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Home » statistics » Analytics » predictive analytics » Workers Comp Predictive Analytics Changed Loss Run Reviews Forever

Workers Comp Predictive Analytics Changed Loss Run Reviews Forever

March 4, 2021 By JL Risk Management Consultants

Workers Comp Predictive Analytics – Do Not Ignore Old Open Claims 

One of the big changes with loss run reviews started with the carriers and now the whole insurance industry not ignoring the old open claims. Workers Comp predictive analytics has changed how old open claims are evaluated in underwriting. 

picture of workers comp claim analytics Aztec calendar

Public Use Wikimedia License – Keepscases

Years ago, I wrote numerous articles that pointed to only considering claims that were going to be fed into the Experience Mod system.   I even said that predictive systems would not work in workers’ comp.   That statement still stands.  I will cover it in the next heading. 

The scenario has changed so much in the last 10 years that I had to change my advice that I give to claims adjusters, employers, agents, and others. 

Does this discount the Experience Mod system?  No, it does not as the Mod is still the most common way to assess the risk of an employer.  

Times are changing though, on how the Workers Comp insurance industry evaluates employers to underwrite them.  One cannot ignore the Schedule Modification factors that carriers assign to employers. 

Read up here on Schedule Mods as more carriers are using algorithms to calculate your risk factor in addition to looking at your Experience Mod.  Schedule Mods can swing your premiums up to 50% in certain states.  

Two Types of Workers Comp Predictive Analytics 

The two areas of analytics as I view them are pre-claim analytics and post-claim analytics.  Pre-claim analytics seem to work well.  Post-claim analytics have not moved forward that far yet. 

Pre-claim Analytics

Analytics on the front-end of the Workers Comp insurance process has become almost the norm in most underwriting departments.  Carriers, Third Party Administrators, Captives, and other entities that provide coverage can now import the claims data, analyze it, and come up with a score that may vary somewhat from the Experience Mod system. 

Many companies have sold and now sell analytics packages that have simplified the front-end rating processes on insureds.  

Work flow of Workers Comp Predictive Analytics tools

Wikimedia Commons – Foxmetrics

Agencies are now more prone to have a set of algorithms that analyze current and potential clients for many types of loss ratios.   

Inside of pre-claim analytics, the old claims count significantly more than with the Experience Mod rating systems used by the rating bureaus (NCCI, WCIRB, etc.).   

Numerous old open claims on a loss run (more than five years old) may have little effect on your E-Mod/X-Mod.  They will have a greater effect on pre-claim analytics.   Closing out the old claims has become more important over time.  

Check out this article on reopened claims causing problems if they are included in any analytic evaluations.  Reopened claims sometimes have the same numbers reset on the claim, as when the claim was originally closed.  These reopened claims can spike an E-Mod or any type of workers comp predictive analytics. 

Post-Claim Analytics 

Post-claim analytics, according to my opinion, attempt to predict claim values using various factors surrounding the claims.  I still have not seen a package that can analyze the healing of the human body with a predicted return to work date or the amount of medical treatment required for a return to gainful employment.   

Over my career, I have reviewed thousands of claims and loss runs.  I have often seen this situation – a group of injured employees have the same:

  • Employer
  • Socioeconomic factors
  • Age, Sex, pre-injury health
  • Treating physician 
  • Injury type
  • Other similar factors. 

The healing and return to work period vary widely for a similar group as the human body does not heal the same.  No algorithm that I have seen predicts the outcome of these claims.  

I still want to be proven wrong.  I have reviewed some of the systems that were good at pre-claim analytics including the level of safety provided to the employees as a predictive factor.   I have not seen one to date taking post-claim data and using it for a model.   

Old Claims Now More Critical – Workers Comp Predictive Analytics 

Predictive Statistical Studies of Workers Comp Predictive Analytics Diagram

Wikimedia Commons – Norton, John Pease, 1877-

Workers Comp predictive analytics looks at more of a longer horizon than the usual.  Even most actuarial analyses are giving more weight to older claims.    

In 2010 – 2011 and before, I would usually ignore claims that were more than five years old.  Why should I ask an employer or insurance agency to pay me to close files that made no difference to the Experience Mod or a self-insured Loss Development Factor?  

Any claims that appear on loss runs, including old open claims, now require treatment as if they were open new claims.  Workers Comp predictive analytics now give them much more weight when analyzing an insured. 

 

 

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Filed Under: predictive analytics Tagged With: Age, front-end rating processes, human body, longer horizon, Socioeconomic factors

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James J Moore
Raleigh, NC, United States

James founded a Workers’ Compensation consulting firm, J&L Risk Mgmt Consultants, Inc. in 1996. J&L’s mission is to reduce our clients’ Workers Compensation premiums by using time-tested techniques. J&L’s claims, premium, reserve and Experience Mod reviews have saved employers over $9.8 million in earned premiums over the last three years. J&L has saved numerous companies from bankruptcy proceedings as a result of insurance overpayments.

James has over 27 years of experience in insurance claims, audit, and underwriting, specializing in Workers’ Compensation. He has supervised, and managed the administration of Workers’ Compensation claims, and underwriting in over 45 states. His professional experience includes being the Director of Risk Management for the North Carolina School Boards Association. He created a very successful Workers’ Compensation Injury Rehabilitation Unit for school personnel.

James’s educational background, which centered on computer technology, culminated in earning a Masters of Business Administration (MBA); an Associate in Claims designation (AIC); and an Associate in Risk Management designation (ARM). He is a Chartered Financial Consultant (ChFC) and a licensed financial advisor. The NC Department of Insurance has certified him as an insurance instructor. He also possesses a Bachelors’ Degree in Actuarial Science.

LexisNexis has twice recognized his blog as one of the Top 25 Blogs on Workers’ Compensation. J&L has been listed in AM Best’s Preferred Providers Directory for Insurance Experts – Workers Compensation for over eight years. He recently won the prestigious Baucom Shine Lifetime Achievement Award for his volunteer contributions to the area of risk management and safety. James was recently named as an instructor for the prestigious Insurance Academy.

James is on the Board of Directors and Treasurer of the North Carolina Mid-State Safety Council. He has published two manuals on Workers’ Compensation and three different claims processing manuals. He has also written and has been quoted in numerous articles on reducing Workers’ Compensation costs for public and private employers. James publishes a weekly newsletter with 7,000 readers.

He currently possess press credentials and am invited to various national Workers Compensation conferences as a reporter.

James’s articles or interviews on Workers’ Compensation have appeared in the following publications or websites:
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