LOB – COMMERCIAL PROPERTY

Workflow Summary with AI Insights

Use Case #CA2

Description: Visualizing the performance matrix by Adjuster utilizing AI

The volume of claims processed on any given day can be overwhelming for the Managers and Examiners in the Claims Department. Massive amounts of data flow into the Claims Management System through documents and conversations with involved parties to the claim. How can you accurately track the performance of your claims team? Insights, lots and lots of insights!

The Charleeā„¢ Insurance Insights Engine (patent pending) utilizes Artificial Intelligence and Machine Learning with Natural Language Processing (NLP) to help monitor the Claim Examiner’s performance, including the progress towards resolving a claim. In addition, the increased severity of claims with specific Topics and Entities can be closely measured and evaluated. The Claims Manager can quickly identify and take appropriate action to improve the job performance of the claims team.

Complete this form below for more information:

    Company Name (required)

    Your Name (required)

    Your Email (required)

    Telephone No : (required)

    Severity Analysis for Hurricane Claims

    Use Case #PT2

    Description: Key Insights Comparing Hurricane Severity

    According to the National Oceanic and Atmospheric Administration (NOAA), there are an average of 17.7 hurricanes every decade. The Property and Casualty Insurance Industry struggles with massive losses from these storms every year. The severity of these weather-related claims, including litigation costs, can be challenging to analyze quickly due to the volume, the type of loss, specific damage to the property, and the late reporting of the claim.

    Claims Managers and Underwriting Analysts can benefit from Artificial Intelligence-generated insights to provide severity comparisons of the significant storms. The Charleeā„¢ Insurance Insights Engine has 40,000 plus insights. The Charleeā„¢ solution was developed by analyzing over 30 million claims. Charleeā„¢ identifies critical topics, events, and entities and interprets the unstructured text in the claim file notes and internal and external documents utilized in the claims process. Charleeā€™s insights can assist the Claims Examiner in potential cost savings and avoid litigation.

    Underwriting and Claims Managers can leverage the Charleeā„¢ Insurance Insights Engine for better and more confident decisions for future storm seasons.

    Claims Insights

    Use Case #PT3

    Description: The Charleeā„¢ dashboard provides the Claims Examiner a quick and easy view of A.I. insights for the Cause of Loss and LOB, so the appropriate action can be taken.

    Claims Examiners are the critical link for customer satisfaction. The volume of claims can overwhelm the most accomplished Examiner. How can you ensure that nothing slips through the cracks, which can cause the claim cost to increase? The Charleeā„¢ Insurance Insights Engine presents valuable Quality Control (QC) Alerts and Red Flags (RF) for the Examiner to have confidence in deciding the proper course of action and decisions in investigating and resolving the claim.

    The Charleeā„¢ Insurance Insights Engine dashboard is intuitive and straightforward for the Claims Examiner. When the claim is received, the clock starts running for legal compliance and other deadlines. Your claims team will significantly benefit from A.I. generated insights in meeting these deadlines and controlling costs.

    RedFlags (RF), Quality Control (QC) Alerts and Recommendations for the Claim Examiner

    Use Case #LA2

    Description: The Charlee A.I. generated insights by claim.Ā  They are presented as RFs, QC Alerts and Recommendations based on industry best practices for the Claims Examiner to review and take the appropriate action.

    The Charleeā„¢ Insurance Insights Engine has prebuilt Red Flags (RF), and Quality Control (QC) Alerts to aid Claims Examiners in processing a claim starting at the First Notice of Loss through settlement. The Red Flag Alerts signal the Claims Examiner that there are potential indicators of fraud, potential litigation as well as possible high severity. The Quality Control Alerts provide instant feedback to the Claims Examiner to follow-up taking appropriate steps in the claim process. The Quality Control Alerts follow industry best practices as well as assist in meeting government regulatory compliance.

    Claim Severity Management

    Use Case #PT1

    Description: The Charleeā„¢ Insurance Insights Engine provides Claim Examiners and Managers a 360 degree view of all the structured and unstructured data to better manage the severity of the claim.

    Low impact speed collisions with soft tissue injuries are the number one issue in addressing claim severity in the automobile line of business. The proper identification and classification of these types of damages are critical to identifying, tracking severity, and potential litigation.

    The Charleeā„¢ Insurance Insights Engine provides the Claim Examiner to accurately identify track injuries so the proper course of action can successfully resolve the claim. The Power of Artificial Intelligence Insights will reveal hidden patterns leading to high severity. Charleeā„¢ will give your claims team the ability to discover these patterns quickly, learn from them, and be ready for the proper actions to ensure a quick and fair settlement.

    FOR MORE INFORMATION

    RedFlags/Quality Control Alerts for Potential Fraud

    Use Case #SF1

    Description: The Charleeā„¢ Insurance Insights Engine (patent pending) has over 40,000 insights to help Claims Examiners identify potential fraud.

