MASSACHUSETTS SETTLES BID-RIGGING SUIT AGAINST GREAT AMERICAN INSURANCE
Massachusetts Attorney General Martha Coakley has settled a bid-rigging lawsuit for her state against Ohio-based Great American Insurance Co. The insurer submitted a fake and intentionally uncompetitive insurance quote to Analog Devices Inc. of Norwood, Mass. as part of a scheme to make sure AIG won Analog Devices’ 2004 insurance renewal. The Attorney General observed:
Rigging insurance bids is a serious offense that unfairly inflates insurance costs for consumers. We believe this settlement will deter similar unfair behavior in the future.
Under the terms of the settlement, Great American will pay $60,000 to Analog Devices and $116,000 to the Commonwealth. The agreement also requires Great American to undertake conduct reforms aimed at preventing insurance bid-rigging in excess casualty insurance. The insurer will also be required to retain certain records concerning its bidding practices. The suit, which was filed in January 2008, alleged that in 2004, at the request of insurance broker Marsh & McLennan Cos., Great American submitted the fake quote to make AIG’s bid appear to be competitive.
In return, Marsh allegedly steered another one of Analog Devices’ insurance policies to Great American at a pre-determined price. Insurers such as Great American and AIG paid Marsh & McLennan lucrative contingent commissions based on the volume of business Marsh placed with them. In January 2009, the Attorney General, along with eight other states, reached a $7 million settlement with Marsh, resolving a four-year investigation by the states into Marsh’s role in the nationwide bid-rigging scheme.
Source: Massachusetts Attorney General’s Office
Contact us today for a free legal consultation with an experienced attorney.
Fields marked *may be required for submission.
If you would like to subscribe to the Jere Beasley Report digital edition, simply visit our Subscriptions page and provide the necessary information or call us at 800-898-2034.
Attorney Advertising - Prior results do not guarantee a similar outcome.