overview

Data and Infrastructure • July 11, 2023

Knowledge Graphs: Unlocking the “DATA-VAULT” in Insurance

A knowledge graph is a data representation that models entities and their relationships in a graph-based structure. It uses nodes to represent entities and edges to connect them. The purpose of a knowledge graph is to capture intricate connections between entities and facilitate comprehension and navigation of these relationships.

For instance, a knowledge graph about people may include entities for individuals, organizations, and places, along with relationships like "works for" or "live in". By presenting a comprehensive and interconnected view of entities and their relationships, knowledge graphs enhance understanding of context and information semantics.

Knowledge graphs find wide application in recommendation systems, search engines, question-answering, and semantic web technologies.

Empowering Insights: Knowledge graphs for data-driven decision making

  • Knowledge graphs combine data from various sources within an organization, providing a comprehensive overview of the data landscape.
  • Stakeholders can use knowledge graphs to form relevant hypotheses and derive informed decisions based on the consolidated data.
  • Knowledge graphs establish meaningful connections between data points, uncovering subtle patterns that may exist within the data.
  • By identifying relationships between data points, knowledge graphs reveal visually distinct clusters of related members, representing communities.
  • Knowledge graphs facilitate the visualization of information flow, enabling the identification of hidden risks and patterns over time in business processes or transactional activities.

Navigating the insurance industry: The role of knowledge graphs in driving transformation

This intensified competition among insurers to enhance customer satisfaction and boost profitability is driving the need for innovative cost-saving measures. Insurers must harness artificial intelligence across all stages of the customer journey and reassess their offerings and customer experiences. Despite having access to a vast amount of data accumulated over their long-standing existence, insurers have largely underutilized this valuable resource.

Insurers often rely on outdated demographic information, with data that can be up to 40 years old or even older. However, this untapped wealth of data holds immense potential, akin to a valuable goldmine waiting to be fully utilized. By harnessing the power of knowledge graphs, this data can be contextualized, analyzed, and effectively employed to enhance decision-making processes, drive innovation, and gain a competitive edge in the insurance industry. 

The application of knowledge graphs unlocks a treasure trove of insights, enabling insurers to uncover hidden patterns, identify emerging trends, and make informed decisions based on real-time, relevant information. By embracing this technology, insurers can tap into the rich and vast resources at their disposal, transforming their operations and strategies for the better.

Unlocking value: Key applications of knowledge graphs for insurance companies

knowledge-graphs-blog-infographic-04
  • Customer Segmentation: Knowledge graphs facilitate customer understanding by mapping customer data and relationships. This enables the creation of focused customer groups for targeted marketing, churn analytics, group-based product pricing, and upsell/cross-sell activities.
  • Product Development: By comprehending the relationships between insurance coverage types and policyholders, knowledge graphs assist insurers in developing new products that align with customer needs.
  • Fraud Detection: Approximately 10% of insurer losses are attributed to fraud, often undetected throughout the customer life cycle. Knowledge graphs assimilate diverse data, enabling the analysis of historical patterns and existing relationships to identify potential fraud and reduce losses.
  • Underwriting: Knowledge graphs enhance customer profiling by revealing data relationships, and assisting underwriters in determining appropriate premium amounts for applicants.
  • Claims Processing: Knowledge graphs streamline claims processing by providing a comprehensive and up-to-date view of all relevant information, including policy details, claims history, and pertinent medical records.

Delving into underwriting: How knowledge graphs revolutionize decision making

  • Improved Data Access: Underwriters often spend a significant portion of their time gathering information about policyholders from various systems. A knowledge graph serves as a centralized repository, storing relevant information like demographic data, medical history, and previous claims. This accessible resource empowers underwriters with a comprehensive view of risk factors associated with policyholders, enabling them to make informed decisions more efficiently.
  • Better Risk Assessment: With an estimated 10% of insurance claims being fraudulent, a knowledge graph aids underwriters in identifying new risk factors and understanding the relationships between different data points. By mapping these connections, underwriters can conduct more accurate risk assessments and make better-informed decisions regarding policy issuance and pricing. This proactive approach helps prevent potential fraudsters from obtaining policies in the first place.
  • Enhanced Customer Profiling: By integrating data from multiple sources and mapping relationships between policyholders and other entities such as employers, healthcare providers, and other insurers, knowledge graphs enable underwriters to construct detailed and accurate profiles of policyholders. This is particularly valuable when underwriting policies for customers in niche markets or with complex medical histories. Additionally, knowledge graphs can reveal patterns over time, indicating shifts in customer behavior that insurers can act upon.

Knowledge graphs offer significant benefits for insurers, revolutionizing their operations and decision-making processes. By leveraging knowledge graphs, insurers gain a holistic view of their data, enabling improved customer segmentation, streamlined claims processing, enhanced risk assessment, and proactive fraud detection. These advantages lead to cost savings, increased customer satisfaction, and improved profitability. 

Quantiphi has been at the forefront of assisting insurers worldwide in unlocking the full potential of knowledge graphs. We have been instrumental in helping insurers harness the power of knowledge graphs to unlock valuable insights, optimize operations, and drive innovation across the globe.

Achieving excellence: Quantiphi's journey in empowering a leading insurer with knowledge graphs

Problem Context:

A Fortune 500 insurer based in the United States faced challenges in identifying areas of premium leakage due to its fragmented data structure. The lack of visibility into data dependencies hindered their ability to pinpoint the causes of premium leakage.

Solution:

To address this issue, a dedicated team consisting of subject matter experts (SMEs) and business analysts was assembled. The team conducted comprehensive interviews with business users to fully understand the scope and nature of the problem. Data sources were carefully evaluated and categorized based on their relevance to the issue at hand. Leveraging this information, a knowledge graph was developed to visually depict the interconnections between the data and highlight the relationships between different elements. Additionally, a dashboard was created to provide a clear visualization of the knowledge graph.

Business Impact:

  • The implementation of the knowledge graph revealed communities of insureds displaying anomalous behavior, indicating potential premium leakage.
  • Identification of policies requiring underwriter attention allowed for the optimized allocation of resources, freeing up underwriter bandwidth.
  • Improved data traceability was achieved through the implementation of data lineage, enhancing transparency and accountability in data management processes.

In summary, the data repositories within organizations represent a vast untapped resource, holding immense potential for unlocking valuable insights. However, the fragmented nature of data storage across different business functions creates obstacles to fully leveraging its power. Knowledge graphs offer a powerful solution by seamlessly integrating diverse data sources and enabling advanced analytics to extract meaningful and actionable insights. To discover how Quantiphi assists businesses in harnessing the transformative capabilities of knowledge graphs, we invite you to visit https://quantiphi.com/ or reach out to our team of experts for further information and consultation.

Sony Ambooken

Author

Sony Ambooken

Start Your Next Gen AI Journey Today

Discover how Quantiphi’s AI-powered solutions can transform your business. Fill out the form, and we’ll help you explore tailored AI strategies to unlock new opportunities for growth.

Thank you for reaching out to us!

Our experts will be in touch with you shortly.

In the meantime, explore our insightful blogs and case studies.

Something went wrong!

Please try it again.

Share