Thanh Hoang:

Good morning and good afternoon everyone, and thanks for joining us today.

We're at webinar on staying ahead of law enforcement liability with new technologies.

I'm Thanh Hoang and the writer based out of San Francisco.

And joining me today is Dan Foster, lost control expert based out of Montgomery, TX.

Then I we work closely together on assessing risk and lost control initiatives.

We'll be diving into current challenges.

We'll be diving to current challenges faced by law enforcement.

Then we spend a good portion of the segment in covering various technologies that are transforming the landscape.

And then I will circle back and provide the underwriting perspective on some of these investments.

We've talked to new technologies.

In recent years, we have seen the rising challenges with law enforcement.

You look at the slide just to list a few of these challenges.

Transparency and accountability laws are leading to more scrutiny and compliance, adding both operational and legal challenges.

Law enforcement agencies are also having challenges with recruiting and retaining officers due to various factors such as negative public perception, safety, burnout, and reforms.

I want to point out the highlighting in red.

Rising cost of law enforcement claims is becoming a pain point for our clients, underwriters and brokers.

Social inflation, rising nuclear verdicts and rising cost associated with repeat offenders.

Police misconduct only exasperating the situation.

However, in recent years, we're starting to see a wave of new investment in technologies and startups to help control or mitigate these causes.

Lauren Tredinnick:

With that, we'll turn it over to Dan Foster who will talk us.

We'll talk about some of these technologies.

Thank you, Thanh.

Dan Foster:
So just to clarify, if you've come here to learn about maybe some new firearms or gadgets that police officers use, that's not this presentation.

Our focus is going to be on how technology, artificial intelligence and data analytics is being used to help improve the risk management and loss prevention scope for law enforcement.

As Thanh mentioned, we're dealing with a new era in law enforcement.

We've got very high escalating claims cost.

We've got a lot of focus on accountability and transparency and there's a lot of attention on and pressure, social pressure on law enforcement agencies to do better, to step up and improve the way that they operate and engage with the public and also how they perform their duties.

So when you think of police technology, you know, these may come to mind, you know, RoboCop or Minority Report, but it's less of this stuff and more what we're going to see on the next slide.

So it's with technology in the form of things like body worn cameras, license plate technology and frankly what  they're doing with the vehicles, the teching out of the vehicles allows them to do a whole lot more in less time and more accurate, more accuracy.

So what's driving the need for technology?

Better tools.

Technology has always been used in law enforcement.

You go back to the days of Sherlock Holmes.

He was using technology for his day.

So it's always been part of law enforcement.

There's just new, new elements out there for them to work with.

There's a demand for better information and more accurate information to reduce false arrests, false identifications and, and errors with law enforcement.

And then also improving the safety of not only the officers, but the citizens that they engage with.

And as we just heard about cyber security, crime is getting more sophisticated.
And so technology is needed to identify and mitigate these new crimes.
So we're going to hit on just a few.

There's many different areas where we're seeing technology and AI helping law enforcement do better in the risk management scope.

But we're just going to look at these four areas today, Body worn camera data, police pursuits, virtual reality training and data analytics and predictive modeling or predictive policing.

OK, let's start with body worn cameras.

I want to give it take the picture here in the landscape.

So there are 18,000 law enforcement agencies you think of federal, state, county, local, tribal, 18,000 nationwide.

80% of those agencies as of last year had body worn cameras in play.

So how are they helping?

So they're used to help with citizen complaints.

Officers with body worn cameras are what we're seeing that they have fewer complaints filed against them than officers without cameras use of force.

There's we're still early in, in the infancy of gathering data on this, but it is trending in the right direction that their officers are using better decision making in terms of use of force and the body worn cameras are helping in ensure that that takes place the impact on investigations.

So we're seeing an increase in the rate of guilty pleas, convictions and cases being cleared out of courtrooms because of the valuable data and images that we're getting from the cameras and reduce litigation.

