OSINT Blog / Post

June 19, 2024

Breaking the Limitations of Traditional Risk Assessment with Pre-Check

Claims adjusters at insurance companies are often in the business of making suboptimal tradeoffs. In order to manage caseloads, they have to make time-sensitive decisions, while simultaneously flagging potential instances of fraud or malingering.

Unfortunately, due to data silos and time and resource constraints, adjusters generally lack the ability to consider flags outside of standard case data and documentation, which are typically provided directly by the claimants or insureds. While certain adjusters’ deep experience or keen intuition can help plug the holes, the right technology can instantly enable adjusters across all experience levels and lines of insurance to access broader datasets, quickly spot red flags, and save the organization time and money.

Skopenow works with a number of large insurance carriers to support automating fraud and risk signaling at scale with Pre-Check. To better understand and illustrate the complexities of this issue, we spoke with real end-users from the claims and SIU department of a major insurance carrier before and after adopting Skopenow's Pre-Check, a purpose-built solution for clerical teams, claims staff, SIU investigators and analysts, and management across all functions and levels.

During the course of customer interviews, it became clear that the claims handlers previously relied on time-consuming, inaccurate, and manual methods to assess claims. Handlers were asked to use their intuition and experience when manually reviewing a claim for legitimacy, with the added challenge of only having access to the limited information provided by the claimant.

To reduce and eliminate reliance on time-consuming, manual methods with an overly narrow view of claims, we first wanted to understand the type of information that adjusters typically have at their disposal.

Surface Level Insights

When an adjuster starts a typical case review, they often have access to disparate, narrow pieces of information to aid their decision-making. That may include the:

  • Claim Form: The first document a claims handler will typically see, which includes basic information such as the policyholder's name and policy number, details about the loss or damage, and the date and time of the incident.
  • Policy Details: The claimant's policy documents to determine what is covered under the policy and what the policy limits are.
  • Supporting Documents: When they exist, these can include police reports, medical records, receipts, and other evidence submitted to validate a claim.
  • Claim History: The claims handler can access the policyholder's claim history to look for repeat claims or patterns or inconsistencies in prior claims.

Our conversation with the Skopenow end-user revealed further insights into the challenges that claims handlers face when evaluating insurance claims, and how these challenges can be addressed with automation tools and technologies.

With Pre-Check, customers can automatically ingest and assess a variety of flags without human intervention, including:

  • Behaviors and Keywords: Surface behavior and keyword insights by analyzing photos and text. Skopenow provides 20 different off-the-shelf categories of behaviors.
  • Business Connections: Review subjects for undisclosed business affiliations powered by secretary of state filings, e-Businesses, domain registrations, and marketplace data.
  • Collusion via Link Analysis: Uncover insights and hidden relationships between multiple parties by detecting and analyzing shared data points and assets from across the open web.
  • Public Records: Cross-check 30+ different public record data types, from bankruptcy and arrests to evictions, determining key causes of concern.
  • Stolen or Listed Items: Skopenow can process thousands of VIN numbers as well as stolen items across 15 marketplaces, highlighting any mentions or references.

The key component is open-source intelligence. Knowing the challenges claims adjusters face is an important step in developing new processes, but it’s also crucial to understand how publicly available information can address these issues and transform the way insurance carriers operate.

The Data Below the Surface  (Pre-Check Case Study)

One of Skopenow's insurance partners recognized the potential advantage of integrating publicly available information for investigations and claims. However, the time-consuming process of merging disparate datasets and determining which claimants to investigate posed a challenge. 

Built directly into their claims management system via API, Pre-Check immediately evaluates and highlights key flags around certain behaviors, network associations, and businesses linked to claims. Pre-Check has enabled the insurance carrier to achieve operational efficiency, cost savings, and faster case resolution by processing claims data for fraud and risk signals at scale.

Stepping beyond the surface-level information provided by claimants, fraud signaling tools can analyze claimants' digital footprints and assist claims adjusters in determining risk levels. Pre-Check rapidly searches thousands of internet sources in real-time for well-informed decision-making, encompassing consumer records, social media activity, vehicle ownership records, digital marketplace activity, dark web, and criminal records.

We spoke with an interviewee about the impact of Skopenow's Pre-Check on their claims decision-making process. They emphasized a recent injury claim after an auto accident in which Pre-Check revealed high-risk details, such as an undeclared criminal history, social media photos of the claimant engaging in physical activity despite injury claims, and data showing a connection between the claimant and the doctor. This example demonstrates how using OSINT for scalable due diligence can uncover crucial information that traditional claims assessment methods might miss, ultimately resulting in better-informed decisions and reduced risk for insurers.

Our previous example focused on an injury-related claim, but automated fraud detection, risk signaling, and investigation decision-making can apply to various types of insurance claims, including commercial, property, and casualty, among others. Pre-Check can efficiently assess extensive datasets like caseloads, inventories, or books of business (also known as policies) in bulk, significantly outpacing manual methods and resulting in substantial time savings.

Pre-Check quickly and accurately identifies high-risk claims, enabling claims handlers to prioritize and focus their resources on investigations with the highest likelihood of producing results. Equipped with an automated tool like Pre-Check, claims handlers can swiftly evaluate and triage claims, pinpointing red flags that may suggest fraud and forwarding the case to an investigator.

Scalable OSINT due diligence solutions hold the potential to transform insurance claims. By giving claims handlers access to a wealth of information beyond what claimants provide, they can make more informed decisions about a claim's legitimacy and alleviate the workload for investigators. Insurance carriers that do not adopt these solutions risk using outdated and inefficient claims processes, which can lead to delayed claims handling, increased expenses, and regulatory errors from not evaluating available data. The stark contrast between the information accessible with and without public data underscores the risk for insurance companies that neglect these tools; they may fall behind competitors, suffer losses, and miss crucial insights affecting coverage, liability, and damage evaluations.

Skopenow helps surface critical insights about people and businesses helping claims teams quickly focus on actionable or materially related information.

Pre-Check is available to start modernizing your investigations today. Request a demo and free trial today at www.skopenow.com/pre-check-demo-request to see firsthand how Skopenow can help your organization unlock the power of open-source intelligence.