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RFP Processing

RFPs for Employee Benefits Insurance

The Problem: Underwriters spend considerable time collecting relevant information from RFP documents and keying data into underwriting applications prior to conducting risk analyses and pricing the proposal. With a surge in RFP volume coupled with market pressures for reduced pricing, merely augmenting staff to accommodate demand is no longer a viable solution. The existing processes and systems entail extensive manual intervention, diverting subject matter experts (SMEs) from concentrating on generating and delivering value to customers.

The Solution: matchRFX for Employee Benefits Insurance streamlines the process of summarizing patient data while ensuring all required topics are covered.

  • Process RFPs for life, short-term disability, long-term disability, dental and vision plans
  • Automatically retrieve RFP documents from file store, Salesforce, or other online sources
  • Extract relevant policy information from RFP documents in multiple formats
  • Automate the census build
  • Post data automatically to rating system for review, analysis and pricing
  • Add additional lines of employee benefits according to your business needs
  • Access cloud-based system or deploy on-premise

RFPs for HR Software

The Problem: Sales teams for HR software invest significant time and expense responding to RFPs, which often comprise multiple files spanning tens of pages, and encompass hundreds of questions and requirements. While the core content of questions and requirements remains consistent across the vast majority, the phrasing of these inquiries varies uniquely within each RFP. Consequently, sales teams must decipher and customize previous responses to align with the specific nuances of each RFP they process.

The Solution: Coming Fall 2024, matchRFX for HR Software streamlines the RFP response process, significantly reducing the time and expense to generate winning proposals.

  • Create RFP proposals, centralize RFP content and manage the end-to-end process
  • Upload sales brochures, product information and other files to build a content library
  • Leverage AI to generate responses to questions, using library content as reference
  • Improve responses as system continuously learns with each RFP
  • Communicate and collaborate with team members, track approvals, and analyze results.

Medical Data Processing

The Problem: Insurance providers need to summarize and process volumes of patient data spanning multiple encounters to aid in medical underwriting. Dozens of key medical topics must be included in the summary, yet the source documents can be arbitrarily long, typically spanning hundreds of pages.

The Solution: Our platform streamlines the process of summarizing patient data while ensuring all required topics are covered.

  • Summarize medical data from patient files including diagnoses
  • Automatically post data to adjacent, integrated systems
  • Improve performance as system continuously learns with each transaction
  • Meet or exceed quality assurance and validation standards
  • Utilize Validation Station for Human-In-The-Loop interactions

Financial Data Processing

The Problem: Insurance providers must extract relevant information from bank statements that list transactions and summaries on multiple institutional investment accounts. There is significant variability in these statements as they originate from multiple sources, contain diverse sets of transactions and may consist of hundreds of pages. Statement processing is subject to strict SLAs for accuracy, turnaround time (TAT), and ability to handle peak volumes.

The Solution: Our platform provides fast processing with high accuracy while scaling to accommodate peak volumes.

  • Extract data from bank statements from multiple financial institutions in multiple formats
  • Post data automatically to adjacent, integrated systems
  • Scale efficiently, horizontally or vertically, to handle peak volumes
  • Meet or exceed processing accuracy requirements
  • Improve performance as system continuously learns with each transaction