In his quarterly conversation with Insurance Thought Leadership, Dr. Michel Leonard is optimistic about the prospects for growth in the P&C industry and for an abatement of the punishing inflation in replacement costs. “After a very difficult two years, given the pandemic economy and so forth, we're heading into a better place for the P&C industry,” he says. But he also warns that the Fed has left the door open to continuing its interest-rate increases into 2025, which would shock financial markets, create new headwinds for the economy and delay the P&C industry’s recovery.

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Paul Carroll

Hi, I'm Paul Carroll. I'm the editor-in-chief at Insurance Thought Leadership. I am joined today by Dr. Michel Leonard, who among the other hats he wears is the chief economist for Triple-I, the Insurance Information Institute. We have these conversations every quarter to get his thinking on the latest outlook for the economy in general, and insurance in particular, I always look forward to these very much. So Michel, thank you as always for joining me today.

I looked at your outlook. And as usual, it's Michel giveth and Michel taketh away. I thought maybe we'd start with the giveth part very quickly to hit the headline numbers. Those headline numbers are about the outlook for the P&C industry versus GDP and the outlook for replacement costs as opposed to inflation. And then after that, we'll get into the Michel taketh away part, where you're going to talk about how interest rates are likely to keep rising even through 2025.

Having teed you up a little bit, how about you start us off with those headline numbers on P&C?

Dr. Michel Leonard

Absolutely, Paul. Again, always a pleasure to be here and to have this conversation. I can't wait to get to the second part of this conversation. But we're going to have underlying growth, which as your listeners recall is the economic driver for the P&C industry. That's going to be 1.3% [underlying growth for P&C in 2023] versus 2.1% [for U.S. GDP]. We are still a little below the overall GDP in 2023, but… there's a positive trend there. If this trend continues next year, underlying growth for the industry will be larger than for overall GDP. For 2024, we're estimating that will be around 2.6% for the industry versus 1.7% for the overall economy. Going into 2025, we’re estimating 4.5% for the industry versus 2.0% for the overall economy.

We're being optimistic there. What your listeners should take away here, Paul, is the trend. After a very difficult two years, given the pandemic economy and so forth, we're heading into a better place for the P&C industry.

Paul Carroll

Tell me about rate increases. My impression certainly has been that we're kind of topping out, and that the Fed was optimistic enough about inflation that they were going to stop raising rates. So I was surprised most of all by what you were saying [about interest rates in your outlook]. I gather that you found some information lurking within a federal report that makes you think otherwise. Could you walk us through that?

Dr. Michel Leonard

Absolutely. And I share your surprise there. We've talked before about how we were looking forward to the Fed no longer tightening. And in the last few months, we were headed that way. The financial press has been saying, "Okay, we're going to probably have one more increase going into Q1 of 2024, probably around March 1. March was likely to be the latest date for that increase, which we anticipate would most likely be 50 basis points [hundredths of a percentage point] or perhaps split into two increases at 25 basis points each between now and then.

That's the consensus. And we're of course welcoming that, as we've been saying that it's taken too long to [get to the end of the rate increases].

The Fed has been really good in the years since the 2007 Lehman crisis insofar as sharing many of their documents. And I urge your listeners to track down a Fed document called the "Economic projections of Federal Reserve Board members under their assumptions of projected appropriate monetary policy." It's a bit of a technical document, but what surprised me is that when it comes to monetary rates, they now have 25 bps [basis points] or 50 bps going into 2025. That doesn't mean that the Fed will keep raising rates [into 2025]. But it does mean that the Fed is opening a door there.

The Fed doesn't like to change overnight. They always telegraph. So now we're seeing this early telegraphing that [rate increases] potentially could go into 2025. If we tried to speculate a bit more, on the basis of the numbers [in the economic projections document], we could see a 25-basis-point increase early next year, which is less than the market consensus of financial economists. But in addition to that 25-bp increase, there may be a second 25-bp increase, for a total of a 50-bp increase into 2025.

It's a bit different [than the current consensus]. It's a bit unusual. And I thought that would be useful to share with your listeners.

Paul Carroll

I assume the implications of that are negative for the economy and for the P&C industry, right? I mean, the more you're raising interest rates, the more pressure you're putting on different parts of the economy.

Dr. Michel Leonard

Yes. And for this one, one doesn't need to be an economist. When the Fed increases rates, they right away impact housing mortgages and auto loans. Those are the two biggest components [for consumer loans]. And of course, this is largely what we insure in the insurance industry: For personal lines, we repair and rebuild cars and homes; for commercial lines, we repair and rebuild vehicles, commercial buildings and equipment.

And this is why the industry and the overall economy contracted [in 2023]. We were expecting to have a much better 2023, because we thought the Fed would really end the rate increases this year.

Going into 2024, and likely throughout the year, we're still going to have a decline in housing starts. We had a correction, and it got better, but housing starts and auto consumption will likely still lag. And that's bad for everything, not just the insurance industry. That specifically could derail our otherwise optimistic forecasts for the spread between P&C underlying growth and overall GDP.

Paul Carroll

I assume a lot of the reason for the possibility of continued interest rate increases is that the economy has stayed stronger than a lot of people thought. I saw something the other day where somebody was twitting Bloomberg a bit because they’d dug up a headline saying that the consensus on the possibility of a recession in the U.S. had reached 100% for the next year—and that headline was from 366 days previously. That 100% consensus didn't quite work out.

Anyway, I would be interested in hearing your thoughts on where the economy stands in terms of strength and how this balance between economic growth and inflation is working out.

Dr. Michel Leonard

Absolutely. The first thing is, we have this thing that economists call nowcasts. Instead of forecasting for tomorrow and next week, we're estimating current numbers. And we think growth accelerated to around 5% in Q3 and even the beginning of Q4. [The official U.S. numbers, released after this conversation, showed 4.9% growth in GDP in the third quarter.] Keep in mind, we think we're going to end the year at 2.1% GDP growth. Now we're at 5%. What does that mean for Q4? That means Q4 could be minus -1%. We could actually have a contraction.

Now remember, it takes two or three quarters [of contraction] and a few other conditions to have a recession. We're far from that. No one's talking about that. What I'm concerned about is that if this message from the Fed [tightening until 2025] starts permeating the financial press, it may bring sentiment down and people may overreact to the minus -1%, or to a much weaker Q4. That could trigger a recession in Q1 and Q2 of next year.

That actually happened in Q1 of last year. We would have had a much better recovery last year, going into Q1 of 2022, but expectations can play a big role. That's where I'm concerned about with these possible Q4 numbers.

Paul Carroll

As long as I've teed up the risks that are out there, how about if you walk us through the other ones that you've identified? The geopolitical risk hits us over the head every day with Ukraine and Israel and Gaza now. But what other risks are you seeing out there that might derail things?

Dr. Michel Leonard

Absolutely. The first one is monetary miscalculation. Paul, right now, the yield curve is fairly flat and slightly inverted. That's why CDs are attractive. While the Fed has been successful raising the full length of the curve, it’s raised the front slightly more.

What we're seeing is that the Fed is continuing to bring down its balance sheet. That's creating some liquidity. But we also know that, with rising interest rates, government debt and private sector debt is going to increase. There is talk in the financial press that we're going to have a steepening of the curve. We've been in this low-rate environment for years, and now we're heading into a world where the curve will begin higher and increase in the longer run. So it's a steeper curve.

