Proposed Florida Insurance Reform (HB 837)

The Florida legislature is thinking of tinkering with PIP and other auto insurance laws again. This time I think it will be a good change!

A version of the bill can be seen here:

One-way attorney fees

Florida has had a law that states that if a plaintiff sues the insurance company and wins, then the insurance company must pay the attorney fees. On the other hand, if the insurance company prevails, there are no attorney fees that must be paid. This created a situation where lawyers filed thousands of lawsuits, in the hope that one would ripen into a case in their favor. The lawyers used templates and generated these lawsuits in mass, each lawsuit acting somewhat like a lottery ticket for the attorney. It was a numbers game, the more lawsuits filed, the greater the likelihood of a payout for the attorney, with no real negative consequence for plaintiff’s attorney for filing so many suits. This resulted in some lawyers having more than 10,000 ongoing lawsuits at a time. This has substantially increased the cost of insurance in Florida making auto insurance more and more expensive. It also has substantially favored fraudsters who do not hesitate to file lawsuits on the thousands of fake cases created by their fraud rings.

Amazingly on page 30 of the PDF of the proposed law, it says: “Section 627.428, Florida Statutes, is repealed.” The entire statute is taken out!

In general, now attorney fees will be carried by each party. However, there remains the possibility of attorney fees in a declaratory judgment for coverage, found in chapter 86 of Florida statutes. It will be interesting to see how courts evolve. I believe this will substantially reduce attorney fees in Florida, but there may rulings that allow attorney fees in unexpected situations.

Bad Faith

My experience with Bad Faith in Florida is as follows. A plaintiff’s firm churns out numerous time-limited demands, especially on cases with weird circumstances. The time limited demands usually only provide 30 days’ notice. If the demand is not paid and the insurer goes on to lose, then a  jury can end up assessing huge “bad faith” amounts. Lawyers can particularly pounce when an honest mistake is made with regards to timing. I have seen multi-million-dollar settlements because a response is a day late or because an email was mistakenly deleted. This time the legislature amazingly seems to have realized this issue and has added provisions that specify that an action for bad faith must be submitted under a standardized form and give 90 days for response. This is a game changer for insurance companies who are subject to “bad faith” when honest timing mistakes are made.

The bill also provides that mere negligence is not enough for bad faith (remember my accidental email deletion example) and that bad faith on the part of the claimant is also a factor. Requiring “good faith” on the part of the plaintiff’s attorney’s was one of the main things I was demanding last time the legislature took up this issue, as I have seen attorneys intentionally be confusing in their demands in an effort to confuse the insurance company to make it appear that the insurance company is acting in “bad faith”.

In general I think this bill will substantially improve the legal situation in Florida with regards to bad faith. Here are references in relation to the PDF cited above:

On page 14, it says: “An action for bad faith involving a 336 insurance claim, including any such action brought under the common law, shall not lie if the insurer tenders the lesser of  the policy limits or the amount demanded by the claimant within 90 days after receiving actual notice of a claim which is accompanied by sufficient evidence to support the amount of the claim.”

On page 15, it says: “In any bad faith action, whether such action is brought under this section or is based on the common-law remedy for bad faith: (a) Mere negligence alone is insufficient to constitute  bad faith.  (b)1. The insured, claimant, and representative of the insured or claimant have a duty to act in good faith in furnishing information regarding the claim, in making demands of the insurer, in setting deadlines, and in attempting to settle the claim.”

Fraud Prevention

As someone engaged in fraud prevention, I strongly favor this bill. In my experience in Florida, when an insurance company reaches a point that it believes a claim is fraudulent, it often still will not take action to deny the claim because it is afraid of the legal pitfalls of the Florida code. With these new changes to the code, insurance companies will be less afraid to call fraud what it is. This should make it less profitable for fraud rings in Florida. Over time, this should substantially reduce the premium paid by auto insurance policyholders in Florida.

Dominion Election Machine Results 2022

Prior to the election, I announced a test of whether Dominion machines correlate to the 2022 results. This test consisted of taking the Real Clear Average polls prior the election and comparing them to actual results, using the percentage of Dominion machine usage in a given state as a predictor.