This is where this is where the budgets really get justification for every dollar spent on body worn cameras equals $4.00 in savings and litigation.

If there's any defense counsel out there, acclaim suggesters, I hope that gets your attention.

We want our agencies to utilize body worn cameras.

It actually is now measurable that it's helping to reduce these costs and then feedback for training with the help of AI.

Body worn camera data is used to evaluate officers behavior deficiencies with their following procedures and it's also identifying new training opportunities.

OK, so there's roughly just under a million police officers out there.

There's 29 billion files of data recorded every month.

That equals 1140 years of footage.

That's a lot of body worn camera data.

And I don't even know what a petabyte is, but 17.4 petabytes.

So what does that look like?

That's about equal to 1 billion users uploading YouTube videos each month.

That's what that looks like.
That's a lot of information.
So without help, there's no way that an agency, a law enforcement agency can adequately review every officer's body worn camera than officers out at an 8 hour shift.

There's 8 hours or so of recorded data.

And you multiply that times a hundred officers, that's just too much information to be able to review sitting at a computer.

So it's not being reviewed.

It tends to be brought in after the fact, except now we have AI to help us leverage this.

What the what the technology does is it reviews all of this data and provides a scorecard on the officer's performance.

It shows red flags that need corrective action, compliance with policies and procedures.

It's amazing.

We don't have time to go into in depth here, but there's several different platforms out there that law enforcement agencies are using and it's definitely improving.

Why do I love this so much?

Because this is from a risk management perspective.

We want to catch these deficiencies prior to a loss.

We don't want to have to scramble and do damage control finding out that we had a bad actor in our agency that was continually violated policy.

We want to be able to identify those behaviors ahead of time and be able to take corrective actions.

That's what this AI technology is allowing us to do.

So the next is vehicle pursuits.

So this is a a disturbing trend that we're seeing.

Unfortunately, vehicle pursuits lead to a lot of fatalities nationwide.

So in the year 2022 we had a record high of 577 people killed in pursuits and the year before that twenty, 21525.

That's well over one per day on average people dying in fatal crashes involving police pursuits.

So, and the data is showing that many of these are resulting that, that there's police pursuits that are occurring and they, they broke it down to take a look at what's, what's driving these pursuits.

And if you look at the, the pie chart to the right, so the Big Blue chunk, that's 62%, that's traffic offenses, that's people speeding, blowing through a stop sign, broken tail lights, swerving, distracted driving, any of those traffic offenses.

Then we get some of the other smaller pieces of the pie, which is misdemeanors, assisting others in police pursuits, non-nonviolent felonies and in violent felonies is 3%.

So these are the things that are leading to police pursuit.

So the majority of police pursuits we find are being driven.

It's the initiated by a traffic stop and the person flees the scene.

So, and this is an issue not, not only because these numbers that we, we read before the fatalities, it's not only citizens, but 1% of of those fatalities are law enforcement officers.

So we're looking at what we could do better.

Next slide, let's look at what we could do.

So this is where technology comes in and, and go ahead and flip to the next slide here.

We'll, we'll talk about what's available to us.

So the vehicles that we drive today are a lot more techie than they've ever been.

78 million cars on the road have GPS technology installed by the manufacturer.

So by the end of next year, 98% of all cars sold will have that.

So think less about GPS, like your GPS maps.

This is actually a, a global positioning tracking that's built into the vehicle itself in the DCM, the digital or, or data control module that's on every vehicle.

It's, it's always on.

So the, there's already something embedded in every vehicle that allows us to know the position and location of a vehicle.

So 78 million cars have that capability right now and we're getting close to 100% of all cars being released.

So what about, you know, somebody that's driving a car that's 20-30 years old that may not have that?

Well, there's alternatives and they're called slap and track devices that can be a fix to be able to identify the location of a device.

If you look down at the bottom on the back of that white pickup truck, there's what looks like a can stuck to the back.

It's a magnetic tracker that can be put on a vehicle at a traffic stop.