What does that mean? In practice, not only are we going to be at these 2%, 3%, 4% or even 5% interest rates for a longer time, but we also can have a steeper curve, which could mean 6% or 7% 10 years out, which will be a very different economic environment.

This isn't just a risk of policy miscalculation, it’s the Fed tightening too long.

We are heading into this new normal. I hate that term. More accurately, we should start saying we are heading into the next normal. The next normal will have a steeper curve, but the whole curve will move up, and money will be more expensive. That further depresses growth over the long run. That average of 2% or 3% GDP growth that we had pre-pandemic is going to be a bit more challenging to achieve.

There are many implications for investments in terms of asset allocation and so forth.

Now, moving on to geopolitics. We've been saying for a long time that this inflation was supply-driven. Goods just stopped showing up. A few months ago, Paul, I presented at a group of business leaders, and we had a poll. We asked what they felt was the biggest risk: geopolitics, monetary policy, recession and so forth. Geopolitics came last across all the polls. It was cited by only 5% of those in the room. I laughed. I said, I agree with the 5% of you because geopolitics could really bring the economy to a halt.

And since then, we've had, of course, the terrible events in Israel. There’s been tremendous repercussions, but not economic to this point. But if [the conflict] continues and spreads to the rest of the Middle East, now we're going to have economic repercussions with oil and so forth. And we still have the issue of this new axis among Iran, China and Russia. That has direct implications for oil prices globally but also has direct implication on the potential for contagion in the Middle East.

Traditionally, besides oil, the Middle East hasn't been one of those triggers that leads to GDP contraction. But we're in a new environment here in this regard. In conversations with folks in the intelligence and defense community in DC, there is still not, as of the time of our discussion, a concern for contagion to Hezbollah and in southern Lebanon. However, that could worsen over the next few weeks. And obviously, that could send oil prices into a much different direction and really bring to a halt our underlying growth recovery.

We still have, of course, Ukraine. As we're speaking today, the president recently sent a proposal to Congress for a $75 billion to $100 billion aid package, which includes humanitarian and military aid. What we're seeing is the threat of Ukraine and Russia affecting the U.S. and Europe, but even more so emerging markets. In the U.S., it's raised the price of food significantly. In Europe, it's raised the price of food and energy significantly. And around the developing world, it's been all of that, but to the point of food not being available. Suddenly, you have these hot spots emerging in India and Pakistan, and we know that at the end of the day, food scarcity can lead to instability. And China could step in during that instability. These are very severe threats to the recovery.

Traditionally, financial markets underestimate the risks they get familiar with, they get comfortable with, and that have been around. That's exactly what's happening right now. Like with that poll, people need to realize that these geopolitical scenarios could change the investment environment and the economic landscape significantly overnight.

Paul Carroll

I have a feeling that what you were saying about interest rates will also increase the dysfunction in Washington, because borrowing costs are going up and will probably continue to do so. If you go back a few years, interest rates were so low that there were some people who were basically saying money is free, just borrow as much as you want. Now, it's pretty clear that there's a real cost to the federal debt. So as much craziness as we have going on in DC, people aren't going to be able to just ignore the deficit. There are going to be a lot of harsh conversations that are going to happen.

Dr. Michel Leonard

Absolutely, Paul, and that is specifically the issue related to the longer part of the yield curve. Infrastructure building, government funding and all of that is going to be much more difficult two, three, even 10 years out. And that will bring back this conversation about spending cuts and empower those who think that cutting is a good talking point.

I do want to speak about those other consequences, but just taking a step back, and not to bore people with economic theory, but [those focused on cutting] are all saying that you should run a government the way you run a household, and you should balance your budget. Well, that's just ludicrous. It's not the way it works.

Think about a household. Yes, we hopefully balance our current account, our checkbook, if we can, but for many Americans, our main asset is our home, and no one would think that you should pay off your home in one year. So even based on that parallel, if you actually look at short-term debt and long-term debt, households don’t balance their budget every year. We think of a house as an investment. For government, if we’re spending on defense, that's immediate protection. And if it's on education and healthcare, that's about preparing for tomorrow, like a family’s home. This misplaced runaway spending narrative comes back time and time again to undermine confidence in government, fueling the populism we have in D.C. Heading into an election year, that is extremely disturbing.

We'll have a few more of these calls before the election, and we can talk more, but there are really big risks that we haven't thought about. In the election of the Speaker of the House, there were threats made to members who didn't support a candidate. And those threats were credible and led to police in different parts of the country coming in and protecting families. This is Third World, banana republic-type stuff. That's very disturbing. And the presidential cycle isn’t even in full swing yet. Let's really think about that political risk for our next quarterly conversation.

Paul Carroll

I would love to talk about that. But to maybe swing things around and leave people on more of an upbeat note, would you talk a bit more about those two points we raised at the beginning, starting with describing how or why the P&C industry is going to outperform GDP? I'll ask you that first, and then we'll come back to replacement parts.

Dr. Michel Leonard

I love these conversations where we get to the context. It may seem optimistic that we're positioning the underlying drivers of the P&C industry to outpace overall growth. However, we need to remember that for many years we had P&C underlying growth that was significantly below growth in overall GDP. It's going to take a few years just to catch up. Even if we look at those optimistic numbers for 2025, where our underlying growth is at 4% and overall GDP is around 2%, we actually estimate we're going to need five years of that to just make up for what we lost during the pandemic. Remember, housing suffered greatly. During the pandemic, cars weren't available.

Now that those areas are returning to normal, we're able to catch up. But you know, it brings us back to the Fed, which keeps raising rates. And let's remember, it's not just whether the Fed keeps raising. It's also the expectation of what the Fed is going to do. That’s a very important point. And right now, there's an expectation in the market that rising rates are going to end in March. People have started to allocate their capital based on that expectation. If suddenly the Fed says, the end is going to be in March of the following year, you're going to have a lot of money moving around, and that can put downward pressure on an already volatile equity market.

Paul Carroll

How about replacement costs? As we've discussed at length, they've been just wildly outpacing inflation, which has already been high. Do you see some relief there, as well?

Dr. Michel Leonard

Yes. And I always have to caveat that it has been a tough few years. If we go back, at the height of the spread between our replacement cost increases and overall inflation, it was 8% for the U.S. economy as a whole and 16% for P&C replacement costs. Used car prices went up 40% because new cars weren't available. Construction materials for homeowners insurance spiked. Lumber went up on average 50% over three years. Remember where we came from.

And with a few exceptions, when inflation goes down, it doesn't mean that prices are contracting. They did contract for lumber and for used cars, but we're seeing an environment where prices will rise maybe 1% or 2% a year. Here again, we estimated that it will take 10 years for P&C replacement costs to get over what we had in the past three years.

The numbers look good, but it’ll take five years to get over the significantly weaker industry growth, and then 10 years on replacement costs. Those are big numbers.

That really affects us in the industry. It's difficult to increase rates fast enough to recover. Everyone is already mentioning about how much we're increasing and our profits are being compressed. We've been reducing employment in the insurance industry slightly in the last year, and we've been cutting costs in marketing and elsewhere. So, we've been able to make up a bit through efficiencies, but overall, there is significant pressure on combined ratio performance.

Paul Carroll

Well, it sounds like we're going to have a lot to talk about during our next quarterly conversation. Thanks as always, Michel.