The 2022 results were the Dominion effect was 4.06% with a one-sided p-value just under 10%


Ten days ago I wrote what type of statistical tests I would do regarding Dominion Election Machines.

I warned that all eyes were on the Arizona governor’s race, where the Republican was ahead (slightly), the Democrat candidate was in charge of her own certification process, and Maricopa County uses Dominion machines–which would have been targeted for cancellation if the Republican won.

Unfortunately, the machine processes failed in some areas, at some points in time, in Maricopa County. I do not know which type of machines (printer vs. tabulator) or which brand of machines caused this issue. I read various “fact checks” that try to blame the printing companies not the tabulators, but the fact of the matter is, the official statement came from video from Maricopa County itself via twitter, which said “20% of the locations have an issue with the tabulators”. Watch the video for yourself, if it is still available. (Here is an article about the person on the right in the video.) I have no knowledge of what machines caused this issue.

So…. where does that leave us?

Unfortunately, it means that a large number of individuals in our society will not trust the outcome of this Arizona election, independently of any statistics I am about to produce.

Having said that, here are some stats to consider.


Table 1 shows the number of elections (for governor or for senate) that were included in the study. Note that the Oregon governor polls were a tie going into the election, so I excluded Oregon from this table to make it easier to read.

Table 1: Overall View
CategoryTotalRepublicans Predicted to Win Republicans Actually Win Democrats Predicted to WinDemocrats Actually Win Change
Dominion Less than 15% of Potential Voters1066440
Dominion Higher than 15% of Potential Voters13627114

Table 2 shows you the data that is used in the statistical analysis. The first two columns with numbers are the value that Democrats were higher (or lower) than the Republicans. The difference is the change from the predicted to actual.

Table 2: Data for Statistical Test
StateElectionRCP Avg 11-5-22 Dem. AdvantageRCP Actual 11-16-22Difference (Y Variable)Dominion Percent (X Variable)
New YorkGovernor6.25.7-0.555%
New MexicoGovernor46.42.4100%
New HampshireSenate0.79.18.40%
North CarolinaSenate-5.2-3.51.70%


Table 3 shows you the output of a statistical regression.

The first field called “intercept” is how far off the polls were from the actual results. The value is 0.66, meaning the general population appeared to vote 0.66% more for Democrats than the pre-election polls. The P-value is 68% which is generally considered not significant. This means the polls were not far off from the election results.

The next field is the number of points the model estimates were moved based on how much of the state was covered by Dominion machines. If the state is 100% covered by Dominion, the expected change from pre-election poll to actual results is 4.06%. For example, if the pre-election polls were a tie, 50/50, going into the election, this model predicts a fully Dominion state would be 52.03/47.97.

A generic least squares model would do a two-tailed t-test, which would produce a p-value of 20%. However, when I announced the test 10 days ago, I pre-announced that we were testing for a positive coefficient. This means that the correct test is a one-sided test. The p-value using this test is 9.99% which is approximately 10%. This means that, given the test I announced prior to the election, the probability that we would obtain a coefficient of 4.06 or higher is about 10%. In other words, this test had a 1 in 10 chance of achieving a Dominion coefficient this high or higher.

Table 3: Results
Intercept (How far off were polls, after adjusting for Dominion Effect):0.6668%
Dominion Coefficient (Percentage point change based on what proportion of voters are covered by Dominion)4.069.99%


Here is the spreadsheet for you to see the math.

What does this mean?

It could mean nothing. Statistics are random.

However, the article you are currently reading and my article from 2020 show:

  • There are correlations from 2022 which correspond to people’s suspicions of fraud.
  • There are correlations from 2020 which correspond to people’s suspicions of fraud.

Producing correlations two elections in a row should make the general public understand that there may be something going wrong, and it continues to be appropriate to push for transparency.

At the moment about 100,000,000 Americans do not trust the results of the 2020 election, as polls show 1/3 of the more than 300,000,000 Americans do not trust the results.

