Changing the Risk Profile of Agriculture: a farmer's perspective on parametric insurance

Never miss an episode of AgTech...So What? Subscribe here!

We recently launched a three-episode deep dive into the future of risk and insurance in agriculture. Over the course of the series, we heard from one listener who offered to share his experience using novel insurance products to manage the risks of both too little and too much rainfall in his own farming operation. This from-the-field perspective was packed with insights, and was such a powerful contribution to our learning that we asked his permission to use the audio for this episode.

Tom Ferguson is a farmer in Northern New South Wales, Australia, and this week you’ll hear a conversation between him and Tenacious Ventures Co-Founder Matthew Pryor. They speak about:

  • Tom’s specific exposure to climate-risk, and why this has led to him exploring new options for insurance
  • His process for collecting data, identifying high-impact risks to hedge against, and using this data to strike tailored, parametric policies with insurers
  • What the impact of using more data on the farm can be for new insurance products, and what’s holding back the integration
  • His adoption of new agtech on the farm, and what factors enabled or inhibited uptake within the business. 

Useful Links:

Sarah Nolet  0:02  
Hello and welcome to AgTech...So What? brought to you by Tenacious Ventures I'm Sarah Nolet. One of the things we love most about our podcast is the opportunity it gives us to learn from our listeners. Back in June of this year, we made the decision to learn out loud about the future of risk and insurance in agriculture. It was a three part series that honestly came from our own digging around, reaching out to experts in our network, and testing hypotheses with each other out in the open. And during the series we were pumped to hear from a listener who seemed to be as interested as we were in the challenges and opportunities within ag insurance as it exists today.

Tom Ferguson  0:41  
I've asked this of a state agribusiness manager: "we're spending money to ensure that we're paying back any liabilities to you, can you give us a cut in our margin?" And his answer was, "ah, we've really got no appetite for that. We already know we can get our money back, and you're not a risk to us anyway. So it doesn't really matter." That is a really poor answer. Maybe we should go and find someone who does align with our values.

Sarah Nolet  1:07  
That's Tom Ferguson. He's a farmer in northern New South Wales. And after listening to one of our episodes about parametric insurance, Tom reached out to share his experience as a farmer and policyholder, and the work he's done learning about insurance to reduce risk on his own operation. Tom recently sat down with my occasional co-host and co-founder at Tenacious Ventures, Matthew Pryor to share his experience for the benefit of our learning and our theories on where the insurance industry might be headed. We found his insights so relevant, especially in the wake of our previous insurance discussions, that we asked Tom's permission to share them with all of you. I'll drop you in here where Tom gets into his early explorations of using insurance on his farm.

Tom Ferguson  1:48  
I took on the role of managing the cropping. And that's where the risk management for us really started to wind up. We've been through until two years ago, like '15, '16, with two of the best years we've ever seen. And then '17, '18, '19 were three of the worst years ever recorded here. So we saw the huge fluctuation in seasonal variability which we both say monthly that it was the best thing that could have ever happened to us, because it's made us understand the risks that we play with. And now we're going into potentially what could be one of the wettest years. So, how we go about managing this risk is probably top of mind to me, I suppose in years gone by with the risk in farming, people haven't really taken a proactive step to try and manage that risk. So that's become a big part of what we do every day.

Matthew Pryor  2:45  
So what are the specific circumstances that represent those kind of risks in a weather and climate sense?

Tom Ferguson  2:53  
The leading one is lack of rainfall, our production is driven off stored fallow moisture, so lack of rainfall through the summer months, then lack of rainfall through our growing season. This year, there's been too much rain at planting, we haven't physically been able to get the crop in the ground. But that's a that's probably specific to 10% of years or 5% of years. And probably the other one is rain at harvest, so, degrading yields and quality at harvest time is probably the other main drama we have.

Matthew Pryor  3:26  
When did you start understanding why parametric insurance was a good match for those kinds of risks that you are exposed to?