Insurance fraud comes at a staggering cost to insurers: more than $300 billion in 2022, according to a study by ValuePenguin. In fact, 21% of auto insurance and 30% of homeowners insurance policyholders admitted to having misled their insurers to save money. (The research shows that younger Americans often don’t even recognize such fraud as a crime.)  

Good news for insurers: Advances in technology are making it harder for consumers to fudge their insurance applications and claims, which makes it easier, in turn, for coverage providers to pay for actual losses while meeting their bottom lines. Here are a few technologies on the horizon that insurers are using to improve their fraud detection.

Machine learning for predictive analytics

Predictive analytics is nothing new, of course; some sources say its history starts in the 1940s, while others date it all the way back to 1689. But the advancement of machine learning — both supervised and unsupervised — has increased the effectiveness of predictive analytics exponentially. After all, computers and artificial intelligence are way better at collecting massive amounts of data and assessing it for patterns than even the brightest team of humans could ever hope to be.

Insurers can use supervised machine learning by flagging fraudulent interactions in the data set and teaching the program to identify similar instances of fraud over time. Unsupervised machine learning can also be used to sniff out anomalies and red flags that might indicate new types of fraudulent schemes, which is useful because fraudsters are constantly innovating. 

Additionally, behavioral analytics can be used to better predict an applicant or claimant’s tendency toward fraudulent actions, drawing on data gleaned from their browsing history, clicks, physical location and more. By using these technologies, insurers are in a better position to identify fraudulent claims or applications earlier in the process.

See also: Using AI to Prevent Insurance Fraud

Satellites and drones

While it’s not the costliest category — life insurance fraud and Medicare/Medicaid fraud outstrip it — home, business and auto insurance fraud represent, as a group, the third most costly kind, resulting in $45 billion in losses each year.

Fortunately, technologies like satellites and drones give insurers literal eyes in the sky, which they can use to capture photographs and data of claimants' homes and businesses. The insurance company can save money both before and after potential losses — beforehand, by engaging with more accurate risk engineering and pricing, and afterward, by ensuring the accuracy of claims.

Photo analysis technology

Because machines understand images better than ever, insurers have been able to vastly increase their use of photo analysis technology in the claims adjustment process. According to Help Net Security, photo analysis technology use catapulted from 49% in 2018 to 81% in 2021. Along with verifying the extent of a claim, photo analysis technology can also be used to detect photos that have been uploaded as part of other claims and any digital alterations that may have been made. 

See also: The Future of Insurance Fraud

Blockchain technology

Although seldom wholly understood, blockchain technology has become more and more prevalent across a wide variety of sectors, from fintech to risk management. Insurers can use blockchain technology to produce records that can’t be changed, tempered with or re-ordered, which can be useful in certain fraud scenarios.

Take the fraudster who files the same claim with more than one insurance provider. Using blockchain technology, this could be avoided, as every claim would be indelibly and clearly recorded. The blockchain can also be used in other parts of the insurance process, such as real-time claim tracking and automation of parametric insurance applications. 

As technology evolves, so will insurance fraud detection

In insurance, as in every other industry, technology is seeing exponential developments, particularly when it comes to artificial intelligence (AI). Today, AI can be used at every step of the process, from chatbot interactions during the application stage to data analysis and fraud detection. 

As technology continues to evolve, so will the way insurance companies use it. They will shore up their business models and tighten their fraud losses, keeping those dollars where they belong.

The Duford Insurance group conducted a study in which they found that almost one in every two agents leave within three months of joining an insurance sales force, and up to 95% are gone within the first year itself. Can you imagine the spend on hiring, onboarding and training this workforce, only to incur it all over again? A costly affair!

This not only impacts immediate cost, but leads to productivity issues, and in general, a decline in overall performance.

In the previous article we covered how insurers could retain their millennial workforce through better career opportunities, state-of-the-art technology tools, and well-rounded benefit programs. In the next in this series, we will cover how carriers can effectively use AI to strengthen their hiring and retention workflows.

To help simplify this, let us take an example of an agent, Leyla, who is being considered for employment by a leading insurance firm. The 24-year old has just attended an interview and let’s see how her firm can utilize AI across her career lifecycle.  

Recruitment

Carriers or wholesalers can leverage AI and ML-based tools to sort and gather relevant details from the candidate’s  resume, documents uploaded, demographics, interactions etc. swiftly to help the recruiting team get a complete picture. AI can also be used to compute behavioral scores to make sure that Leyla is the right fit for the role and has attributes that will help her align to the company’s culture and values.

Onboarding

The first 90 days in Leyla’s career as a producer are going to be crucial. Several studies and reports into why insurance agents leave suggest that poorly designed onboarding programs are among the top three reasons.

With the right sales tech tools, carriers can build a superior onboarding experience for new hires. This is a first step to addressing churn by ensuring a positive experience in the first place.  Through ML-driven playbooks that are developed based on best practices, the insurance firm can take Leyla through her 90-day onboarding through nudges and interventions that will, for example, 

• Ask her to complete training videos due for this week and nudge her to finish any tests that she needs to.
• Remind her manager to update her with important information from client meetings
• Nudge the manager to set up time with Leyla to discuss learnings from her first sale
• Recommend best practices that other top agents followed in their onboarding period so she is able to replicate this for the same results
• Remind her to take the right actions towards a lead as she starts selling

Well orchestrated playbooks help carriers ramp up their agents faster in the first few months, reducing the cost and effort that is otherwise required in preparing agents for their roles.

Nurturing

The first three months, AI-led systems are also able to gather data and attributes to build a better profile of Leyla. Carriers will are now equipped with better insight into,

• Skill gaps and activity gaps
• The areas she needs manager intervention
• If she is at a high risk of churn
• A high will-low outcome scenario. For example, if she is inclined to sell more and reach out to more leads that she is doing, the system algorithm can identify more leads, better leads so she is contributing and improving on her performance.

This is a game-changer. To be able to predict churn and alert them to take remedial action can help carriers strengthen their retention strategy through a combination of learning programs, rewards and newer opportunities to help agents like Leyla continue in their roles and reach their potential.

Career Growth

Artificial Intelligence and Machine Learning tools are able to strengthen the talent acquisition and retention function in an insurance company. Predictive capabilities while identifying the right candidate, playbooks for a robust onboarding journey and the right insight and interventions to nurture, coach and mentor them can help solve one of the biggest challenges the industry is facing today.

Beyond this, an AI-enabled tech ecosystem can support agents like Leyla experience much higher learning curves,  better coaching and mentoring and a more rewarding career. Another upside to this is a stronger branding of insurance careers among the millennial and Gen Z workforce.

 

Sponsored by ITL Partner: Vymo

 

Dr. Heck is the CEO and Co-Founder of Nauto, a Palo Alto-based technology firm focusing on smart cars. A former Stanford faculty member, he advises long-term investors on opportunities for transformational change, including AI-integrated designs for new investment vehicles and modification of existing ones. He is based in Palo Alto, California, US.

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Insurance Thought Leadership:

At The Institutes, of which ITL is an affiliate, the idea of “Predict & Prevent” has become a major theme. Why just use all the data that insurers have to price risk, then indemnify people after they have a loss? Why not prevent losses in the first place?

You’ve been working toward that goal for years now. Maybe start us off with a quick summary of what you’ve achieved so far?