For our society to stop having 100,000,000 people who do not feel like their election choices are being fairly counted, it is an imperative that society do one of the three:

  • Develop a process to make the overwhelming majority feel that machine voting is fair; this is urgently needed for Dominion, for example;


  • Stop using machine voting;


  • Stop using specific machine brands that have not developed a process for people to verify and feel comfortable that the machines are fair.

Stats for Nerds

Okay, above I showed the outcome of a pre-announced test.

If you are interested, here are a few other things to consider, some strengthen the theory and some weaken it.

Question 1: From a data perspective, what really happened?

Answer: Florida, Oklahoma, and Texas, which are not heavy Dominion states broke hard for Republicans, while most of the other places broke Democrat. Some states that were not heavily Dominion broke hard for Democrats, such as New Hampshire and Washington. If the theory about Dominion machines were true, we would not have expected the New Hampshire and Washington to break this way. The below chart illustrates the results and the modeled output, using the model above. Notice the wide range of values where Dominion % is close to 0. This is not a sign of a particularly good model.

Question 2: Did the polls miss how the Hispanic vote would break?

Some people theorize that the polls underestimated that the Hispanic vote would swing Republican, which is why Florida, Texas, and to some extent New York didn’t follow the rest of the nation which went more Democrat than some anticipated.

Answer: If you add Hispanic vote to the regression, it does show Hispanic vote swinging towards Republicans, and the Dominion effect strengthening to 7.54, with a one-sided t-test with a p-value of 1.7%. If this theory were true (that Hispanics broke for Republicans but Dominion broke for Democrats), it would be a reason why Nevada, Arizona, and New Mexico still ended up mostly Democrat while Florida and Texas went hard for Republicans.

However, I am not in favor of adding variables to a model of this type with so few observations.

Attached is a spreadsheet a friend of mine made.

Question 3: Did the Real Clear Politics polls change after you took the data over the weekend prior to the election?

Yes. And I went back and looked at them after the election, and I did not feel I could use what the website showed. In some states it stopped showing the “RCP Average” and just showed individual polls.

Question 4: Shouldn’t the real test be the actual outcome of the election, meaning win or lose, not whether Florida runs up the scoreboard?

Answer: I think that is a good way to look at how this should be tested. To do this, I ran a test on the outcomes, win or lose, and used a logit regression. There was a warning generated which indicates it may not be a good fit. The results were that the Dominion effect was 3.44 with a two-sided p-value of 32%, which I think would correspond to a one-sided p-value of 16%. Again, there were warnings, which indicates that there was not enough data points for this type of regression to be a good fit. Attached is the data and the R code:

Question 5: Were there any races that went against the Dominion theory?

Answer: Yes. Nevada is a heavy Dominion state, yet the governor went to the Republican. The Repulican in Wisconsin winning in a close race for senate is also interesting.

Question 6: What do you really think about this overall test?

Answer: It was interesting to make a hypothesis prior to the election and test it. However, I don’t think there really are enough data points in this test to get a good fit. I think the work I did in 2020 was much more comprehensive because it had much more data. I do note that both tests showed a correlation. Two tests in a row should strengthen the need for transparency. When I first heard the theory about Dominion, it sounded crazy to me, but the correlations are there.

Dominion Election Machine Hypothesis Test, Setup Prior to 2022 Election

As many know, I wrote a paper about the 2020 election which tested whether there was a correlation between Dominion Voting Machines and the 2020 presidential election. (This paper can be seen here:

The paper concluded that there was a correlation between counties that had implemented Dominion and the change in election outcomes comparing 2008 vs. 2020. I made no attempt to assess the cause of this statistical correlation. The test outcome could have occurred randomly. If it was not random, the reasons behind the correlation could have been unrelated to the voting machines, or if they were related to the voting machines it could have been related to some hacking technique unknown to election and Dominion company officials.

At the conclusion of the paper I called for audits (not recounts) to assess what happened. The only place such an audit occurred was in Maricopa County, Arizona.

As we approach the 2022 election, a common question asked of me is what I would expect to happen in 2022 if there is actually a persisent correlation between Dominion and positive results for Democratic candidates.