Tom Ferguson  3:34  
Parametric insurance has been around commercially for 30 plus years in Australia. It's just never been delivered to ag. I don't know what that reason is - there's a fairly high lack of uptake with all of these products. So the insurances that first started getting a roll were the multi peril, insurances, and that's where we started. With this. I don't think anyone's offering a multi-peril in Australia anymore because the model was flawed. We got five out of six payouts. So there's a problem with that model, like the whole idea of insurance that you don't want to claim every year. And everyone has a different opinion on this. But the idea is to take out the highs and lows, we want to buffer ourselves from the extreme. So those multi peril products, the fact they were paying out so often meant that you're playing in the wrong space or trying to cover too many perils for the premium. So going into the parametric insurance, you're able to tailor multi perils, I suppose I should clarify this, covers every peril it's on, it's on $1 per hectare agreed value. If you don't meet that value, they will top up. So when we start looking at parametric insurance, we are then having to go: it's not every parameter. It's either excess rain, lack of rain, hail, that's coming into parametric insurance like if it's specifically and independently measured, they will generally write a policy on it. So then it's back to the farmer or the consumer of that product to work out what the risk is in their business.

Matthew Pryor  4:39  
As we dug into that more, it felt like maybe there were two aspects about why things like multi-peril or more traditional forms of insurance were CAFO. First is, as you say, if the policy is paying out all the time, like it's going to be expensive for everybody. But the second also is, it seemed maybe before a lot of the stuff was more digital, the tailoring part, perhaps was harder to do for a lot of people like you had to have a agronomist or a specialised salesperson who could work with you to help you tailor it. Whereas maybe a bit more these days are the more modern products, perhaps and I'd be interested in how you take delivery of these products, but the ones we've seen that you can actually get on a kind of dashboard and dial it up a bit and say, "these are the specific events that I'm interested in. And this is how I want to tailor it specifically for me."

Tom Ferguson  6:04  
That's right. Before there is someone selling you that product you have to know in your business, what risks you're facing. No one can tell you that. So the process that we went back, and we started looking at income and expenses per millimetre of rain, over 25 years of financial data. And looking at those big ticks, what made that boom or what made that bust, and then looking at our fallow rain to our in crop rain and trying to decide where our biggest risks were and then coupling that with, right, okay, our biggest risk for the last couple of years has been excess rain at harvest, right, let's look at that specific period. And this is not something anyone's going to be able to tell you and every farm will generally probably be different given their location in the country. But we know that if we've got a ripe crop sitting there on the 25th of October, our proportion of early crop is 30%. So it is going to be the ripest. If we get a storm in that time, and it dumps 20 mils of rain on us. And October's generally starting, well it is getting hot, so 25 mil, if the sun comes out two hours later or the next day, that will not put us in a situation where we are losing quality. What happens though, a couple of storms in a row, then that puts us in a situation where we're sprouting, we're losing test weight, we're losing quality, and we're losing money. So that's the first risk is that we get days of rain together. And the other risk is we live on a gigantic floodplain. So what happens if we get a huge amount of rain in the six weeks that we are trying to harvest, which makes the ground completely untrafficable. And that might be 80 mil of rain or 100 mil of rain in that time period. So trying to see what makes our business tick. On the flip side, at the end of 2019, when the drought was really biting hard, we decided to take out one for rain. So the complete opposite we're trying to hedge against it raining now we're hedging for it to rain. And we said if we can get 120 mil of rain in this period, that'll get us out of trouble, we'll have enough moisture to plant sheep food. And we ended up with 80 mil and we grew enough feed to keep us through the next two months until it actually started raining again. So that's about knowing your production system and what you need. And then hedging against the biggest risk in that concept and that idea that you're trying to get through.

Matthew Pryor  8:44  
You also mentioned they're coming in and doing this economic analysis over a pretty long period worth of data. Two questions for me the first: is there anything you think in your background or your kind of journey into being in this role that made you perhaps more interested or willing to do that kind of analysis? And secondarily, how hard was it to bring all that data together? And when you think about other people doing that, what are the kind of enablers or blockers to allow people to be able to do that basic analysis that they can then be in a position to tailor these products well.