Stefan Heck:

We set out to beat the seatbelt, which was the previous high water mark for injury prevention and reduces losses by 20%. At Nauto, we now routinely achieve loss reduction percentages of 60%. We've taken some fleets from multiple fatalities per year to essentially zero, which I wouldn't have thought possible a couple years ago.

And the improvement is really fast. We see a huge reduction in risk behavior in just a week or two. Losses continue to decline for several months, then stay consistently low for many years.

Insurance Thought Leadership:

How much of the behavior change comes just because I know somebody is watching me?

Heck:

Not much, and it’s temporary: The “watching you” factor -- also called the Hawthorne effect -- produces 10% improvement for a week or two. Then it goes away. We've measured that.

The single biggest piece of lasting behavior change occurs through in-vehicle voice feedback that makes the driver aware of risks they did not perceive and prescribes the right action. If you're tailgating, the voice will say to leave more following distance. If you're using your phone, it will say to pull over to use your phone. It is an escalating set of interventions, starting with gentle behavioral nudges and real-time voice coaching and ending in alarms for the most dangerous situations. We find that, after about a week, you don't get into the higher-severity levels anymore. You get the first nudge, and you immediately know what to do. Over a couple of weeks, nearly all the risky behavior goes away. In a few fleets, we’ve even see ALL risks disappear. Historically, no insurance company thought that was possible.

We’ve tried other approaches, but voice works best.

You have to be very precise. If you tell the driver to leave more following distance and there's nobody in front of them, they're not going to listen the next time the voice says something. We don’t launch risk detection AI algorithms until they are wrong less than one time in 20, and the more mature risk detectors are down to one false alert in many hundreds. That’s when the drivers trust the systems and are grateful for the heads up on risks they missed -- we see smiles, people thanking the device or even waving to it like you’d express gratitude to a passerby who warned you of a danger.

We actually don’t alert the driver every time we see a risk. We make a judgment of how critical the risk is and only intervene when it’s dangerous.

For example, if you're stopped at a red light, we don't alert you if you’re using your phone. It's still illegal in many states, and you can get a ticket for it, but it's not that risky. It's not zero risk. You slightly increase your risk of getting rear-ended because the guy behind you may see the light turn green while you don’t.

If you’re speeding, well, everybody speeds a little, and it’s not that risky if you’re on an open road and in the flow of traffic, but if you're speeding and tailgating and then look down at your phone, now you're 45 times as likely to have an accident.

In addition to the risk coaching, we also build in real-time collision warning. You get forward collision warnings for vehicles, pedestrians, bicycles. You’re warned if you’re getting drowsy or falling asleep – those tend to be alarms because you don't have much reaction time. They eliminate about 20% to 25% of collisions.

The third piece is that, after a couple of months, 85% to 90% of your drivers will have improved, so your bottom 5% of drivers will be about 50% of your remaining risk. A portion of those drivers turn out to have medical problems. You’ll find they need glasses or have night blindness or sleep apnea or whatever. The fleet safety team then figures out how to help them or reassign them to a different route or schedule to avoid drowsiness.

Insurance Thought Leadership:

How broad a range of vehicles are you in by now?

Heck:

We’re in every kind of vehicle and every size you can imagine as long as it has four wheels and drives on roads. We don't do forklifts in warehouses. We don't do farming or mining equipment. But we do everything from sub-subcompact cars in Japan all the way up to Class 8 trucks.

About 80% of it is what's called light commercial -- so pickup trucks, vans, package delivery trucks.

We now protect a lot of very large fleets. Our largest fleet has over 30,000 vehicles and is still growing with us a lot. We also work closely with middle-market fleets, which for us is 500 to 1,500 vehicles per fleet.

We entered Japan in late 2018, early 2019, and it’s about 20% of our business. We have a smaller presence in Europe, mostly the U.K. We’re about to launch in Canada with multiple fleets and expanding in Europe, as well.

Insurance Thought Leadership:

I’ve seen reports of pushback from drivers who resent being monitored. How do you deal with that issue?

Heck:

Well, that’s mostly backlash to older camera and video recording solutions out there. At Nauto, the entire system can work with real-time warnings and coaching only, with ZERO video recording or uploading. Even for a typical deployment, where event recording is enabled, we’re only uploading 0.4%

of the driving time, so nearly all your time in the vehicle is not recorded, not monitored. I tell drivers, if you're picking your nose, nobody will ever know unless picking your nose causes you to crash. Then, it'll show up in those 10 seconds around the collision moment. We never sell personal data. The only data we share outside each fleet are things like updates to maps -- e.g. there is a new stop sign here -- or abstract anonymous risk insights like which maneuvers or locations are dangerous.

The other big concern among drivers is about tracking the number of hours they can drive, which limits their ability to make money. Unfortunately, that issue is not simple for us to fix because it’s based on federal regulation for heavy duty trucks and interstate transportation. I can tell you, based on our data, the rules are too simplistic. The rules are a sledgehammer approach, a one-size-fits-all. They basically say that, after eight hours, you have to take a break, but we see drivers who get drowsy after two hours and we see drivers who drive for 12 hours and never have a problem. With some fleets that aren’t under federal regulations, we see drivers who go for 16 hours a day and are truly fine.

From a performance point of view, you’d want a system that says, “Hey, driver, you're drowsy, take a break,” but lets the driver go 10, 12 hours if they never become drowsy. I hope some Department of Transportation regulators are reading this and making a note.

Drivers also don’t want to be recorded during breaks or while they are sleeping in their truck cab. So, five minutes after you park, our device goes to sleep. What you do in the back when you sleep or read a book or whatever is never going to be captured.

We actually don’t have to record at all. We’re just providing a safety device that provides real-time alerts. Whether it records is entirely optional for the client.

Even drivers tend to want to record collisions because, after a couple of months, the fleet is so good that 80% of the remaining collisions are other people’s fault, and fleets want the video so they can exonerate the drivers. Fleets also benefit from knowing right away when their driver is at fault. If they wait until they’re served with a lawsuit three weeks later, they pay 22 times as much as if they realize right away that they’re at fault and call an ambulance and get out their checkbook.

Insurance Thought Leadership:

How far along are you in incorporating outside data, such as about where accidents tend to happen?

Heck:

We have the historical events. We know how risky a location is both from our own data and from third-party data.

Insurance Thought Leadership:

How quickly can you incorporate information about current road conditions? Can you let me know that a vehicle in one of your fleets just skidded on black ice a quarter-mile ahead of me?

Heck:

We don’t have any way to detect black ice today because there’s no way to see it. But, in time, we’ll get more integrated into vehicles, and the traction-control system could tell us a vehicle just crossed some ice, and we could alert everybody else.

We certainly don't cover all risks yet. We've driven 3 billion miles, and we provide real-time preventative alerts for about 60% of the risks we’ve seen, and we’ll push that north of 90%.

We have 80-year-olds driving trucks in Japan, because of the aging population. If they have a heart attack, we'll detect that their eyes are shut and they’re slumped over, but it's a little late, right, so we want to keep extending how early we can detect risks to intervene before they turn critical.

Yet we really can deliver these 60%, 70%, 80% safety improvements.

Insurance Thought Leadership:

I have a feeling you get some pushback from insurers and fleet managers when you make that claim.

Heck:

I’ve actually stopped telling insurance companies that I have a technology that within two weeks can make their drivers 80% better. The executives look at me like I've just said I have a voodoo doll.