From 10,000 ft. up, I would expect if the Dominion machines are somehow influencing elections that the Republican candidate for governor in Arizona, Kari Lake, to lose. Right now Kari Lake is winning in the Real Clear Politics average of polls. One of her main campaign issues is she wants to change election processes. It seems apparent that Lake would do everything in her power to remove Dominion from Arizona, so it conversely seems that if there is some control of the election emanating from Dominion machines, that those forces would defeat Kari Lake.

Compounding the Arizona situation, Lake’s direct opponent, Katie Hobbs, weirdly and unethically, as acting secretary of state, is overseeing her own election.

If Lake wins, this would be evidence that Dominion machines are not controlling elections. Even after winning, I suspect Lake will remove Dominion machines from Arizona. 

But if Lake loses, I expect the people of Arizona to be quite upset. And, if that were to happen, simply saying “Kari Lake lost, so there must be fraud” will not be enough. There needs to be more evidence that something went wrong. So, I have thought about this in advance and I wish to share what I plan to study after the elections close on Tuesday (I am typing this on Sunday 11/6).

I wish to test the difference between Real Clear Politics averages versus final results. There should be a national swing that happens, either for Democrats or for Republicans, but this national swing should be independent of which machines a state uses.

I took Real Clear Politics Averages over the weekend for the governor and the senate and they look like this:

State Election RCP Avg 11-5-22 Dem. Advantage
Maine Governor 6
Oklahoma Governor -1
Oregon Governor 0
Texas Governor -9.2
Kansas Governor 3
Florida Governor -11.5
Minnesota Governor 4.3
Pennsylvania Governor 10.7
Wisconsin Governor -0.2
Michigan Governor 4.4
New York Governor 6.2
Arizona Governor -1.8
Colorado Governor 11.7
Nevada Governor -1.8
New Mexico Governor 4
Connecticut Senate 11
New Hampshire Senate 0.7
North Carolina Senate -5.2
Washington Senate 3
Florida Senate -7.5
Ohio Senate -6.7
Pennsylvania Senate -0.1
Wisconsin Senate -2.8
Arizona Senate 1
Colorado Senate 5.3
Nevada Senate -2.4

For these locations, I know the percentage of the state that appears to use Dominion machines.

State Election RCP Avg 11-5-22 Dem. Advantage % Dominion
Maine Governor 6 0
Oklahoma Governor -1 0
Oregon Governor 0 0
Texas Governor -9.2 0
Kansas Governor 3 5
Florida Governor -11.5 8
Minnesota Governor 4.3 14
Pennsylvania Governor 10.7 19
Wisconsin Governor -0.2 31
Michigan Governor 4.4 54
New York Governor 6.2 55
Arizona Governor -1.8 60
Colorado Governor 11.7 92
Nevada Governor -1.8 98
New Mexico Governor 4 100
Connecticut Senate 11 0
New Hampshire Senate 0.7 0
North Carolina Senate -5.2 0
Washington Senate 3 1
Florida Senate -7.5 8
Ohio Senate -6.7 13
Pennsylvania Senate -0.1 19
Wisconsin Senate -2.8 31
Arizona Senate 1 60
Colorado Senate 5.3 92
Nevada Senate -2.4 98

I intend to complete the analysis after the election. What I mean by that is I will take the difference between the predicted vs the actual and run a regression that includes the Dominion percentage as a potential influencer. If a positive coefficient for Dominion emerges that is statistically significant, this would be further evidence of a connection between the machines and election outcomes.

Of course there is always true randomness. This means that whatever such a model produces only provides evidence but does not provide conclusive proof. Random events are just that, random.

I have attached the spreadsheet I intend to use for this test. By publishing this spreadsheet prior to the election I hope to avoid accusations of post hoc rationalization.

Right now this spreadsheet allows the user to simulate the election. However, after the election, the simulated election values will be replaced with actual values and the statistical test result will be produced. Please note, I have excluded Georgia, because of a complicated relationship with their incombent governor and Dominion machines, and Kansas and Maine because the polling data is too small. All other races were included that were available from Real Clear Politics when I wrote this.

I’d like to make one other point. I really hope the election results are such that our society can be comfortable with the outcome and we can move past the idea that the machines are somehow influencing results.