Tom Ferguson  9:19  
I suppose on the data part of that, first, everyone's got that data. If you don't have it at your fingertips, the accountant will have it. They know how much money you've made out of stock, how much money you've made at a crop even if you don't have a detailed analysis on your accounting software, you'll be able to get it from your accountant and the BOM's already recording all of that data. Most farmers are actually really great at recording their rainfall data. It's putting that from a rainfall chart into Excel and being able to analyse that financial data and the environmental data. And it may not be rainfall, it may be heat, too much heat at the end of your canola flowering or frost or it's not necessarily rainfall. The thing that's driving us, we're fairly early in our farming careers, and like, we've got two businesses in farming, your production business and the land business, that land business is increasing in value every single year, no matter if you get out of bed or not. The production businesses is the thing that we spend a lot of our time in. But if the production business fails, it's easy to just go and say, Oh, we've got a bit more equity this year so doesn't matter, we can borrow a bit more money. I suppose our view on that is that we don't want to be doing that we want to be limiting the risks in the production business every year, which we can do this with this insurance policies, and being able to take all the emotional decisions out of this, and put some metrics in our production business so that we can grow both these businesses quick as we possibly can for the next generation,

Matthew Pryor  11:00  
That kind of Excel, doodling and stuff, you talked about then, were they skills you already had, was that stuff that came from your kind of business and marketing background, or just interested in that willingness to really dig in and use the data to build a model that then helps you buy the parametric insurance?

Tom Ferguson  11:18  
I think you've got to want to delve into numbers like that. I know it's not for everyone, everyone's very different in that aspect. It's just something that I I enjoy doing. And I love taking the emotion out of things. I'm not an emotional decision maker at all, the numbers never lie. If it's making money with the numbers, then yeah, emotion has a little part to play in it, but not a lot. There's no no room for emotion like that in farming, I don't think. It's probably come from bit of my background. But basically, it's just the want to make sure that you're not losing out in those big years and not losing out in the really poor years either.

Matthew Pryor  11:53  
Do you see, you mentioned where there's a big difference between you being willing to do this yourself versus helping other people to do it? And the degree to which they're actually motivated to do that? If you're at a barbecue having a chat with friends and family, are they kind of "oh there goes Tom with insurance again?" Or is it a sort of thing that would come up in conversation? Would people say that it's a bit of an obsession of yours? Just interested to know how it goes.

Tom Ferguson  12:21  
It comes into a fair bit of it. Like when you're doing planning, harvest logistics and stuff like that, geez, we can't get that extra header for harvest this year. So to put it into context, if we're struggling to find that extra header, so we'll go we've got this insurance policy. So we've hedged against the part of the risk that if we don't get it all off, we are still covered, we will we'll cover that downgrade. So it does come into logistical and operational talk all the time. And yeah, it has become not so much an obsession, it's just a tool to help us with our planning of what goes on in this farm.

Matthew Pryor  13:03  
Sometimes when I'm using tools that I'm not super familiar with the experience can be a bit suboptimal? Are there occasions or what have you learned with using parametric as a tool that are maybe some positives, or or some notable negatives in terms of how it works, or not fully understanding the edge cases of how it works?

Tom Ferguson  13:22  
There's the guys that are offering these policies in Australia, they're fantastic with helping, like all they want to see is this go big in ag. So they're very happy to help tailor things for you. But again, they'll sit there and say, "well, I don't know what's going to make your business tick, I don't know the backstory of why you're trying to do this, even if I did, I probably can't tailor it any more, you've got to put the legwork in and work out what you are trying to do." But I suppose the unknown in the past was they plug everything into their software, and spit out a quote for you. If it's say they're trying to insure for too much rainfall, moving your insurance period, by a matter of days, either side of where you want it to be could be the difference of five or 10% in premium given what's happened in the past. So being able to talk to those guys and explain what we're trying to do. And then them trying to build your policy where you can get the best value for money. And what percent premium you're willing to pay to cover that risk. Now that can change every year, depending on what your situation is. I've been a part of, I suppose a bit more backstory, a part of the New South Wales Farmers Grains Committee for a number of years. I'm not on it this year, but have been in the past, and a part of me being on there was trying to see where this could go.  Instead of giving out money for the drought, what appetite the government have to step in and say "yeah, let's help underwrite these policies and these products. so that we're not handing out money in droughts or floods, or let's let everyone educate everyone to take the step and do it themselves. We ended up getting money out of the New South Wales Government to run a pilot programme and do a bit of research into this, the NFF got the money and ran it, I was a little bit disappointed with the outcome. And I don't know whether there's only a certain percentage of the population who are worried about ensuring this, some guys put money in FMDs, as a bit of risk management, some guys will hedge currency, some guys will have off farm investments, however they want to play it. So there's a bit of discussion to be had there about how everyone is hedging their risk, and everyone is different. But no one's really hedging their risk in a production sense, like with the weather, and the weather and emotional decision making are the two biggest risks we have.

