American Association of State Compensation insurance Fund
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member fund.

CopperPoint Mutual Insurance Company
Phone: (602) 631-2000
Address: 3030 North Third Street
Phoenix, AZ   85012

State Compensation Insurance Fund
Address: 333 Bush Street
Suite 800
San Francisco, CA   94104

Pinnacol Assurance
Phone: (303) 361-4000
Address: 7501 East Lowry Boulevard
Suite 800
Denver, CO   80230-7006

Hawaii Employers' Mutual Insurance Co. Inc.
Phone: (808) 524-3642
Address: 1100 Alakea Street
Suite 1400
Honolulu, HI   96813

Idaho State Insurance Fund
Phone: (208) 332-2100
Address: 1215 West State Street
P.O. Box 83720
Boise, ID   83720-0044

Kentucky Employers Mutual Insurance
Phone: (859) 425-7800
Address: 250 West Main Street Suite 900
P.O. Box 83720
Lexington, KY   40507-1724

Louisiana Workers' Compensation Corporation
Phone: (225) 924-7788
Address: 2237 South Acadian Thruway
P.O. Box 83720
Baton Rouge, LA   70808

Maine Employers Mutual Insurance Company (MEMIC)
Phone: (207) 791-3300
Address: 261 Commercial Street
P.O. Box 11409
Portland, ME   04104

Chesapeake Employers’ Insurance Company
Phone: (410) 494-2000
Address: 8722 Loch Raven Boulevard
P.O. Box 11409
Towson, MD   21286-2235

SFM Mutual Insurance Company
Phone: (952) 838-4200
Address: 3500 American Boulevard West Suite 700
P.O. Box 11409
Bloomington, MN   55431-4434

Missouri Employers Mutual Insurance
Phone: (800) 442-0590
Address: 101 N Keene St
P.O. Box 11409
Columbia, MO   65201

Montana State Fund
Phone: (406) 495-5015
Address: 855 Front Street
P.O. Box 4759
Helena, MT   59604-4759

New Mexico Mutual Group
Phone: (505) 345-7260
Address: 3900 Singer Boulevard NE
P.O. Box 4759
Albuquerque, NM   87109

New York State Insurance Fund
Phone: (212) 312-7001
Address: 199 Church Street
P.O. Box 4759
New York, NY   10007

Workforce Safety and Insurance
Phone: (701) 328-3800
Address: 1600 East Century Avenue Suite 1
P.O. Box 4759
Bismarck, ND   58506-5585

Ohio Bureau of Workers Compensation
Phone: (800) 644-6292
Address: 30 West Spring Street
P.O. Box 4759
Columbus, OH   43215-2256

CompSource Mutual Insurance Company
Phone: (405) 232-7663
Address: 1901 North Walnut Ave.
P.O. Box 53505
Oklahoma City, OK   73152-3505

State Accident Insurance Fund (SAIF)
Phone: (503) 373-8000
Address: 400 High Street SE
P.O. Box 53505
Salem, OR   97312-1000

Pennsylvania State Workers Insurance Fund
Phone: (570) 963-4635
Address: 100 Lackawanna Avenue
P.O. Box 5100
Scranton, PA   18505-5100

Beacon Mutual Insurance Company
Phone: (401) 825-2667
Address: One Beacon Centre
P.O. Box 5100
Warwick, RI   02886-1378

South Carolina State Accident Fund
Phone: (803) 896-5800
Address: P.O. Box 102100
P.O. Box 5100
Columbia, SC   29221-5000

Texas Mutual Insurance Company
Phone: (800) 859-5995
Address: 6210 East Highway 290
P.O. Box 5100
Austin, TX   78723-1098

Workers Compensation Fund
Phone: (800) 446-2667
Address: 100 West Towne Ridge Parkway
P.O. Box 2227
Sandy, UT   84070

Washington Department of Labor and Industries
Phone: (360) 902-5800
Address: P.O. Box 44001
P.O. Box 2227
Olympia, WA   98504-4001

Wyoming Division of Workers Safety & Compensation
Phone: (307) 777-7159
Address: Cheyenne Business Center
1510 East Pershing Boulevard
Cheyenne, WY   82002

Workers Compensation Board - Alberta
Phone: (780) 498-3999
Address: 9925-107 Street
P.O. Box 2415
Edmonton, AB   T5J 2S5

Workers Compensation Board of British Columbia (WORKSAFEBC)
Phone: (604) 273-2266
Address: P.O. Box 5350 Station Terminal
P.O. Box 2415
Vancouver, BC   V6B 5L5

Manitoba Workers Compensation Board
Phone: (204) 954-4321
Address: 333 Broadway
P.O. Box 2415
Winnipeg, MB   R3C 4W3

