Insurance is a data-driven industry, where it is common to make use of multiple data sources in decision-making processes.
External data sources are becoming more important when it comes to detecting potentially fraudulent insurance claims. External data offers key signals not available in internal data sources: weather, credit scores, technographics, firmographics, regulatory, and governmental.
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 them in predictive models improves their performance. Enrich your internal data with external data signals to gain better insights and improve business outcomes. 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 improve 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. 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.
Insurance claim 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 alternative risk boosts their accuracy. This enables you to offer a much better service to your customers, boost revenue, and reduce churn.
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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