Data is the lifeblood of insurance: data allows insurance companies to judge risks, set a price to them, and offer protection to their customers. Historically, insurers have drawn from standard sources like demographic data, health data, traffic patterns, and environmental data to understand large groups of people and their risks to provide each segment the best product. Now, with data streaming into insurance organizations from nearly every angle—from social media to the billion-strong Internet of Things—insurers have more data than ever before to fine-tune their risk profiles and offer more personalized products to micro segments of their customer base. However, driving value from huge volumes of data requires a mature data management framework that leverages a modern data platform to handle the complexities of formatting, new regulatory responsibilities, and the need for security posed by large-scale data engineering.
In this blog, we’ll give an overview of why data management is a necessary component of insurance in the digital era, the main challenges of the process, the added benefits of a successful data management strategy, and where to start.
The basics of data management
Challenges of herding data
Insurers are tied up in more data streams than ever before, with historical enterprise data accumulating alongside third-party providers like actuaries. Additionally, increasing digitization of processes generates far more information overall from everyday interactions with customers, distributors, and other partners. All these different sources pose a challenge for insurers trying to chart their data environment, as data can enter an organization ad-hoc wherever they are being used, leading to numerous distinct data management workflows across the enterprise.
Corralling these together, once they’ve been identified, raises its own problems. Owing to the different formats and structure of the information, centralizing access to all data can become a convoluted technological challenge with expensive solutions. Plus, deciding how to organize data is not merely a technical question, but a question of how the business intends to drive value from its data—another case where the involvement of the full enterprise is necessary to achieve the business objective of a tech initiative.
There are new risks associated with modern data management too. Security is always a central priority, and establishing rigorous data governance goes hand in hand with modernizing a business’ data environment. This will be even more crucial in light of recent regulatory changes that require documentation and reporting on a much larger scale. These changes will make data management more costly and intensive, especially for insurers without a modern data platform.
Taken together, these challenges can make effective data management seem daunting. However, organizing and maintaining data streams with intention is not optional for modern insurance companies—already this is a deciding factor of success in the digital era, and mastering its basic tenets early can help construct a launchpad for future growth.
Critical components of data management
Data management is a broad area of focus, but four fundamental components make up the core of any data management strategy. These components are tasks that are likely already being performed in one way or another within a business, often on the side and duplicated across departments. The goal of a data management strategy is to optimize these tasks and unify data within a single modern data platform.
- Organize data – Consolidate data coming from different silos, sort and distribute the data to enable effective use
- Enhance data quality – Assess and validate data to empower business intelligence analysis
- Devise a security framework – Ensure the safety of proprietary and customer information, along with thorough documentation for legal purposes
- Data storage and backup – Maintain ready and reliable access to data, along with failsafe procedures to protect data and limit downtime in case of crashes
These four components give insurers the foundation to operate with efficiency in a data-driven industry. This is the first step to centralizing and democratizing access, enabling more users to drive business value from the data by gleaning actionable insights to inform their decisions. Additionally, with more data readily available, businesses can apply advanced artificial intelligence and machine learning techniques to develop new capabilities. For example, fraud detection, which has already been significantly automated in the financial services industry, stands to become much more efficient in insurance through data-powered algorithms. The same is true for risk management and claims, where machine learning algorithms can quickly formulate a preliminary adjudication in seconds.
Data management can lead to new or more customized products and services based on formerly unseen consumer trends that fulfill important needs, as well as generating improvements across the customer experience—in portals, personal assistance, and self-service. These benefits are felt by both the consumer and insurer, building trust and satisfaction in customer relations.
The data-driven future
Insurers are still in the early stages of uncovering the hidden potential of their data, but the field is moving fast. Investment in predictive modeling and other leading-edge AI functionalities is growing as early adopters demonstrate their value, and InsurTech’s insights become more mainstream. Like the financial services industry, insurers are discovering new revenue streams and business models made possible by the cross-dimensional value of data. But all of this depends first and foremost on a mature data management strategy—the effective and transparent gathering, storage, and distribution of data on a modern data platform. No matter how far ahead or behind the technological curve a business may be, improving data management remains a basic driver of growth; it bolsters operational efficiency and leads to better customer experiences. Though the challenges are imposing, building effective data management is a necessary step to success in the digital era.
If you’re ready to leverage new insights to drive business growth, ValueMomentum can help. Check out ValueMomentum’s Modern Data Platform services to see how we can elevate your data management strategy.