So if an officer feels the need to, you know, they might, if there's a gut feeling that there might flee the scene, they can put that slap and track on there.

And then if the vehicle leaves, they can track it and, and, and locate it elsewhere.

OK, so this technology that we're talking about, what it's allowing us to do is change the way we do things.

So you've got a police, you got a traffic stop or a police pursuit and you're able to use your, your license plate tracking to identify the vehicle.

You find out it's got GPS capabilities in it.

You're able to identify where that vehicle is at all times.

So rather than endanger the public with a high speed chase through neighborhoods or heavy traffic intersections, you could go and, and, and actually have more of a planned confrontation where that vehicle is, is going to end up being located.

And we're, we're finding great success with that.

So the slap and track devices, one manufacturer, Star Chase reports an 85% apprehension rate with their devices.

That's pretty good.

That means that every time that Star Chase is used in a pursuit or to track a a, a vehicle that leaves the scene, 85% of the time they're getting those vehicles and apprehending the person that's responsible.

So this is where technology is leveraging and improving the safety and well-being of not only officers, but us, the public, and minimizing the risk of these unfortunate deaths that are happening due to police pursuits.

The third area is virtual reality training.

And this one I'm really excited about because it's, it's taking the training and officer competency to a completely new level that I'll just, I'll just couch it by saying this.

One of the challenges we have in risk management and defense of law enforcement claims is the that the officer is found to be incompetent or failed to follow procedure.

And it usually comes back to a deficient training issue with the officer.

And so agencies are constantly trying to make sure that their officers are well trained and following procedure.

Virtual reality training is a game changer when it comes to this.

So just like with video games, they're using these headsets, the goggles like you see and incorporating them into various scenarios.

So the the old style of training would be the obstacle course.

You see them go around with a firearm and they're doing scenarios of armed of, of engaging in, in lethal use of force and, and training to that element.

And they're getting typically they're getting about 154 hours of weapons and tactical lethal use of force training, 154 hours of that.

Then they get 18 hours of education on de-escalation techniques.

Well, what that's doing is it, it's building up the law enforcement space to basically confront situations with lethal use of force.

There's times when it's needed.

But are we, are we deficient in other ways of being able to mitigate these encounters that they have?

Well, that's where virtual reality training is, is making a big, big change.

So what we're finding is first of all, with the, with the training, they're able to create any number of scenarios.

So whereas you have a usually a state post off, which is a training center that's centrally located in the state somewhere and it's training everybody from urban to rural and so on.

And so it's very standardized.

It's, there's no flexibility with how they set that up.

Virtual reality lets you change and flex your training for your location.

If you're a small town, you could set your training up for your officers based on the types of confrontations and encounters that they're going to have.

If it's a big urban setting, New York City, for example, that's going to be a completely different type of training protocol that they're going to need for those types of encounters.

And if it's a country sheriff there, there's going to be different encounters that they're going to have there.

So it lets you customize the training based on the types of encounters you can that the officers are going to have.

So the retention on virtual reality training is phenomenal, 80% is retained after one year of virtual reality training.

That's way higher than what we've seen with any other type of training that officers get.

Officers have a 40% improvement in the confidence in dealing with situations.

In other words, they're saying we feel 40% more confident that we're able to do our job properly and adequately.

I feel adequately trained at 35% advantage and effectiveness of training over the traditional methods.

So we see a third improvement in the effectiveness of that.

These are all great numbers to see and it's definitely the way we're going to see law enforcement training go from today and in the future.

So U.S. Department of Justice claims 90% of law enforcement agencies believe that virtual reality technology will improve officer training and reduce the likelihood of accidents or injuries.

Arizona State University reports that officers undergoing virtuality training should have 48% reduction in the use of force during simulated encounters compared to those who receive traditional training.

There's so much pressure on law enforcement agencies to, to reduce the use of force, find other ways to deal with a situation without shooting people or putting, you know, life, life, life threatening encounters.

So they're, they're seeing an improvement, a reduction in those and still able to complete the task of apprehending and, and incarcerating somebody.

