Comprehensive data helps insurers better understand potential risks, leading to more equitable coverage options and reducing the likelihood of misjudged assessments.
Predicting policy
lapse
Inaccurate prediction of policy lapses can result in revenue leaks and missed opportunities for timely customer interventions.
Limited access to alternative data
Traditional data sources can often be limiting. Access to diverse data sources is vital for a holistic risk analysis and policyholder understanding.
Building effective predictive models
Utilizing new sources of data necessitates tools and strategies that can harness these insights effectively for predictive modeling.
Our solution
Omnisient addresses the twin challenges of risk assessment and policy lapse prediction by enabling insurance providers to access a rich trove of alternative data through secure collaboration.
Our platform doesn’t just expose insurers to new data sources; it equips them with advanced tools to build effective predictive models on this newfound data.
This approach enhances the precision of risk evaluation and improves the prediction accuracy of policy lapse.
With our US-patented Crypto-IDs, we ensure this data expansion remains compliant and privacy-focused.
Dive deep into alternative data, refine risk assessment, and sharpen policy lapse predictions with our pioneering solutions.
Enhanced risk assessment
By tapping into diverse alternative data sources, achieve a more accurate and holistic risk assessment to ensure that policy offerings are fair and tailored to individual needs.
Accurate policy lapse prediction
With enriched data and cutting-edge modeling tools, accurately predict policy lapses, allowing for timely interventions and reduced revenue losses.
Access to alternative data
Break free from the limitations of traditional data sources by accessing a vast ecosystem of alternative data, offering richer insights.
Advanced predictive modeling
Harness the power of advanced AI and Machine Learning tools in a secure collaboration environment that can effectively process and model the new data, providing actionable insights for improved policy management.
Featured case study
Enriching Policyholder Data to Accelerate Payouts for Beneficiaries
The objective was to enhance the contactability of policyholders and dependents and expedite the claims process for beneficiaries by updating and enriching the contact details of policyholders and their dependents.