insurance claims due to improper handling.

Integrating IoT technologies into insurtech could change the perception and delivery of insurance services, specifically by positioning insurance as a risk-prevention partner rather than just a safety net in case of an accident. For example, a smart home sensor can detect water leaks, smoke, or break-ins and notify homeowners and the insurance company in real time.

Big data analytics

Big data analytics helps insurtech companies extract insights from vast unstructured data sets that exceed the capacity of commonly used software tools to capture, manage, and process data within a reasonable time frame. It involves using advanced techniques such as data mining, statistical analysis, and descriptive analytics to ensure data accuracy, summarize information, and predict future outcomes.

As insurers increasingly collect digital data from a growing range of sources, such as social media, IoT devices, telematics, and historical insurance records, big data analytics allows them to assess risks more accurately, identify unusual patterns and anomalies in claims data, refine existing products based on customer feedback, and develop new premiums that better meet customer needs.

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Artificial intelligence

While big data analytics focuses on understanding data on a large scale, artificial intelligence uses that data to train systems capable of making decisions and performing tasks that usually require human intelligence.

Modern insurance companies and startups require faster, more accurate decisions to replace traditionally lengthy (and costly) insurance processes, and therefore they see significant potential in the use of machine learning. Let’s explore cases where artificial intelligence could reveal its potential.

Automating claims and benefits management

AI systems can review documents and identify patterns that might indicate fraud. For instance, a machine learning model can quickly analyze photos of a car accident, determine whether the incident qualifies as an insured event, and make a decision – all in minutes instead of days. In addition, AI models can examine historical data to detect fraudulent behavior, such as an unusually high frequency of insurance claims or inconsistencies across documents, images, medical reports, or bills provided by the applicant.

Dynamic pricing models

Machine learning models can use inputs from multiple sources, such as driver behavior detected through telematics devices, physical activity and health data from fitness trackers and smartwatches, and insurance claims history, to create personalized insurance offerings.

Chatbots and virtual assistants

Chatbots powered by natural language processing models can provide 24/7 customer support from any device. They guide customers to suitable coverage options, explain policy terms, and resolve common issues such as billing inquiries, claim statuses, policy renewals, and cancellations.

Predictive underwriting

Underwriting is the process by which an individual or entity assumes financial risk for a fee. Machine learning models can analyze numerous criteria based on customer applications, helping to determine how much to charge an applicant or whether to offer them coverage at all. In car insurance, the evaluation criteria may include driving experience, the average cost of repairs for a given car brand, and how often a specific make and model are involved in accidents, according to statistics. For life insurance, artificial intelligence evaluates age, health, medical history, and physical activity.

Drones

Traditionally, insurers relied on manual inspections and risk assessments – a process that was both time-consuming and costly. Now, drones equipped with high-resolution cameras, thermal imaging, LiDAR mapping technology, and gas and chemical sensors can conduct these inspections by capturing detailed imagery and environmental data to assess damage to properties, infrastructure, and vehicles.

Drones can:

• Inspect buildings, roofs, and other structures in hard-to-reach areas, particularly after natural disasters such as hurricanes or floods.
• Capture aerial images to evaluate potential risks for facilities located near fire-prone forests, flood zones, or coastal areas vulnerable to storm surges, hurricanes, or landslides.
• Monitor compliance with safety procedures at construction sites in real time.
• Report the extent of damage or potential risks, allowing inspectors to respond swiftly and effectively.

Drone technology significantly increases the speed and accuracy of assessments, helping insurtech companies to manage risks more proactively. Similar to the integration of IoT in insurance products, drone inspections have the potential to reshape the perception of insurance services, positioning insurance as a partner in risk prevention rather than merely a method of compensating for losses.

Final thoughts

Insurtech is transforming the insurance industry by increasing efficiency through automation, data analytics, and real-time monitoring using IoT devices and drones. The use of the latest technology enables the development of insurance products tailored to the specific needs of customers and helps inspectors make faster assessments based on real-time information.

Last but not least, insurtech has emerged amidst a technological shift that allows for remote work. Employees of insurtech companies can now use digital tools and fast internet access to complete tasks, making collaboration among team members located many kilometers apart easier and more efficient.