So virtual reality training plays a key role in reducing use of force when engaging the public of fundamental requirement that law enforcement agencies in most states have today.

By that I mean states are have initiated laws and measures to say to law enforcement agencies do something to reduce your use of force.

The final segment here is on data analytics and predictive modeling.

So data analytics we we've heard a lot about, it's a buzzword for today and it's really analyzing data.

And we're fortunate that we have the capabilities now to analyze all kinds of data.

Predictive modelling is like that.

It's taking data and trend information and being able to see where, where is this path going?

Where if I follow this out ahead, where is it going?

We just, we saw that recently with hurricanes, we track the path, we can come up with different predictive models on where a hurricane is going to land, what area is going to get hit and how to prepare for that.

So that's how these two disciplines work together.

So predictive analytics, I just mentioned that it's, it's using the, the forecasting future outcomes, OK.

So law enforcement agencies are now incorporating predictive analytic models into their risk management.

This is really new stuff and it's, it's taking off.

And I'm particularly paying very close attention to it for our clients because I believe it's going to help make the difference between really good risk that we insure and average risk that we insure.

So some of the areas that where it's being used is identifying risk behavior with officers.

So you, you talk to law enforcement agencies and if they, if they're honest with you, they'll talk about like, yeah, there's that one cop, you know that, you know, he's been around a long time.

You know, we, he, he, this, he or she is who, who they are.

And they have these behavioral issues that they're always working around and dancing around.

So risk behaviors can be identified and measured in a analytically now verifying officer compliance with policies and training protocols.

So give an example of a real quick example of risk behavior.

181 law enforcement agency I spoke with, they kept getting complaints about one officer that kept speeding through town.

The vehicles report the cruiser was being reported and so the chief didn't really know what was going on until they were able to look at the telematics data on the vehicle.

And this officer was kicking into pursuit mode for everything.

So the chief sits down with this officer and asked him, why do you initiate pursuit?

You're not allowed to do that.

You have to get permission to do that.

And he says, well, that's how I was trained.

And he was going back to some poor training that he received and he had never been corrected.

The technology, the telematics was able to identify the officers deficient behavior.

The chief was now able to get this officer the training and corrective action that was needed.

So this is this is the this approach using this type of approach is definitely helping us see improvements in helping to identify areas of deficiency and improve the officer and agency staffing needs that are there.

So next slide, OK, so one of the companies that's most forefront for front facing on this is Benchmark Analytics and they have something called first sign early intervention System, first sign EIS.

So they've analyzed 9000 officers from 26 agencies and over A2 year.

They assess arrests, use of force, severity of force and complaints and they identified looking at those when implementing the early intervention system that all of those saw a reduction.

First sign was able to detect adverse behaviors and at risk officers and provide corrective action.

And then these steps were taken before.

This is the part that's really important before a critical incident took place.

So by implementing these changes, we're going to see things improve in terms of critical incidents being reduced, public safety is improved, officer safety is improved and the risk of litigation is avoided.

Bottom line, if you're doing claims defense counsel, you want to have something like this in your back pocket to be able to show that the agency is at is at or above standard in terms of how they're operating.

It's great defense.

It's what we need on many of our claims that we see next slide.

OK, last thing real quick is just the numbers that they show 85% efficacy rate.

Efficacy is what we hear a lot about with vaccines.

They're showing 85% efficacy rate with how well first science is working compared with a 75% failure rate for traditional early intervention systems.

I just want to lay out here what the future of law enforcement's looking like with technology.

Basically we've got blue-green and red, Red is we're not doing anything about it.

Blue and green are how these things are being budgeted.

And as you could see, technology is being implemented on a lot of different where areas in a lot of different ways.

And most of it is, is well, you know, we we're seeing it's implemented well over 50% of the time across agencies in the United States.

Thanh Hoang:

Thanks Dan for giving us those interesting insights into the various law enforcement technologies.

