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Insurance companies require data to reach optimal levels of success. While the industry has always had a wealth of data, it’s only in recent years that there has been a real push to monetize this vital asset.

However, from underwriting and risk assessment to claims settlement and customer interactions, insurance enterprises today produce and deal with vast volumes of unstructured data—one of the industry’s significant challenges. For example, forms and claim settlements — including images, emails, and other documents — contain precious data that can empower insurers to create holistic views of their customers and optimize processes.

Straive’s data solutions for insurers focus on automating the capture of unstructured data residing in varied sources and diverse formats and unlocking qualitative actionable insights.

Our Capabilities

Damage Analysis

Straive’s proprietary data management platform, Straive Data Platform (SDP), can help accelerate, improve, and streamline rooftop damage analysis and estimation. Until recently, insurance companies had to conduct manual onsite inspections or agent reviews for more minor claims. While drone imagery solutions have helped reduce onsite inspections and improved the claims processing time, it still requires a manual agent for review. As such, SDP accomplishes the following processes:

  • Image preprocessing for optimal image identification
  • A Before and After comparison of images to identify the damage percentage and further map to square feet to estimate the damaged area
  • Scraping and tracking of roofing material pricing to help feed the damage estimation

Claims Processing

Straive’s services around claims processing focus on reducing the time spent by agents on processing every claim and making data easy for any downstream audits.

We can effortlessly extract data from forms, reports, emails, and other free-form text with our Text Intelligence solutions and SDP. Our platform can be customized either to extract sentiment or a more customized concept extraction exercise. Using SDP, we also help reduce any agent bias that may creep into claims processing. By working closely with our clients, we define each data point and utilize a strictly agnostic platform to cover the heavy lifting in extraction so that the human layer is only involved in curation.

Additionally, as paperwork continues to be filed at all odd hours, SDP can also act as a classification engine, identifying the received document types, flagging important and missing documents, and identifying any potential issues at this point rather than later.

Using SDP, insurance companies can ensure their agents are more focused on higher-value tasks than data extraction. With an average scale-up time of four weeks, Straive provides solutions for all your needs to improve the claims process. Claims Processing.png

Roofing assessment

Using computer vision on our proprietary unstructured data platform, SDP, Straive helps insurance companies assess rooftops with drone imagery, extracting critical datasets about the roof itself as well as using before and after photos to help assess any critical damage.

Customer 360-degree

Using SDP, Straive helps insurance companies accelerate customer data acquisition from unstructured data, both internal and external, to get a complete view of your customers in the underwriting process.

How SDP can help

We leverage our AI-based platform, Straive Data Platform (SDP), and SME inputs to conduct intelligent document analysis quickly, allowing us to

  • Identify the customer sentiment in internal and external sources
  • Streamline claim settlements through automated damage analysis
  • Enhance analytics with more data

From rooftop damage analysis to the extraction of relevant data from the many reports in the claims process, SDP can be customized to any insurance provider’s unstructured data needs quickly and at scale.

Apart from the expenses and longer turnaround time associated with manual data extraction, agents tend to bias the data process. Straive works closely with claim agents to understand their end data goals and customize SDP specifically to those needs. Further, SDP uses a combination of rules-based and Machine Learning auto-extraction techniques with human curation to maintain high levels of accuracy.
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Other solutions

  • Enhancing the KYC process during underwriting by automating document classification and extraction to optimize customer onboarding
  • Extracting entities and critical metrics from forms and external sources for underwriters to evaluate risks
  • Assisting damage identification and payout estimation for P&C claims settlements
  • Enabling search for contracts, emails, forms, and other interactions for future audits and compliance purposes
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Image of aim with an arrow inscribed in circle – Data Extraction Services


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