Title: Leveraging POI Data for Insurers: A Fresh Perspective
Geoff Michener, heading the esteemed dataplor, a trailblazing startup, focuses on equipping companies to triumph globally via top-notch geospatial data. In the real estate and insurance sectors, risk assessment and premium setting remain challenging tasks. Based on a Swiss Re report in 2023, a staggering 60% of the $280 billion losses caused by "natural catastrophes" worldwide remained uninsured, with property information gaps being a significant contributor.
POINT-OF-INTEREST (POI) DATA - THE SAFE HAVEN?
Addressing this gap, POI data can offer insurers deeper insights into property characteristics, market makeup, and adjacent risks. This data assists in refining underwriting accuracy, enhancing risk modeling, and accelerating key processes. But how exactly can insurers leverage POI data, and how can they maximize their potential in navigating present risks and preparing for future challenges?
GETTING STARTED WITH POI DATA
In a fundamental sense, insurers can capitalize on POI data to derive detailed, specific insights that bolster underwriting – the methodology insurers use to evaluate risk and establish coverage terms and pricing. Attributes like property type, business characteristics, industry composition, and neighboring risk factors provide a comprehensive appraisal of a location's risk profile. Identifying a business's type, age, and composition of surrounding establishments can further empower insurers to conduct risk assessments tailored to market dynamics.
WHAT INSURERS CAN DO:
- GATHER POI DATA: Insurers can resort to various data gathering methods, such as crowdsourcing or physical surveys. Advanced options, however, involve utilizing POI data providers. If you opt for the latter, ensure thorough vetting, focusing on the provider's data validation, real-time updates, and sourcing & verification methods.
- AUDIT DATA REGULARLY: Frequently conduct data audits to uphold accuracy and currency, particularly in critical markets and high-risk properties.
- INTEGRATE DATA INTO UNDERWRITING MODELS: Enhance existing risk models by incorporating your POI data, prioritizing the addition of key property and neighborhood attributes to boost precision.
ADVOCATING FOR DATA LITERACY
Property and casualty insurance market growth is predicted to hit $757.5 million at a compound annual growth rate of 8.8% between 2023 and 2028. To remain competitive in this market, insurers should prioritize data accuracy and education on how to tactically employ POI data to enhance risk assessments and automated decision-making processes. To tackle ensuing challenges, they'll also need to address the following hurdles.
WHAT INSURERS CAN DO:
- ADOPT DATA GOVERNANCE POLICIES: Establish stringent internal data standards, focusing on data accuracy, timeliness, and relevance.
- ADDRESS TECHNICAL CHALLENGES: Integrating new data sources—like POI data—into complex insurance systems might necessitate specialized technical expertise. Consequently, insurers will likely need to invest in visualization tools for effective POI data utilization.
- LAYER POI DATA WITH RELEVANT DATA SOURCES: This may include weather patterns, demographic information, and historical claims data. The process necessitates data cleaning, standardization, and spatial analysis.
SHIFTING FROM REACTIVE TO PROACTIVE RISK MANAGEMENT
Insurers can utilize their POI data to move from reactive risk management to proactive risk management. By evaluating both real-time and historical data, insurers can forecast emerging threats and warn policyholders. For example, by assessing nearby construction sites, hazardous materials, or demographic changes, insurers could alert clients to potential risks before they materialize and provide mitigation strategies.
WHAT INSURERS CAN DO:
- MONITOR INDUSTRY-SPECIFIC TRENDS: Track industry developments and geographic areas to anticipate emerging risks, such as increased climate-related vulnerabilities.
- ADJUST UNDERWRITING CRITERIA: Develop underwriting guidelines that can adapt based on POI data insights. This ensures flexibility in response to evolving market conditions.
- SET UP REAL-TIME ALERTS: Implement systems that monitor changes in POI data, such as new construction or alterations in neighboring businesses, to proactively alert underwriters and policyholders.
- LEVERAGE HISTORICAL DATA FOR TREND ANALYSIS: Evaluate historical trends to predict potential future risks and tailor policy offerings accordingly.
Insurers can better navigate complex risk environments, identify new opportunities, and become trailblazers using resources like POI data. By leveraging high-quality, reliable location data, insurers can stay nimble, well-informed, and prepared to tackle emerging challenges.
In the realm of trailblazing insurance companies, Geoff Michener, the leading figure at dataplor, underscores the importance of Geoff Michener in harnessing the power of geospatial data to help companies succeed globally. By integrating Point-of-Interest (POI) data into their risk assessment and modeling processes, insurers can gain a more comprehensive understanding of property characteristics and neighboring risks, leading to improved underwriting accuracy and enhanced risk management strategies.
