The insurance industry has always been data and insight driven, utilizing multiple data sources to make informed decisions on insurance policies for businesses and individuals or determining which claims are fraudulent.
External data sources have become more important to this process as they offer key signals not available in internal data sources: weather, credit scores, technographics, firmographics, regulatory, and governmental. Utilizing these sources is critical to understanding what’s going on in the market and adding context to internal data - leading to more accurate, impactful analytics.
Consolidating external data for analytics is resource and time consuming Explorium’s External Data Platform centralizes access to public, premium, and proprietary external data for business analysts, data scientists, and business leaders
Transforming, matching, and integrating external data is tedious work Explorium’s External Data Platform ML capabilities automatically match and integrate external data with your internal data accelerating time to value
Assessing the value of external data is inexact Explorium’s External Data Platform identifies the relevant external data signals and calculates the uplift in your ML models before deployment
The right external data is a competitive advantage.
Understanding the broader trends in the market and including that in your analytics and models will improve their performance. Integrate external data with your internal sources to improve decisions and outcomes for your business Learn more
Refine customer lifetime value and churn analysis Consumers have more options than ever when deciding on insurance providers. Identifying profitable customers is critical - before they jump to a competitor. Redefine LTV and churn models by enriching your internal data with external data signals such as payment history compared to socioeconomic and income status, social activity, reviews of similar products, and income and claims history. Learn more
Improve customer conversions Increased competition and choice has put pressure on insurance companies to find ways to boost conversion rates. The challenge is understanding which factors could lead to conversion at the start of the cycle, as soon as users submit an initial form. Reliance on internal data alone offers too narrow a scope. External data allows insurance companies to make smarter marketing decisions by understanding which actions would lead to user conversion. As a result insurers can design a better user journey to boost revenue and improve customer engagement. Learn more
Reduce claims fraud and costs Insurance claims fraud costs the industry billions every year. Efforts to reduce fraud without impacting the customer experience is a careful balancing act. Insurance companies need a way to detect fraudulent claims earlier in the process without adding more steps that could create bottlenecks and impact their user experience. Enriching fraud models with external data such as economic information, social media interactions and history, person data, and alternative risk boosts their accuracy. This enables you to offer a much better service to your customers, boost revenue, and reduce churn. Learn more
If you’d like to know how you compare with other organizations in the pursuit of the most relevant 3rd-party data, then don’t miss our latest research.
Explorium’s External Data Platform improves analytics and machine learning. Explorium enables organizations to automatically discover and use thousands of relevant data signals to improve predictions and ML model performance. Explorium’s External Data Platform empowers data scientists and analysts to acquire and integrate third-party data efficiently, cost-effectively and in compliance with regulations.
Information that is available from government records and other sources available to the general public.
We partner with established tier 1, 2, and 3 data aggregators and niche data providers to source premium data. Data aggregators provide raw and modeled data.
Data we acquire, process, and standardize to create derived data. Derived data can be used to enrich internal data and build new or existing ML models
Example data signals for Insurance
Review based information:
Business rating and reviews
Average pricing of businesses in area
Number of sales
Growth and stability indicators
Number of businesses nearby by category
Foot traffic information: number of visits in the area, places people visited on the same day, etc.
Tourist attributes: hotels and attraction characteristics (number of hotel rooms in an area, etc.)
View our Data Gallery to see more examples and learn more.
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