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PREDICTIVE EXPERTISE ACTUARIAL RESEARCH LAB

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PEARL

The Vision

The Power of PEARL

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When Michel Hebert took over R&D for the U.S. market, he had a vision of pursuing profitable business solutions for our clients. His goal was simple, to use the power of predictive modeling to improve mortality assumptions, promote positive distribution growth, and maximize client profitability.

Michel's extensive knowledge in data analytics and mortality management led him to develop our first predictive modeling tool for the Final Expense Market. This tool has provided guidance to many of our senior market carriers on the areas they needed to navigate to maximize their returns. The success of this tool led Michel to grow his team of data scientists and actuaries to have the best predictive modeling expertise the market has to offer.

This team created our Predictive Expertise Actuarial Research Lab "PEARL". Precision, rigorousness, and a passion for providing real value for our partners are the principles that this program is founded on and we are excited to introduce it to you, our partners and prospects.

Whether your product is Fully Underwritten, Simplified Issue, or Accelerated Underwriting, we've got you covered with the predictive power or PEARL.

Michel Hebert

Michel Hebert

Michel Hebert

FSA, FCIA
Vice President, Actuarial

PEARL AUW - Accelerated Underwriting

Key Features:

  • Based on PEARL Fully Underwritten (FUW) model

 

  • Monitors actual mortality slippage from Accelerated Underwriting (AUW) programs

 

  • Provides granular results on the slippage by age, sex, risk class, face amount bands, and more.

​​​​​Carrier Applications:

  • Obtain detailed results of your company's observed mortality slippage

 

  • Enables a more precise cost/benefit analysis of increasing your AUW limits

 

  • Improve profitability/straight-through processing rate with the use of UW tools

PEARL SI - Simplified Issue

Key Features:

  • Mortality model that shows how experience differs from traditional industry tables

 

  • Adjusts the Select period of traditional industry tables for the specificities of these products

 

  • Measures mortality variations from different distribution channels

Carrier Applications:

  • Provide your actuaries guidance in setting pricing and reserving assumptions

 

  • Helps assess the effectiveness of UW tools and design of application questions

PEARL FUW - Fully Underwritten

Key Features:

  • Mortality model based on industry data with over 1.4M claims in our dataset

 

  • Precisely captures the effects of:

     - Preferred Class

     - Issue Era

     - Mortality Improvement

     - Type of Product

     - Traditional variables impacting mortality

Carrier Applications:

  • Improving your mortality assumptions used for pricing and reserving

 

  • Benchmarking your mortality experience with other companies

 

  • Understanding areas where your experience deviates from industry averages

 

  • Obtain mortality variations when adding or removing underwriting requirements

PEARL FE - Final Expense

​​​​​​Key Features:

  • Mortality model based on our data, with 45k claims

 

  • Large precision improvement over available industry tables

 

  • Taking into account effect of Rx Check on mortality

 

  • Reflects high rescission rates, specific to that line of business

 

  • Mortality insights by geographic region & specific health indicators and thoroughness of application questions

 

  • Post-Issue distribution monitoring with "Agent Watchlist Score"

Carrier Applications:

  • Defining or improving mortality assumptions by providing more precision than current industry tables

 

  • Provide a better mortality analysis by removing the correlation effect between variables that traditional methods do not provide

 

  • Obtain insight on your book of business where mortality is significantly different than the market average

 

  • Define sales incentives for distribution; guiding agents towards areas of profitable growth

 

  • Enhance your UW workflow with analysis on the mortality impact of each UW tool & health questions

 

  • Better control of distribution by monitoring persistency, smoker declaration, misrepresentation % by Rx tool, and rescissions by duration

PEARL Partnership

Whether you are looking to improve your mortality assumptions, promote controlled distribution growth, or maximize profitability, PEARL's predictive model has you covered. Start experiencing the predictive power of PEARL by reaching out to your Optimum Business Development Representative to provide the list of data fields below.

PEARL - The Strength of Expertise.

Policyholder

  • Policy Number
  • Gender
  • Smoker Status
  • Issue Age

Underwriting 

  • Current & Historical Applications
  • Current & Historical UW Requirements
  • Output from UW tools & Application
  • % of random & models holdout (AUW)
  • Accelerated Indicator (AUW)

Experience

  • Termination Type
  • Lapse Date
  • Claim Status
  • Claims Paid Amount
  • Claims Notification Date
  • Claims Paid Date
  • Cause of Claim
  • Date of Death

Policy

  • Preferred Class (if applicable)
  • Issue Date
  • Product
  • Benefit Type
  • Face Amount

Distribution

  • Distribution Channel
  • Agent ID/Agency
  • First Year agent commission %

Geographic

  • State/Residence Code
  • Zip Code

*As with all models, the more data fields provided improves the output. Additional fields may also be added based on your company's needs.

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