— Murray Izenwasser, SVP, Digital Strategy
We’re excited to launch the blog series, “Under the Hood: Unlocking the Hidden Value in Insurance Data,” a deep dive into the world of insurance data.” We’ve all heard — since Clive Humby, the British mathematician, coined the phrase in 2006 — that data is the new oil. But what value is oil if we cannot refract it into gasoline or many of the other products we use daily? Like oil, data’s fundamental value lies in our ability to extract and use it. In this blog series, we’ll explore how carriers can get the most value out of data by extracting insights and integrating them into every step of the decision-making lifecycle — ultimately optimizing efficiency, offering a better customer experience, and turning this unexcavated data into a goldmine of opportunities.
This is part 1 of a 10-part series where we examine one of the foremost data challenges carriers face today— and how it hinders them from realizing data’s full value.
Data Is Everything. Everything Is Data.
In a world where “Data is everything, and everything is data,” carriers need to leverage data better than ever before.
Every day, a staggering 2.5 quintillion bytes of data are being generated, collected, and harnessed worldwide. And 90 percent of this data, according to Forbes, has materialized in just the past two years. Meanwhile, the global insurance data market, valued at USD 16862.62 million, is experiencing rapid growth and is expected to reach USD 30151.24 million by 2028. *
Hidden within this data are customer insights and business opportunities. But for this data to be valuable, you must be able to find the data you want when you need it. Then, turn this data into information and information into action.
But that’s becoming increasingly harder due to the sheer volume and nature of data. Different kinds of data — transactional data from core business systems and the data collected through other sources (imagery, sensors, warning systems, telematics) — can be scattered throughout a business, making it challenging to marshal in a concerted way. So, while data is everywhere, the question is how do we bring it all together? How do we analyze and extract insights at scale to improve decision-making, create efficiencies, and provide better customer experiences?
As AI’s influence grows, data will continue to play an outsize role, especially in insurance, where customer data has long been the lifeblood of insurance operations. AI can help carriers analyze vast amounts of claims data, credit scores, and unstructured social media activity, enabling them to offer personalized coverage to customers, evaluate risk, and price policies more accurately.
What Hinders Carriers from Unlocking Data’s Full Potential?
There is no Artificial Intelligence without data. Or, for that matter, Machine Learning, Natural Language Processing, or any emerging technologies that hold tremendous promise for the future of business. Data is the key to unlocking insights and patterns buried in databases and applications. For the insurance industry — with its vast troves of customers and other historical data — this presents a huge opportunity. Yet, for this data to be truly useful, carriers must transform all this data into insights that drive action and value.
However, Property and Casualty (P&C) carriers encounter several challenges that prevent them from getting the most out of their data.
We all know that within almost all organizations (and especially in the insurance industry), not all data is accessible to everyone. Finance, marketing, underwriting, and claims departments have different roles and tend to store their data in different locations or information silos. Over time, as each department collects and stores its data, it creates its own silo mirroring the organizational structure.
The Pain It Brings
- Data silos limit the view of the data. Without a comprehensive view, analyzing the data for customer insights becomes difficult. And when decision-makers can’t access crucial customer insights, they miss out on opportunities to strategize, improve customer experiences, and drive competitive advantage.
- Silos prevent relevant data from being shared across the organization, limiting collaboration, stifling innovation, and creating conflict, while negatively impacting productivity.
- Without an enterprise-wide view of the data, it becomes hard to spot inefficiencies and find opportunities for improvement, resulting in dissatisfied customers and loss of revenue owing to poor operational efficiency.
- Siloed databases/applications impact customer service and prevent carriers from moving to digitized underwriting. The manual data intake limits the underwriter’s ability to analyze large volumes of data and identify patterns and trends, which can lead to suboptimal risk assessment and pricing decisions.
- Data silos threaten data integrity. When the same information gets stored across different databases, it can lead to data inconsistencies and poor business decisions.
Breaking Down Data Silos
An organization that digitizes without breaking down data silos won’t access the full benefits of digital transformation. By tearing down barriers between data silos and making data more shareable, carriers can unlock data’s true potential. The first step to breaking down departmental silos is to identify where the data currently sits, how it is collected, and how relevant it is. Once the data has been gathered and audited, and individual teams have identified the challenges with their existing data management system(s), the business can zero in on the platform they will use as their single source of truth, including the systems that will be integrated into it.
Once the data is centralized, everyone will have an up-to-date, holistic view of the information that will help them improve the experience they deliver.
Customer Service: Service agents reacting to complaints will be able to quickly recognize customers, past interactions, previous purchases, and which marketing initiatives they were part of.
Personalization: Marketers can deliver a unique and personalized experience to each customer across their journey by producing the right content on the right channel at the right time, thus increasing customer loyalty and retention.
Sales: Sales agents can use existing data to forecast trends as well as target new prospects similar to and based on their existing customers.
Product Innovation: Product teams can use data insights to understand which products work within each market, where customers are reporting most issues, and identify where to invest.
Decision-making: Giving everyone access to the same platform to view the latest data (appropriately) in underwriting, claims, product development, and marketing. It eliminates siloed versions and delayed decisions caused by different definitions or filters of the same data, for example on quote and sale volumes
This wraps up part one! Stay tuned for our blog post on legacy systems and how they lock away valuable data and insights next week.
* Global Insurance Data Industry Research Report, In-depth Analysis of Current Status and Outlook of Key Countries 2023-2028