    Insurance Fraud is a significant problem for the Insurance Industry and the Consumer. The Claims and Underwriting teams need to leverage Artificial Intelligence-generated Insights to identify patterns and activities for potential fraudulent claims and policies.

    The Special Investigation Unit (SIU) is responsible for investigating and bringing these claims to a proper conclusion. The Charleeā„¢Insurance Insights Engine provides A.I. generated insights for identifying QC Alerts (industry best practices) and Red Flags pattern recognition to identify suspected fraud schemes and behavior.

    The ability to leverage the correct data at the right time for the right person to make the right decision for the proper disposition of suspected fraudulent claims is critical in the avoidance and mitigation of fraud. Charleeā„¢ gives your anti-fraud team more power in discovering essential insights in the unstructured text in files.

    Open Claims Predicted for Litigation, and Litigation Avoidance

    Use Case #LA1

    Description:Ā  Charleeā„¢ provides a quick view of open claims predicted to be litigated, but have not yet fallen into the litigation category.

    The power of Charleeā„¢ for litigation prediction allows the Claims Examiner and Manager to identify the claims at risk for possible litigation, allowing the claim handler to take action to resolve the claim efficiently and promptly. The Charleeā„¢ Insurance Insights Engine (patent pending) will alert the user weeks before the claim falls into litigation. Artificial Intelligence and natural language processing, coupled with Infinilyticsā€™ proprietary insights, brings these predictions with over 80 percent accuracy.

    Assignment of Claims to the appropriate Examiners

    Use Case #CA1

    Description: Ā  Claims are flagged at the First Notice of Loss and throughout the life of the claim, assisting in the assignment to the appropriate level claim handler.

    The Charleeā„¢ Insurance Insights Engine provides the claims team the capability to Fast-Track appropriate claims with no issues with coverage, liability or litigation. If the claim has no Quality Control (QC) Alerts, Red Flags (RF) or the propensity for litigation, Charleeā„¢ clears the claim for an efficient resolution.

    Starting with the First Notice of Loss through the final settlement of the claim, Charleeā„¢ constantly analyzes the structured and unstructured text in the claim file, scanning all of the documents and external data, for patterns of high severity, litigation, and potential fraud.

    Average Claim Settlements Compared by Incidents

    Use Case #RC1

    Description: Analysis of various loss types and Average Costs by CAT events

    The Charleeā„¢ Insurance Insights Engine (patent pending) provides Artificial Intelligence-generated insights that allow quick and accurate data comparisons and claim metrics of significant weather events over a specified period. Underwriting and Claim Managers can leverage these insights for accurate reporting to Regulators, improved risk analysis, and planning for future events. Regulatory data calls can be accurately and quickly answered.

    Regulatory Data Calls

    Use Case #RC2

    Description: Charleeā„¢ provides key insights to ease and speed required compliance reporting.

    The Charleeā„¢ Insurance Insights Engine (patent pending) quickly provides near real-time insights from your Claim Portfolios for accurate and efficient reporting to Regulators. Whether it is monitoring claims reserves, settlements, litigation, or mandated reporting of suspected fraud, Charleeā„¢ gives your Risk Management and Claim Teams the ability to view and capture the necessary data accurately and efficiently quickly.

    Key Risk Factors and Emerging Risks

    Use Case #PRI1

    Description: Charleeā„¢ quickly provides risk insights from claims that helps with accurate and efficient risk analysis for Underwriting.

    The Charlee Insurance Insights Engine (patent pending) provides a great resource for Underwriting Management Risk Analysis in evaluating and managing portfolios. Previous years of claims data can be leveraged for powerful Artificial Intelligence generated insights for a good understanding of prior losses. These Insights can help an Underwriting Manager develop and monitor an efficient and effective Underwriting strategy, including risk selection and endorsements.

    Loss Development Analysis

    UseCase #PRI2

    Description: A Loss Triangle analysis chart can be easily created for visualization of various risk indicators extracted from unstructured data.

    Charleeā„¢ will extract various insights hidden in unstructured data to identify key factors leading to various claim development patterns. For example, an Underwriting Manager can use Charleeā„¢ to determine Loss Triangle Patterns on claims that have elements such as distracted driving, wind driven rain and other topics. Additional filters on various claim attributes help gain a deeper understanding of various loss patterns. Understanding these patterns assists in developing effective risk selection as well as appropriate endorsements and overall portfolio management.

    Loss Ratio Analysis by Agent

    Use Case #PRI3

    Description: Underwriting Manager can analyze the Loss Ratios by Agent and State.

    Charleeā„¢ will analyze claims under each agentā€™s portfolio and reveal key factors related to loss ratios. Various topics from unstructured claims data are extracted and analyzed with these factors. Understanding the agentā€™s loss ratio patterns help identify the strengths and weaknesses of their portfolios for improved risk selection.

    FOR MORE INFORMATION