I had a conversation with a chief underwriting officer who said, “We love new technology.” I said, “Great. If we do a deployment together, how much data do you need before you can build Nauto into your product?” He said, “Oh, at least 10 years of data.” I said, “You don't really like new technology if you’re only buying 10-year-old stuff.”

Every insurer wants to prove the technology in their own fleets. But we’re in 800 fleets already, all over the country, dirt roads to interstates and crowded cities. Hundreds of thousands of vehicles. This stuff works.

The mindset is the real barrier. People fundamentally don't believe you can take any guy off the street and make him two-thirds better by next week. And we can.

Insurance Thought Leadership:

I’ve always pushed back some on the economics of Predict & Prevent. Yes, you can save a lot of money by detecting water leaks before they cause damage, but you have to install an awful lot of sensors and automatic shutoff valves. Do your savings outweigh the expenses?

Heck:

The payback is about four months because vehicle collisions are unfortunately a lot more common than water leaks. A typical fleet will have between $3,000 and $7,000 of risk per vehicle per year if you include third-party liability on vehicle damage, workers’ comp and medical payments and injuries. For a large fleets with thousands of vehicles, they will often have multiple collisions a day before deploying Nauto. We don't even factor in loss of use of the vehicle, missed deliveries, all that stuff, but we still provide an average of $3,000 gross savings per vehicle per year. Our hardware installed is $500, and service costs about $500 per year. So you earn your $1,000 back in four months, and you don’t have to pay for the hardware in subsequent years.

The payback is so quick that once they see it, customers want it for the kids or spouse, too. We don’t sell to consumers (yet!), but Nauto employees can get a Nauto systems as a perk for their family.

Insurance Thought Leadership:

What comes next?

Heck:

We’ll add more sensors. Better and more camera sensors, reading more data from the vehicle itself. As I said, we cover 60% of the risks; we want to get the other 40%, or at least just about all of that. The last 3% or 4% gets really hard.

The next frontier is where you're actually going with your black ice example. At the moment, we have about a two-week retraining cycle. We pull the risk data from our vehicles into the cloud, we rerun the models and we deploy the models back out to vehicles while parked. What you really want is to be near-instantaneous. There’s no reason why a second car should ever have to run into the same danger if one car has already seen it.

Ultimately, my goal is to make this free. This should be built into your car, built into your insurance. There's no reason for this to be an extra thing that you're buying. And, of course, we want to make it available to teens and elderly drivers, not just fleets.

Insurance Thought Leadership:

When your daughter learned to drive, did you use your device to keep her safe?

Heck:

Absolutely. She hasn’t had ANY accidents, which is rare -- unassisted teens typically have 2.5 collisions before mastering driving.

In addition to the production version, I sometimes have the latest beta release in my car as part of our dog food program. [A truism in Silicon Valley is that you have to eat your own dog food by using your own technology.] Sometimes, the new risk detectors don’t work perfectly yet while in beta. One time, we released a feature for smoking detection. It turns out that smoking isn’t just a health risk. It elevates collision risk by 50% because it can distract you. Well, the smoking detector went off in my car. What? It turned out that the straw in my daughter’s boba drink looked enough like a cigarette that we got a false alarm. We had a great laugh about that. Boba detector!

She actually started learning from the device well before she ever learned to drive, because she heard what it was saying. She’s been beta testing with me since she was little. She tells me, “Dad, you have to do what your device says.”

Insurance Thought Leadership:

Don’t you hate it when kids are right?

Thanks, Stefan. It was great to catch up.

FROM THE EDITOR  Wandering the floor at this year's InsureTech Connect, I had a hard time finding a booth that didn't somehow tie into generative AI. But I think two aspects of the technology are getting short shrift, so I was delighted to be able to explore them in this month's interview, with Megan Pilcher, a senior vice president and the insurance go-to-market leader at IntellectAI.  First is that generative AI doesn't just let you do work faster. It helps you do work that you otherwise wouldn't get around to.  For instance, Megan says: "As an insurance carrier, you'd love to have documentation on every risk that comes through the door because you are going to see that risk again. But when an underwriter prioritizes their work, documenting the accounts they did not write is a less than desirable task. We can start using AI to do that documentation and provide a summary. When the risk comes back the following year and a different underwriter picks it up, they can get a rundown....   "With today’s manual processes, someone only pulls [loss run] information if a decision has been made that at least they want to quote the risk. But would there be value in doing it at the beginning of the process, extracting loss information on risks that you would have weeded out? What could your actuaries do with that data? Could their predictive modeling be different if we were able to provide them loss data on every submission that comes to the door?  "When all the data is being manually keyed in, you're not going to get all that information; not for a quick decline. But maybe it's a year later, and you start thinking about getting into a particular class of business, or a particular line of business, and you wonder, how many submissions would you get? What would the losses be? How would you need to price it? Now you have historical data to use for evaluation." That's powerful stuff.  I realize that we'll always be limited by how much our audience is going to consume. Just because generative AI can churn out novels doesn't mean anyone will take the time to read them. But the kind of data synthesis that now becomes possible means that important, previously buried information and trends can be easily brought to the surface.     Second is that generative AI makes it easier to integrate information into someone's workflow -- addressing a truly hard problem.  If you go back to the early days of personal computers, starting 40 to 45 years ago (yes, it's been that long), the revolutions were just better forms of existing tools. The electronic spreadsheet replaced the paper one. Word processing software supplanted typewriters. PDFs were better forms of fax machines. And today, most of the focus among insurtechs is on building better tools.  The problem is that the focus on tools leads to a herky-jerky workflow. An underwriter in the middle of a file has to launch a tab and open a tool, use it and then integrate the result back into their work -- then open another tab for another tool, and so on. The same goes for pulling in data. The underwriter taps into a source, cleans the data so it fits into their workflow, incorporates the data... then moves on to the next external source.  Generative AI, while in its early days, will make it far easier to incorporate tools and external data. The tool will simply pop up, within the workflow, as needed. So will the information from external sources.  Megan explains: "When I think about all these tools that are coming up in insurance, the other part that's super critical is, how do you tie them into your underwriting workbench, so they’re part of your underwriters’ flow? Non-underwriters love to invent tools for underwriters that we think will make their life easier. Especially when tools are newer, they're almost always piloted outside the underwriting workflow. But the result is that you give underwriters a tool that stops their workflow. You're asking them to do something different, sometimes log into something different, something that they're skeptical about, and then pull the result into their workflow—and hope everyone's doing it the same way. You have to make sure tools are part of the flow, not an afterthought." Our conversation was one of the meatiest I've done in some time. I hope you'll give it a read. Cheers, Paul   In this month's FOCUS on Artificial Intelligence (AI), Megan Pilcher, SVP and Insurance Go to Market Leader at IntellectAI, delves into the significant implications of AI in the insurance sector. She elaborates on how AI is revolutionizing the industry by streamlining processes, enhancing decision-making, and ultimately paving the way for a more efficient and competitive landscape. Read the Full Interview "AI is not a new hammer, and we’re not just walking around looking for nails, but AI can be another tool in the toolbox. Carriers need to start thinking about where within their workflow they're going to take advantage of it. " — Megan Roche Pilcher Read the Full Interview READ MORE Taking Generative AI for a Spin Tools like ChatGPT and Bard offer endless applications for auto insurers, but adoption of generative AI isn’t a linear path. Read More Do You Have FOMO on Gen AI? Tech leaders are feeling pressure to integrate generative artificial intelligence into their programs, but some caution is in order. Read More AI: Beyond Cost-Cutting, to Top-Line Growth Call centers will no longer be viewed as cost centers. AI and actionbots will turn these hubs of customer interaction into revenue generators. Read More Using AI to Prevent Insurance Fraud AI-powered fraud detection and human expertise combine to fortify insurers and minimize risks for all stakeholders. Read More How to Think About AI in P&C AI applications have been used for discrete tasks but will soon drive end-to-end decisions across the entire claims management experience.   Read More 5 Ways Generative AI Will Transform Claims Generative AI will revolutionize how carriers, third-party administrators and medical management firms operate and the results they can deliver. Read More FEATURED THOUGHT LEADERS Henry Kowal Alex Sun Muddu Sudhakar Isaac Smith Yury Pensky Jeff Gurtcheff

