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Intake AI™

Increase speed to quote using intelligent document processing (IDP)

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Convr’s Intake AI engine eliminates manual submission processing by digitally ingesting, preparing and analyzing underwriting documents. For every submission that flows through your business we extract key data points and augment the information with third-party data to broaden and deepen the risk profile. By automating and digitizing the insurance application process, underwriting teams quote faster, with more confidence, enhanced application data and achieve more nuanced insights.

Key Capabilities

Drive Efficiency with Straight-through Processing

Ingest, organize and digitally store all your documents in a single Digital Asset Library, including ACORD forms, loss histories and SOVs - virtually any structured or unstructured document.

Avoid Data Leakage

Collect, analyze and retain all the information you’ve captured in the application process to inform future pricing models and decisions. Benefit from consistency of format and data granularity while assuring historical audit compliance and data sharing across departments.

Realize Faster Speed to Quote

Digitize and centralize the submission data extraction process, transforming both the underwriting and customer experience.

Intake AI Reduces Manual Effort to Process Insurance Applications by

Applying AI to Digital Processing

Intake AI digitally processes submission documents using patented intelligent document processing (IDP) – including any structured or unstructured documents.

Document Library with Submission Bulk Upload, Email or Drag & Drop 

Multiple documents are split, extracted, digitized into a single view with lineage

Certified Extraction

Identifies most credible source of data for underwriting or operations workflow requirements

Editing/HITL Interface

Telling you when review is necessary – user can accept or change

File Prep & Export Templates

Export account information to excel rater or via API to policy systems, rating engines, etc. for customer handoff

Efficient Submission Intake

File Preparation Speed & Accuracy

IDP Wheel

Getting it right from the beginning is essential for a quality outcome. The initial setup of submission information includes applications, loss runs, statement of values, broker forms from producers or insureds and more.

We are able to ingest, digitize and standardize the information within those files and bring them into a single view, in a single place, into a single format. No more gathering, re-formatting and loading into an Excel workbook. No more cutting and pasting and the inevitable errors!

With Convr, file prep is faster, easier and more accurate – as fast as 30 seconds vs. hours to days for some accounts.

Why Intake AI?

Intake AI uses our patented, AI-driven engine with user-inspired capabilities for data customization and insights

  • Empower underwriters to bring their own data

    Easily integrate your own data with Convr’s third-party data sources to gain a holistic view of a given business and to build more confidence in risk selection.

  • Digitize and centralize structured and unstructured data

    Take advantage of Convr’s machine learning P&C models that are pretrained on thousands of ACORD applications, loss runs and other key insurance documents.

loss run

Capabilities

Underwriting Insights from Digitized Intake

Extracted data provides underwriting teams with threshold eligibility scores that include dashboard graphs of loss runs, claims and losses, the ability to compare results with prior year submissions and more.

Patented Capabilities of Intake AI

  • Ingest

    documents in configurable stages. An example would be prioritizing sources such as taking the broker name and address from the email body instead of an ACORD 125 form.

  • Extract

    extract and digitize select data fields for clearance, file preparation and underwriting insights.

  • Navigate

    verify and analyze field-level documents with “High” or “Low” confidence scores to enable underwriters to benefit from straight-through processing and in-line quality control (HITL).

  • Assess

    submission application data from structured and unstructured documents and sources, including the digital footprint constructed in Convr's Risk 360 AI.

  • Visualize

    side-by-side the actual document and structured view to fix and/or validate data elements for underwriting insights and analysis and selection.

  • Validate

    data lineage with insights specific to source derivation, including date last updated, name of the data source and a direct linkage to the source of the data.

Scores

Commercial Auto

Forecasts risk per power unit in the coming 12 months – combining the number of injuries, accidents and fatalities

Workplace Safety

Forecasts risk per employee in the coming 12 months – combining injuries, respiratory illness, poisonings, hearing loss, and skin disorders and fatalities​

Submission Selection & Prioritization

Indicates the relative fit of a submission within underwriting guidelines

Convr at Work​

Learn how Tangram Insurance Services drove real results with Convr submission intake

golden gate bridge
  • Increased efficiency by over 130%
  • Achieved 91% machine read data accuracy
  • Enabled same-day small business insurance quoting
Read the Tangram Insurance Services Case Study

Benefits

Quality Underwriting Experience

Streamline the underwriters’ work experience with more complete and accurate data, clearer insights and heightened decision confidence

Productivity

Prioritize submissions to rapidly narrow risks within appetite and deep dive on selected risks

Speed to Quote

Increase quote-ratios and new business by accelerating the underwriting process from intake to data collection to identifying the right submission questions and answers

Underwriting Efficiency

Drive efficient submission intake, prioritization, underwriting analysis and decisioning with a full suite of AI-infused commercial insurance tools

Customer Experience

Reduce data gathering touch points and the time associated with record retrieval and validation for applicants

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