Unleashing the Potential of Data in Insurance – The Road Ahead | Blog
Leading insurance organizations seek to be more data-driven in their business decisions by harnessing the full potential of the data that resides within their enterprise boundaries. With the evolving technology landscape, real-time experience management, and explosion of data types, insurers are increasingly leveraging real-time insights to improve customer experience. In this blog, we will explore the potential benefits for carriers of unlocking data in the insurance value chain.
Insurance enterprises are facing a tough business environment marred by macroeconomic challenges, heightened natural catastrophes, and unfavorable interest rates. This is creating an urgency to re-evaluate underwriting and pricing models by taking data-driven approaches.
Data can help insurers unleash the next growth wave, enable targeted cross and up-selling generated through higher customer engagement levels, and provide a 360-degree view of their customer needs. For example, embedding data and analytics and Artificial Intelligence and Machine Learning (AI/ML) models within the claims workflow can enable zero-touch insurance claims transactions. The digital interaction process can flow seamlessly from intaking all filed claims consistently across channels, validating and assigning complexity scoring to each claim, segmenting and routing the claims based on complexity, to finally settling them as quickly as possible.
Infusing intelligence across insurance operations while investing in data and analytics capabilities can generate a surplus economic value of US$ 874 billion, according to Everest Group research, as illustrated below.
Source, Everest Group
However, the industry faces challenges to effectively unlock the full potential of data in insurance, including:
- Siloed and scattered data: Insurers face a high data spread across disparate systems, business lines, functional areas, and channels preventing them from gaining a 360-degree customer view, resulting in high integration costs
- Inadequate enterprise-wide data strategy: Insurers need to foresee the entire insurance lifecycle to democratize enterprise-level data and analytics objectives and define how they can manage data as an asset and drive critical business decisions
- Attraction and retention of skilled talent: Employees with technical expertise and domain-specific skills are scarce
The changing road ahead
Insurers are not only striving to make data-driven decisions but also beginning to explore new business models by combining available big data with advanced AI and ML capabilities.
Insurers are shifting from being risk mitigators to playing more of a risk avoidance role with data, cloud, and platforms being their foundational components. Digitization of the value chain, new business models, and underwriting transformation are helping insurers expand their roles from underwriters to risk decision partners who predict unforeseeable risks and ensure protection.
Data from connected devices is becoming a prominent source to assess and prevent risks. To illustrate, in the auto insurance industry, sensors, blind-spot assist, collision avoidance tools, and other safety systems have already been pre-built into vehicles using behavioral data to help improve safety.
Vast data stores are opening up opportunities to price risk more accurately and offer personalized product structures. For instance, utilizing climate and other third-party data empowers insurers to assess geographical areas that present greater catastrophic risk and charge higher premiums instead of measuring these types of risk through traditional approaches.
Deploying AI and other latest technologies not only assists with ingesting unstructured data but also helps generate actionable insights that previously were unavailable to underwriting and claims teams. Insurance data and analytics spend is growing at an accelerated rate of over 25% annually as insurers look to transition to being data-driven enterprises.
Leveraging data from different types of sources such as wearables, internet of things (IoT) sensors, and telematics through clients’ lifestyles and behavior, insurers are embarking on a new age digitized underwriting process. Smart loss capture and IoT sensors are expected to bridge the gap between the traditional claims processing mechanism to zero-touch claims transactions.
How will the insurance industry progress toward a data-driven approach?
Insurers need to actively engage with the ecosystem of data generated by the insurance enterprises as well as information coming in from external sources such as InsurTechs, and services and technology partners. By doing this, insurers can create and implement strategies that will lead to unmatched automated decision-making support that they can leverage to drive growth and efficiency and extract maximum value.
Source, Everest Group
Data will be a central driving force to strengthen competitiveness in the industry moving forward – allowing carriers to leave behind their traditional approach of solely being risk protectors and move them toward being risk preventers.
As insurers look to become data-driven, data centers and cloud services can enable companies to respond to evolving customer needs, improve resiliency, instill agility, and drive enhanced operational efficiency. Similarly, leveraging AI/ML models and predictive analytics offer a major solution to the challenge of providing real-time actionable insights. Insurers that can create true differentiation and impact using internal and external data will be able to future-proof their business and be seen as leaders in times to come.
To learn more, check out our State of the Market Report 2022 – Unveiling the Economic Value of Data and the Road to Actualization. To discuss more on these topics and share your perspectives with our analyst team, contact [email protected], [email protected], [email protected], and [email protected].