Seenity’s retrospective analysis is more than just a comparison of underwriting and claim data—it’s a dynamic system that integrates advanced data analytics and AI to continuously refine risk assessment. By evaluating risk components identified at underwriting against those realized during a claim, Seenity ensures a detailed examination of discrepancies or consistencies, leading to highly accurate fraud
detection and risk evaluation.
At the core of this process lies Seenity’s unique ability to connect insurance companies to immediate, real-time risk components. This vision is executed through a highly secure and efficient data transport mechanism that injects up-to-the-minute data into predictive models. The platform’s ability to integrate real-time data isn’t limited to simple updates; it enriches AI models, enabling insurers to assess evolving risks with unparalleled accuracy.
A cornerstone of Seenity’s innovation is its big data infrastructure, which continuously indexes risk components with a focus on two critical dimensions: time and location. This capability allows insurers to analyze risks as dynamic, context-dependent entities rather than static data points. For example, a claim for flood damage can be cross-referenced not only with historical weather data but also with real-time environmental conditions at the specific location and time of the incident. This granular level of detail ensures that any anomalies, such as claims inconsistent with actual conditions, are flagged promptly.
Furthermore, Seenity’s platform doesn’t just react to claims—it proactively monitors and indexes potential risks across its database. By continuously updating and refining risk models with real-time external and internal data, insurers can maintain an up-to-date understanding of risk landscapes. This process not only enhances fraud detection but also empowers insurers to adjust underwriting criteria dynamically, ensuring policies remain aligned with current realities.
Seenity’s expertise in linking risk to time and location extends beyond the claim itself. It enables insurers to identify patterns, detect trends, and predict future risks. For example, if a particular region experiences a spike in accidents due to changing road conditions, Seenity’s platform can quickly highlight this trend, allowing insurers to adjust
underwriting models for that area or introduce targeted policies.
This seamless integration of real-time data and sophisticated analysis represents Seenity’s commitment to transforming how insurance companies perceive and manage risk.
By providing an ever-evolving, context-aware risk model, Seenity equips insurers with the tools to not only detect fraud but also enhance customer trust and improve overall operational efficiency.
.