I wanted to give a analyze point of view and underwrites take on these type of law enforcement technologies.

Underwrites are definitely increasingly considering the use of technologies.

I know Dan gets very exciting when he sees law enforcement agencies piling new technologies.

We are also seeing more technology startups and companies seeking to engage with insurance carriers and clients.

So the founders we talked to are very passionate and mission driven to not only help reduce claims costs, but also building a safer law enforcement community.

Analysts are building more comfort in emerging technologies such as Dan mentioned, predictive policing technologies.

As more data are being collected, analyzed, and interpreted, analysts are starting to see how helpful these technologies can be.

For example, new technologies can help ensure law enforcements are complying with new regulations and compliance from reforms.

Well how the effective usage of body Cam can help mitigate potential losses in hard to place law enforcement liability coverage scenarios.

Adopting new technologies can also help improve terms and conditions or even be a difference maker in attaining coverage.
But at the same time, there are challenges with these technologies.
Some of the concerns that analyze have is uncertainty of how new technologies would reduce risk and if they do reduce risk, what are the other liabilities that they could potentially pose?

You could reduce law enforcement claims, but would that increase to civil rights violation claims?

And could the questions the analysts may have also is do the agencies have appropriate staffing, operational support and training for these technologies?

How much human error does these technologies create in real life scenarios?

You can have the best technologies, but if using correct incorrectly, it could lead to other problems.

Another challenge nursery may ask is, you know, how do you measure the impact of these technologies?

How do these technologies address frequency, severity and to what degree?

As you know, law enforcement is a is very complex and challenging and so it is hard to conduct correlation studies because there's just so many variables involved.

I think what works is telling the story.

Workers, risk managers, and loss control expert could help explain why these technologies are valuable and how they could make a difference to agencies and insurance underwriters.

Workers and risk managers can tell powerful stories of how these new technologies can help reduce law enforcement claims by focusing on clear and relatable connections between innovations, providing success stories or case studies.

On this slide, this is an example of a usage of drone for vehicle pursuits.

It's almost a no brainer for underwriters because there's a clear path of how these drones can give information to police officers to make safer arrests and that could lead to underwrites confidence in discounting these losses.

Do you think police forces would get away from police pursuits or do the risk or do the risk and possible claims outweigh the arrests?

Dan Foster

So the short answer is no.

Will there's always going to be a need for pursuits, particularly when it comes to dangerous encounters, armed robbery, somebody fleeing a murder?

You know, and they're going to pursue that person because they're a threat.

But what's going to change is the need for pursuits.

As you saw 62% of those are for traffic offenses.

So that's the area where we're going to see reduction in pursuits.

But they'll they're not going to go away completely.

Thanh Hoang

Looks like we've got another question.

Is technology replacing officers?

Dan Foster

All right, I'll, I'll take that one.
No, there's every agency is still in in hot demand for qualified officers.
But what's happening is we're seeing the need for technology is growing.1:00:57
So for every officer, there's almost a one to one where they need somebody with technical qualifications.

There's a lot of positions out there for analysts, scientists, Cybercrime is a huge growing area for law enforcement, and they're constantly needing people that have the skills and technical disciplines to be able to work in that area.

So they may not be a Commission officer, you know, hitting the beat, but they're going to be doing law enforcement in a different way.

So we're going to see it transition, but they'll always be a need for law enforcement officers.

So if you know anybody that wants to be a cop, there's still opportunities for them to get a job.

Thanh Hoang

Looks like we got one final question.

We will adopt the technology in law enforcement qualify for schedule credits or premium discount.

I could go ahead and take this question.

The favorite underwriting answer is it depends.

So generally underwrites there's no release for most companies.

There's no reset schedule credits such as you see in personal Lines auto where if you adopt an object you get a automatic 10% discount.

With law enforcement underwrites, we look at specific information variable factors such as loss experience, attachment point training and policies in deploying the technologies operational capabilities.

And with that, I'll go ahead and turn it back to Lauren.