InsurTech: Transforming the Insurance Landscape with Digital Solutions

How digital insurance solutions revamp the industry

Let’s look at how innovative technologies are driving the industry's transformation. We’ll focus on three key pillars: IoT (Internet of Things), data management, and digital twins.

How technologies are improving various aspects of the insurance industry:

• IoT data acquisition – InsurTech solutions can be embedded with IoT sensors to collect data from various sources such as vehicles, buildings, wearables, etc. Thin can provide insurers with extensive data like driving behaviour, property conditions and health vitals to ensure a general view of risks and help in accurate underwriting, pricing, and claims management.
• Data insights – Effective data management techniques allow insurers to process and analyse large volumes of data efficiently. Advanced analytics and machine learning algorithms can extract valuable insights from the data collected through IoT devices. These insights enable insurers to identify patterns, trends, and risk factors, improving decision-making processes and enabling more precise risk assessment and pricing models.
• Digital twins to assess risks – By creating digital twins, insurers can simulate various scenarios and evaluate risks associated with insured assets. For example, digital twins of buildings can be used to assess structural vulnerabilities or fire risks. This technology enhances risk assessment accuracy, enabling insurers to provide more tailored coverage and pricing.
• Loss prevention and risk mitigation – Digital insurance solutions can leverage IoT devices to monitor and mitigate risks proactively. For example, sensors can spot problems like water leaks, changes in temperature, or security breaches early on. It can help to reduce potential damage and insurance claims, saving money for both insurance companies and the people who have policies.
• Personalised customer engagement – IoT-enabled devices and data management platforms enable insurers to offer personalised services and engage with customers in new ways. For instance, insurers can give policyholders real-time feedback on customers' driving behaviour or provide customised risk management recommendations. This level of personalisation enhances customer satisfaction and loyalty.
• Claims management and fraud detection – Digital insurance solutions utilising IoT and data management can streamline the claims process. Real-time data from connected devices can automatically trigger claims notifications, initiate the assessment process, and expedite claims settlement. Additionally, advanced analytics can help detect patterns indicative of fraudulent activities, reducing insurance fraud instances.

By leveraging IoT, data management, and digital twin technology, digital solutions can potentially transform the insurance sector. It can lead to more precise risk assessment, elevated customer experiences, and increased operational efficiency.

IoT’s role in the insurance industry

The IoT devices can have a dual impact on the insurance industry. On the positive side, IoT solutions can help insurers reduce risk and enhance personalisation by providing real-time data on customer behaviour, like driving patterns or health and fitness habits. Meanwhile, there are concerns about data breaches and cyber attacks, which could compromise sensitive customer information.

Let’s take a closer look at the positive and negative sides that IoT can have on the insurance industry, as outlined in Deloitte's research.

Let's continue with car insurance as an example. In the past, submitting an initial notice of loss (FNOL) could be challenging, especially if accidents caused delays in informing the insurance company. This not only increased fraudulent claims but also left customers feeling dissatisfied. However, with IoT, airbags can immediately alert insurers and speed up the FNOL process - leading to happier customers and reducing fraud.

3. Personalised insurance practices

Insurance companies can offer personalised policies without categorising customers into risk groups. It has led to the introduction of pay-as-you-go (PAYG) plans that calculate premiums based on actual usage, resulting in reduced costs if you use your vehicle less often. Such a system offers greater fairness and flexibility to policyholders.

4. Transformation of the insurance landscape

While traditional insurance used to cover risks like house fires, smart homes equipped with telematics can now detect gas leaks and take preventive measures.

This transformation presents both opportunities and obstacles. IoT devices allow for early detection and prevention of potential risks. Meanwhile, some insurers may need to reconsider their strategies to maintain profitability.

5. Data privacy and security concerns

In some cases, IoT devices may collect data that could be attractive to other industries or represent entirely private information to the customer. It raises concerns about data misuse and the possibility of intrusive sales tactics that could negatively impact individuals' privacy and well-being.

The power of IoT data management in insurance

Data management is crucial in helping insurers understand and leverage the information and actionable insights gathered from IoT devices.

Below are key areas that help insurers to make the most out of IoT data management:

• Data acquisition - gathering IoT data from multiple sources, such as wearables, homes, vehicles and industrial equipment, is a complex task, and data management establishes mechanisms to gather such data effectively.
• Data storage - it's common to use cloud-based storage solutions to manage the information produced by IoT devices. However, insurers may also use data lakes or warehouses for storage and future analysis.
• Data governance - encompasses establishing guidelines for managing information, ensuring its high quality, and overseeing it throughout its lifespan. It helps to ensure that the data collected is reliable and easily accessible when needed.
• Data processing and analytics – to gain insights from IoT data, it's necessary to do some preprocessing and analysis. It involves using machine learning algorithms to identify data patterns, trends, and anomalies. Moreover, the processing and analysis are often required in real-time for timely decision-making. Insurers can use stream processing technologies to analyse data once it's gathered - enabling them to monitor events or incidents in real-time while sending alerts if needed.

How digital twins change the insurance sector

The digital twin is the technology that allows the creation of a digital representation of any physical object. With its help, companies can extract "virtual data". The integration of digital twins as a source of information holds great potential for the insurance industry in years to come.

In the past, insurance companies have used historical data to perform risk assessments. But now, thanks to digital twin technology, they can predict and evaluate any potential risks with ease.

The combination of digital twins and IoT encourages insurers to switch to a new approach focusing on preventing or minimising damages rather than simply providing compensation. To gain a better understanding, let's consider an example:

Imagine a smart factory that uses digital twins and IoT technology. The factory’s complex machinery, each equipped with IoT sensors and represented by a digital twin.

Digital twins constantly combine and analyse data that are represented by physical assets, such as temperature, vibration, etc. When a machine has abnormal behavior, special sensors detect it and transfer data to its digital twin. The twin then simulates the potential consequences - how likely the device is to break down and how much fixing or replacing will cost.

Based on those predictions, digital twins can notify the maintenance team when to fix machines so they don't break unexpectedly. It helps keep everything running smoothly and saves time by only fixing things that need it instead of adhering to a set maintenance schedule.

In addition, digital twins can use all the gathered data to identify trends and patterns, which can be later used to improve production processes, save energy, and produce less waste.

To sum up, digital twins can help to improve the following insurance processes:

• Underwriting - more accurate prediction of potential risks.
• Claims processing - facilitated claims processing.
• Fraud detection - duplicating the environment where the damage occurred in virtual space helps to assess whether or not the claim is fraudulent.