Megan is an experienced insurance professional with over 25 years in the industry. A large part of her career was spent working for insurance carriers in roles ranging from sales, distribution management, product, and digital transformation for underwriters, agents and brokers. She has hands-on experience across several lines including personal, small commercial, mid and large commercial, specialty and reinsurance. In her role at IntellectAI, Megan leads product development, sales, and solutions. Megan is passionate about helping carriers and MGAs improve their underwriting experience resulting in new business growth, improved retention and better underwriting outcomes. Megan has a BA from James Madison University and an MBA from the University of Hartford.

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Paul Carroll

I think this is one of those moments when a technology just pops and grabs everybody’s attention. As big a deal as the iPhone introduction was in 2007, I don’t think I’ve seen anything like this fascination with AI since the first commercial browser was introduced in 1995.

IntellectAI has been working with AI for a long time. How would you frame what we’re experiencing?

Megan Pilcher

AI is not a new hammer, and we’re not just walking around looking for nails, but AI can be another tool in the toolbox. Carriers need to start thinking about where within their workflow they're going to take advantage of it.

I don't see a scenario any time soon where people will look to automate underwriters. Carriers believe that “no one can do underwriting like my underwriters can,” and I agree. But there are parts of the process that we can really start taking a look at.

It’s interesting to go back and look at the end-to-end underwriting workflow and to reevaluate all the places where there’s friction. To this point, we’ve accepted a lot of friction, as if to say, "That's just how insurance works." We didn't have a tool to resolve that friction, but now AI brings something else to the table. We get to revisit the process.

That's why I think the industry is really at the cusp of being transformed.

For instance, we use our embedded AI to do data extraction from a submission. We take everything the agent or broker said about the risk, then we take the carrier's guidelines about what they’d like to write. You put the two together, and you can start looking at any risk. Here are the positive attributes, and here are the negatives ones. Here are the ones in the middle. When you bring the underwriter in, everything is ready for them. They're not having to go look for information.

Underwriting rules can be great, especially in small business, where a lot of the decisions are binary. You don't need AI if there was a claim in the last three years and the guidelines say a submission has to be claim-free. You’re not going to write it.

But when you get to those meatier accounts, there's almost always going to be positive and negative, and the AI can bring to an underwriter’s attention those things of which they should be aware.

The underwriter can then figure out, "Is there a way for us to make money on this risk?" How do we craft terms and conditions and pricing? The underwriter gets to spend the majority of their day on the parts of the process that require a real underwriting skill set and not on mundane tasks like gathering information.

AI can also provide guardrails that help newer underwriters make sure they’re looking at all the relevant aspects of a risk. AI can help seasoned underwriters, too. They know the rules, so they aren’t looking for changes, but you can alter a guideline online and have it hit everybody simultaneously.

Paul Carroll

As you take this newly possible, end-to-end look at underwriting, are you seeing other friction points that you can address?

Megan Pilcher

One point of friction for brokers and wholesalers is to ensure that the carrier did what they proposed. What was bound? What was issued?

We can compare what was issued versus what the carrier said they were going to issue. Is there anything extra in there? Is there anything missing?

There are organizations that will do this work manually, but our AI can do it faster, better, and cheaper.

Paul Carroll

That's interesting. Both my brothers were professional poker players. And they would keep track of that sort of thing. How many hands did they play [as opposed to folding immediately]? How many times did they get into the final round of betting on a hand? How many times did they win? They would go back afterward and review their play. Was I too aggressive today? Was I not aggressive enough?

It sounds like the work of an underwriter becomes much more interesting when you take a lot of the mundane work off their plates.

Megan Pilcher

You can start upskilling your underwriting assistant staff, to put them on the journey to underwriting. You really create a career path by getting rid of some of the work that is more clerical. We think the change will make jobs more satisfying and ultimately attract more people to insurance, especially young people.

Paul Carroll

ChatGPT and the other large language models are letting you communicate more easily with AI than you could before. How does generative AI change things?

Megan Pilcher

As an insurance carrier, you'd love to have documentation on every risk that comes through the door because you are going to see that risk again. But when an underwriter prioritizes their work, documenting the accounts they did not write is a less than desirable task. We can start using AI to do that documentation and provide a summary. When the risk comes back the following year and a different underwriter picks it up, they can get a rundown.

What is the risk? Why did we not write it? The documentation helps determine what to do with it this year.

A lot of information gets lost today, and that's where embedded AI can help.

Paul Carroll

What are some other opportunities?

Megan Pilcher

I was just on the phone with a prospect. We're going to do loss run extraction for them using embedded AI. Where in the process do they want those loss runs extracted? With today’s manual processes, someone only pulls that information if a decision has been made that at least they want to quote the risk. But would there be value in doing it at the beginning of the process, extracting loss information on risks that you would have weeded out? What could your actuaries do with that data? Could their loss models be different? Could their predictive modeling be different if we were able to provide them loss data on every submission that comes to the door?

When all the data is being manually keyed in, you're not going to get all that information; not for a quick decline. But maybe it's a year later, and you start thinking about getting into a particular class of business, or a particular line of business, and you wonder, how many submissions would you get? What would the losses be? How would you need to price it? Now you have historical data to use for evaluation.

I think this part of the extracting is what you would go to a vendor for, but the carriers then can create their own special sauce. What do I think about all that lost data you extracted? What do I think about my appetite for risk? What do I think about my underwriting guidelines? What triage models should I apply to determine what risks I want to absorb or avoid?

That's where you can say to the technology folks at the carrier that there is super-high-value work to be done. These decisions are literally what make the carrier tick.

Paul Carroll

What is holding up adoption of AI?

Megan Pilcher

AI tools are going to pop up everywhere. I was just reading an article discussing an assortment of random AI tools, and one picture showed a street sign in New York City in front of a parking spot. It was really a number of signs about rules around when it's a bus stop versus when you can park here and when it's a towing zone and when there is alternate day parking or street sweeping, etc. Someone built an app where you can screenshot the signs, and it can tell you when you can park there.

I got a parking ticket this summer in New York. My husband and I just stood and looked at all the signs, and we thought, "Can we park here?" We decided we could. And we were wrong. That app would have been great to have.

But how would I have even known that app existed?

