Efficiency and accuracy are crucial in commercial insurance. Pibit's AI-driven platform revolutionizes loss run analysis, transforming traditional manual processes with unparalleled speed and precision. This solution empowers commercial underwriters to make data-driven decisions, enhancing overall risk management strategies.

Uplifting Underwriters

Pibit’s AI Solution for Loss Run Analysis

The commercial insurance industry has traditionally relied on manual processes for managing loss runs. This time-consuming approach hinders efficiency and accuracy in underwriting for commercial insurance companies. Underwriters play a crucial role in analyzing loss run data, which encapsulates critical information about an insured entity's claim history, including claim dates, types, amounts, and status. This manual data processing can lead to several pain points:

  • Slow Quote Generation: Extracting data from loss run documents can be a lengthy process, delaying quote generation for customers.
  • Backlog of Submissions: Manual data entry can create a backlog, leading to missed submissions and frustrated customers.
  • Increased Errors: Manual data entry is prone to errors, impacting the accuracy of risk assessments and potentially increasing loss ratios.

Pibit's AI-powered Loss Run Analytics

Pibit's solution tackles these challenges by offering an automated and efficient loss run analysis and analytics platform for commercial insurance companies. Submissions can be uploaded through various channels, including email, SFTP, API, and the Pibit user interface. Our AI models, powered by Machine Learning (ML), Natural Language Processing (NLP), and Computer Vision (CV), automatically extract data from loss run documents, regardless of the template used. A human-in-the-loop process ensures 99.9% accuracy in data extraction.

Comprehensive Reports and Actionable Insights

Pibit generates a variety of reports that provide valuable insights for commercial insurance companies. These reports include:

  1. Loss Run Data
    Detailed reports on loss incidents include claim numbers, dates, loss types, and associated loss amounts.
  2. Key trends and patterns
    • Loss Run Summary: Overview of the insured account with key metrics like number of claims, open/closed claims, and total incurred values.
    • Loss Summary by Year: Year-wise trend analysis of loss runs, including details like paid, reserve, and recovery amounts.
    • Claims Summary by Year: Analyze trends and patterns over time, providing insights for future risk management strategies.
    • Loss Distribution: Identify claim range and the number/percentage of claims impacting overall losses.
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  3. Analyze why losses are happening
    Gain a deeper understanding of factors contributing to losses, such as causes of injury, body parts affected, occupations most at risk, claim loss types, and state-wise claim distribution.
    Uplifting UnderwritersUplifting Underwriters
  4. Track top losses and Top delayed claims
    Identify high-impact losses and areas for improvement in claims processing times.

These reports are fully customizable to meet the specific needs of each commercial insurance company.

Benefits of Pibit's Loss Run Analytics

By leveraging Pibit's solution, commercial insurance companies can achieve several benefits:

  • Streamlined Workflows: Automate loss run data processing, freeing up underwriters' time for more strategic tasks.
  • Faster Quote Generation: Generate accurate quotes quickly, improving customer satisfaction.
  • Reduced Errors: Eliminate human errors associated with manual data entry.
  • Data-Driven Decisions: Gain actionable insights to optimize risk assessments, pricing strategies, and loss prevention efforts.

Embrace Analytics for a Competitive Advantage

In today's dynamic commercial insurance landscape, embracing data-driven analytics is no longer a luxury; it's a necessity. Pibit's Loss Run Analysis & Analytics empowers commercial insurance companies to make informed decisions, improve operational efficiency, and achieve a competitive advantage.