Phone: (506) 632-2200
Address: 1 Portland Street
P.O. Box 160
Saint John, NB   E2L 3X9

Workers Compensation Board of Nova Scotia
Phone: (902) 491-8999
Address: 5668 South Street
P.O. Box 1150
Halifax, NS   B3J 2Y2

Prince Edward Island Workers Compensation Board
Phone: (902) 368-5680
Address: 14 Weymouth Street
P.O. Box 1150
Charlottetown, PE   C1A 7L7

Saskatchewan Workers Compensation Board
Phone: (306) 787-4370
Address: 200 - 1881 Scarth Street
P.O. Box 1150
Regina, SK   S4P 4L1

Puerto Rico State Insurance Fund Corporation
Phone: (787) 793-5959
Address: G.P.O. Box 365028
P.O. Box 1150
San Juan, PR   00936-5028
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AASCIF Newsletter

Predictive Analytics in Workers’ Compensation

Kama Kolbe, Vice President, Underwriting and Loss Control - IWIF
Policyholder Services Committee

Predictive modeling is not new.  Not a week passes that we are not reading an article in one of the trades about the advantages and merits of predictive analytics – this week is no exception.

What is new is the way our industry is applying the technique. Of particular interest is how traditional, conventional, conservative and staid old insurance companies are embracing the concept well beyond the established personal lines underwriting applications.  Gone is the commercial lines mystique that for many years insisted that somehow commercial accounts must be touched by an underwriter. That type of thinking is challenged by a real need to grow revenue, increase profit and gain market share, while trimming costs and improving process efficiencies. And do not forget the respectful bow to compliance and the need to remain consistent in risk selection and pricing decisions.

We live in a world of trying to know what happens before it does.  Insurance organizations are particularly focused on predicting future outcomes as they pertain to budgets, policy count, premiums and the cost of losses.

In extremely simple, unsophisticated terms, predictive analytics uses a group of data, (internal and/or external) and applies a statistical algorithm to identify hidden patterns, trends and relationships to predict future outcomes. It is the predicted outcome that will dictate or guide the actions taken to achieve the desired business goal.

Predictive analytics has proven to be a useful application across all major functional areas of insurance organizations.

  • In Marketing, it can be used to increase hit ratio by identifying the purchasing patterns of who likes to buy from us, what they like to buy and how they like to buy. That information can translate into targeted marketing strategies that focus agents on customers and distribution channels meeting the profile of a “more likely to buy” customer. Funds who have other products available, engage in even more successful cross-selling campaigns.
  • In Underwriting, where predictive analytics has been most widely accepted, models have been deployed successfully to right price business and improve profitability and to create no-or-low touch business processes that have underwriter intervention only on the account that presents an anomaly - the exception account. These actions reduce underwriting cycle time, enhance the customer experience, provide for consistency in underwriting, improve expense ratios, and again, produce better overall underwriting results.
  • Claims models are often used for early identification of severity cases and can impact medical cost management through earlier intervention of Nurse Case Managers or other specialty handling.  Use of claims models can further result in reduced LAE and improvements to the overall claim ratio.
  • In Premium Audit, models can identify recession resistant industries and help select accounts for audit that are less impacted by current economic circumstances. These models can also indentify what type of audit (physical, phone, or mail) offers the best return on often limited resources.

With all the positive outcomes associated with predictive analytics, there are drawbacks that must be considered as well.

  • Building the model can be costly. Most of us, while we have the data, may not have the knowledge or level of in-house expertise required to build a sophisticated and statistically relevant algorithm that will produce the intended (credible) outcome. It may be worth soliciting the services of those with known expertise in the field, such as Valen Technologies, Inc. or Delloitte Consulting, LLP.  These firms have extensive experience with carriers in building models and are equipped with divisions dedicated to analytics.
  • Implementing the techniques may require a substantial investment in new software and hardware.
  • Data quality may be lacking or insufficient. The model is only as good as the data that goes into it. Time and resources may be needed to scour data for missing or incomplete records and to make corrections to assure the accuracy of the model. If data is insufficient it may require the purchasing of data from a third party.
  • Lastly, but with no less significance, there may be resistance to change within the organization. Employees currently involved in the operations may feel threatened by the streamlined operational gains or that their experience is no longer valued.

As we strive for the edge that will help write or retain another piece of business, improve profitability or streamline operations, predictive analytics cannot be overlooked as a viable solution - many have found it a necessary and worthwhile investment. Whether predictive analytics serves  as an intervention tool  in the decision making process, an additional resource for staff to consider, or a means  to enhance workflow, the technique should be given due consideration.  The advantage of knowing you have something your competition does not could be priceless.



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