When I think about all these tools that are coming up in insurance, the other part that's super critical is, how do you tie them into your underwriting workbench, so they’re part of your underwriters’ flow? Non-underwriters love to invent tools for underwriters that we think will make their life easier. Especially when tools are newer, they're almost always piloted outside the underwriting workflow. But the result is that you give underwriters a tool that stops their workflow. You're asking them to do something different, sometimes log into something different, something that they're skeptical about, and then pull the result into their workflow—and hope everyone's doing it the same way. You have to make sure tools are part of the flow, not an afterthought.

When the time comes to take a look at the risk, the app is already there, and it's ready for you and it's part of your process.

Paul Carroll

I love that app that answers the question, "Can we park here?" I lived in New York for 14 years, off and on, and parking is really confusing. If you're an underwriter and something pops up and says, don't write this risk, or think about this, and it’s part of the process, not a separate tool, well, I can see that being really valuable.

Megan Pilcher

We're not at the point where AI should be making decisions. But what if something is just emerging as a risk, and the AI notes for the underwriter, "We should keep an eye on this. We've had some claims in this area"? It's not a process. It's not a guideline. The AI isn’t telling you what to do. But it's asking you to notice something you might want to consider in your decision making.

Paul Carroll

This has been a fascinating conversation. Thank you for your time, Megan.

Gaurav Garg, partner and global head of property & casualty insurance at Oliver Wyman, recently sat down with ITL Editor-in-Chief Paul Carroll to talk about the state of digital transformation, now that the insurance industry has been tackling the issue for years. He says many businesses have moved through the first stage, in which paper-based processes are digitized. They are now in the second phase, where they are working to use data more effectively to drive decisions—the rush toward using generative AI is part of this phase. Garg says the third phase will come as businesses emulate social media engines that “allow almost instantaneous dissemination of data, instant consumption of data and instant access to data.” Get ready for your smart assistant.

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Insurance Thought Leadership:

You’ve been involved in the digitization and transformation of insurance for a long time. Let me start by asking you for an overview of where things have gone over the last few years and where you think we can get in the next few. Then, we’ll dig deeper.

Gaurav Garg:

Digital technology disruption has been discussed within the insurance industry for over a decade. In the last two to three years, events have made it a business necessity, not just something that is good to have.

COVID forced companies to think of ways to connect with all their stakeholders — employees, distribution partners and clients. The supply chain has been disrupted, first because of COVID and now because of the war in Ukraine. There has been a kind of trade war, or at least significant friction, developing among some bigger economies. In addition, in recent years we’ve seen a surge in catastrophe-related losses (CAT-losses). And the talent shortage is a big issue, especially in insurance.

Companies are focused not just on digital connectivity but on efficiency.

Insurance Thought Leadership:

That’s a great start. Would you say a bit more about what you mean by digital disruption?

Gaurav Garg:

Over the last several years, companies have focused on what I call CI and CX — customer interface and customer experience. The front-end seems to be getting the most attention in terms of creating a digital experience. Not many companies are disrupting the way they work internally.

A truly digital insurance company has digitized all aspects of its business, entwined across the value chain.

Insurance Thought Leadership:

You talk about the three stages of innovation. Would you explain that a bit?

Gaurav Garg:

The first is what I call the foundation phase. You can’t build a truly digital company if you have a lot of manual processes. So, companies need to institute things like robotic process automation and the digitization of payments and cash management. Get rid of paper. Maybe start on machine learning. These efforts won’t be fully integrated with the enterprise, but they’re a start.

In the second phase, you start adding data-driven outcomes, data-driven decision-making, data-driven underwriting. You go toward straight-through processing [STP] on underwriting, on claims and on payments.

In retail insurance, let’s say you run 80% of everything through what we call the black box STP, and only 20% spits out as exceptions. Even there, you’re more efficient because that 20% takes advantage of the foundation pieces of digitization from the first phase.

This second phase is what most companies are building out now. One piece that is being developed rapidly is generative AI, which is transforming business. Everyone, including people who are not too conversant with computers, including people in my family, are using generative AI.

In the third phase, companies put themselves in a position similar to what you see in the social media world. These social media engines allow almost instantaneous dissemination of data, instant consumption of data and instant access to data.

Three things are holding insurance companies back. One is obviously regulation. Number two is privacy laws. And number three is the enabling technology. But I think all those issues will be solved. The laggard will be regulation, but there are already some “regulatory sandboxes,” including in Bermuda, where companies can start to experiment and innovate.

Insurance Thought Leadership:

I'm interested in exploring generative AI a bit. As someone who’s followed the technology world for 35 years now, I’m not sure I’ve ever seen anything catch on quite so fast, not even the internet. Would you please say a bit about what the actual uses are that are happening now and lay out a road map for what’s coming?

Gaurav Garg:

From what I’ve seen, working with several companies on this and with our own generative AI at Oliver Wyman, companies will start with a closed loop. They’ll use internal data to train the AI. Then they’ll move to an open loop, bringing in data from outside.

Many are starting with claims, where generative AI can assess what’s happening with policy conditions, deductibles and so forth and can measure and report on the outcomes. The same thing is starting with underwriting, where you consume a lot of external data and have to turn it into useful information.

Insurers, like all enterprises, will also use generative AI for other, general activities, such as research. If you look manually at earnings for companies in a sector where you might want to invest or want to know the state of a line of business in insurance, like D&O [Directors and Officers Insurance], that takes a long time. But generative AI can gather all that information within seconds. It’s not perfect yet, but you can add another layer of AI to screen for errors.

Finally, you have your day-to-day uses: Smart assistants, email management and other internal tools are popping up. All kinds of work will be taken over by generative AI.

Insurance Thought Leadership:

Lots of people talk about how generative AI lets people do things faster and more efficiently, but I was talking to someone the other day who said large language models like ChatGPT will also let companies do more things. For example, a state of the business report to a partner might take too long to justify if done manually, but ChatGPT could spit out a report in no time. Do you agree with her take on doing more things?

Gaurav Garg:

Yes, output will increase tremendously, because in a short time you can do much more. But this is going to throw out another new challenge: There's a limit to how much information humans can consume.

People will have to learn to use generative AI to provide precise answers to precise questions. Maybe you start out wondering what the rate environment is in commercial insurance, but then you have to be able to zero in on cyber insurance, say, and then to figure out how much of the rate increases relates to ransomware.

You also have to deal with the “hallucinations” that generative AI can produce. How do you create a reliable AI that doesn't need a second level of scrutiny?

I think we will get there very fast.

Insurance Thought Leadership:

I find it interesting when you talk about external versus internal data. At this point, generative AI basically consumes everything that’s out there, but I can imagine an insurance company, or any company, saying, “Okay, we're going to have an internal ChatGPT, and it's only going to have access to our policies, our data and so forth. And on that basis, we'll be much more comfortable with the accuracy than we would be if it just grabbed everything that was out there.” It sounds like you're seeing that possibility, as well.

Gaurav Garg:

Yes, certainly. One has to be extremely careful with the information about policyholders, but the technology will address that issue, as well.

In financial services, where I’ve worked for over 30 years, there is the concept of the maker and the checker. We might see that with generative AI: One layer of AI will be the maker and another the checker.

Insurance Thought Leadership:

What about other technologies that hold real potential for insurers?

Gaurav Garg:

IoT [the Internet of Things] will allow for connected homes, connected cars and so on, but is also a challenge, because all those connected devices present so many opportunities to hackers.

I see some companies now coming up with personal cyber. How do you make homes more secure? It could be disastrous if someone hacks into any of these home systems, with all the cameras and all the devices that control practically everything in my house.

A related area is sensors. A lot of things that were actually done on a manual basis, such as inspections, are now being done by sensor technology. Sensors also allow for more parametric insurance, not just by measuring rainfall or wind in natural catastrophes, but by measuring something like the water level in factories.

Drones are playing a big role, too, with things like roof inspections.

Another big one relates to the future of mobility, where Oliver Wyman has done significant work in our insurance and automotive practices. Two things are happening here:

As safety features keep getting better and as autonomous vehicles move toward full self-driving, the liability shifts from the driver to the technology, and what had previously been considered personal insurance becomes commercial insurance. Liability also shifts to the infrastructure, because the technology is reading the road signs. If the infrastructure gets messed up, who’s responsible in an accident?

The other part is the emergence of EVs [electric vehicles]. Safety features are making drivers safer, but if something happens, there is a much bigger loss because there are so many sensors to replace. If a pebble hits your windshield, you can’t just call a service and have it replaced at home. There are cameras and sensors in the windshield, the system has to be recalibrated… and the price of the repair doubles.

EVs also complicate things because the batteries have a life, whether that’s 10, 12 or 15 years, and the battery is the main component of the car. How do you insure the car as it is aging? In the financing world, some companies are leasing batteries separately. And you may wind up with a different battery in the car, because some companies are trying to save time for drivers — especially for truckers — by swapping in a fully charged battery rather than make people wait while their batteries recharge.

The future of mobility will have a huge impact on P&C insurance. And remember, auto insurance is the major chunk of P&C. How are companies preparing?

Insurance Thought Leadership:

That’s great. Any parting words?

Gaurav Garg:

I am personally of the opinion that companies that are fully committed to technological changes and that become fully digital will survive and thrive.

There is no other option but to meet the client and the market where they are, not where the company is. There are companies still on the periphery and still kind of wedded to a very traditionalist model. They will find life extremely difficult, because their customers will leave, their distribution will leave and their employees will leave.

But for anyone that can get past that traditionalist approach, this is a very exciting time.

Insurance Thought Leadership:

This was great. Thank you for your time, Gaurav.

We are entering a profound age of acceleration. AI is a co-pilot and brings huge opportunities for economies of the future, for the future of work, and for the future of workers. In Part 1 of our series, Reinventing Insurance with Generative AI, Oliver Wyman explores the opportunity for insurers and the impact on operations, strategy and ways-of-working.

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Sponsored by ITL Partner: Oliver Wyman

As the insurance industry is starting to evolve, the small and medium business (SMB) market becomes an interesting growth opportunity. Customer needs and wants are beginning to shift, opening new value pools. To win, thrive and gain market share in the SMB market, Oliver Wyman presents 10 considerations that should be at the top of every insurance carrier’s list.

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Sponsored by ITL Partner: Oliver Wyman

When I first read about an accident involving a Cruise robotaxi that happened in San Francisco in early October, it sounded like a bizarre one-off. In fact, now that more details have emerged, it's clear that the accident represents a real challenge to the near future of all autonomous vehicles.

As originally reported, this was the story:

The accident happened in the central business district at about 9:30 pm on Oct. 2 when a driver hit a woman who was crossing Fifth Street, not in a crosswalk. She was thrown into the path of a robotaxi operated by General Motors' Cruise unit, which was in full autonomous mode. The car hit her and then quickly stopped, with the woman trapped under the car. The robotaxi waited for EMTs to show up and take her to a hospital, where she was treated for multiple trauma injuries. (The driver who hit her first never stopped.)

But that turned out not to be the whole story. When a robotaxi encounters a situation it doesn't know how to handle, it generally pulls off to the side of the road and waits for instructions or assistance. That's what this Cruise AV did -- dragging the injured woman 20 feet in the process, while she was trapped under the left rear axle.

Compounding the problem, the California Department of Motor Vehicles says Cruise didn't initially show authorities the full video from the incident. The DMV says Cruise only showed the seconds leading up to the impact and then the robotaxi stopping -- leaving out the video of the car pulling off to the side of the road while the woman was trapped underneath. Cruise says it showed authorities the full video multiple times.

In any case, the investigation into the accident has ramped up tensions between Cruise and city and state authorities, which were already sky high, and could drag in Google's Waymo and other AV companies.

What happens now? 

For the moment, Cruise has not only halted its operations in San Francisco, as ordered, but has stopped nationwide -- it was also operating a commercial service in Phoenix and Austin, Texas, and a free form of its service in Dallas, Houston and Miami. Cruise had also announced plans to test its vehicles in Nashville and Seattle, on the way to a broader rollout.

The company has also committed to "examine our processes, systems, and tools and reflect on how we can better operate in a way that will earn public trust.” That will be key. 

Cruise had faced opposition from the San Francisco Fire Department, in particular, when it applied to operate a commercial service throughout the city. Robotaxis sometimes have trouble figuring out what to do when facing emergency vehicles and all their flashing lights, and the SFFD said Cruise had interfered with its vehicles many times. 

While Cruise won approval from the California Public Utilities Commission in early August, the DMV, just a week later, ordered Cruise to cut by half the number of AVs it was using. The DMV action followed an accident in which a Cruise robotaxi pulled into an intersection after the light turned green and was hit by a fire engine that, with its sirens on, was running the red light. Cruise vehicles had a number of other, well-publicized problems, including one getting stuck in a patch of wet cement after missing signs that warned cars to drive around it. (If you're interested in more details, I wrote about the initial approval here and the curtailing of that approval here.)

Tesla is adding to the PR problems for AVs, as it's in the middle of two trials blaming it for fatal crashes involving drivers using its Autopilot system. In my opinion, Elon Musk has been irresponsible in extolling the capabilities of what, as his lawyers are now arguing in court, really amounts to advanced cruise control and not anything close to full self-driving. Tesla won a major case in 2019 in which the company argued that any crashes are the fault of the drivers, who've been warned that they need to stay attentive and be prepared to take control of the car. But even if Tesla wins these two latest cases, the AV movement still takes a hit, because the company will have won by highlighting the limits of Tesla's technology.

So far, Google's Waymo seems to have the best safety record, but that only partly insulates it from Cruise's and Tesla's problems. Reilly Brennan, a partner at Trucks Venture Capital, who writes an influential newsletter on innovation in vehicles, says the AV world suffers from what he calls the WALTER syndrome -- companies Win Alone but Lose Together. In other words, Waymo only gets credit for its own success stories but gets pulled down by anyone's failures.

Waymo could take advantage of Cruise's pause to grab market share, although we're early enough in the move to autonomous vehicles that I doubt it can do permanent damage to Cruise, unless the forced hiatus drags on for many months. 

More broadly, I think (and hope) the effect of Cruise's temporary shutdown will be to drive AV companies toward more transparency and to push regulators to standardize how they measure safety. At the moment, AV companies are required to report accidents but are allowed to be rather idiosyncratic about how they do so. They should be reporting even more data than they do now and in a format that makes it possible for regulators -- and the rest of us -- to compare and see which operator is the safest.

I'll still flag down a robotaxi the next time I'm in San Francisco, even if it's a Cruise, but, then, I'm always technology-curious. Operators and regulators need to up their game if they are going to reach the broader market any time soon.

Cheers,

Paul