Matthew Pryor  15:56  
A couple of things that seem worth digging into there. First would be the farm data side. And you mentioned, obviously, there are people that do have it, maybe they don't manage it or it's not all brought together. One of the things that we talk about is, there's probably a lot more to gain from being less worried about bringing data together than there is to be lost. Do you see there being possibilities for these services to extend in that idea of parametric insurance, like helping with that problem of bringing all that data together in a way that you can do more of this kind of scenario modelling to save people having to jump into Excel and do it all themselves?

Tom Ferguson  16:34  
I was only talking about this the other day is farm data, it's like ISOBUS hooking tractors to implements - it all sounds great, until you actually go and do it, and then it sounds horrible. And it is horrible. There's no platform where we can store all this stuff nicely. No, like I understand why it's not having a go at anyone. It's all in different formats where everyone wants different things. And there's different outputs and inputs. And then there's until we've got a place where we can store all of this stuff, we've really, I think we've really got our heads in the sand. We're trying to integrate some of these things like so we've got some Goanna private weather stations. Now, with the guys who do our parametric insurance we said to them, we put a last year, we put our interpolated grid over one of the grid points was right on top of our weather station. So we said let's do a bit of a trial. And let's see how this plays out because the parametric insurance is done on interpolated data. Now, our rain gauge said one thing, the interpolated data set another thing and that cost us about $250,000 Because our rain gauge physically recorded what happened, but the interpolated data didn't agree. So what we're trying to do and my point is that everyone is sceptical in agriculture, aren't they, I think I can throw blanket over everyone and say everyone's pretty sceptical, especially of new things and we've got the same scepticism in our business, sitting there saying "no, we signed a contract on interpolated data." So now we're doing it retrospectively looking at what the interpolation said and what our Goanna station said, so we're trying to get the reinsurers to come to the party and go well, okay, that's correlated enough, in the past to progress this forward. Let's now say let's come up with an agreement that if if the interpolated data and the private weather station data, correlate within X percent, then everyone's happy, we'll use the data off the weather station. If there is a big discrepancy, how do we handle that discrepancy? I think once we push through that barrier, then everyone can go my rain gauge is there. It's rained. So that's my policy. And if really still sceptical, go and put a manual gauge next to it. Like, if you really want to make the data more credible in your own eyes. But yeah, I think we need to push through some of those data barriers yet to really make all this stuff hum, but we're just not there yet. There's no platform to make this work. I don't know. And I don't know what the answer is. I'd love it. If someone could tell me.

It is a tough one, as you say, and the scepticism that's there. We tried to dig into that too, in terms of what is this fear that sometimes attends to hold people back and pointed to one problem or another class of problems, which is that it's actually technically hard? Like the data isn't in the same format and when it's in inches and ones and millimetres and all that kind of stuff. But then secondarily that that I suppose fear to some extent of while a bit of like share it with this mob then is that going to come back to bite me? I think you've just given a really positive example of if the reinsurer is prepared to take yours and nearby weather station data to improve their model, it's a better result right and gives you a better result. And that was the other point we were making about the difference between generally sharing data in a supply chain sense versus specifically for insurance. Because it's pretty clear in your example you just gave were, okay, the reinsurer's gotta get comfortable. But once they're comfortable, it's clearly better for both parties that we agree on what is more accurate, more regional, more local, and therefore, properly represents the risk you're exposed to.

That's right. There's positives and negatives to sharing data. As you said, that's a positive example. A negative example is private stocks reporting of grain supplies, but they can't be they're not one in the same. You can't just say data. And then all data is bad because of this. It's all specific to what you're trying to do.

Matthew Pryor  20:43  
Another kind of question I had is, so you talked there grain is another fantastic example of that incidence of where the rain event that you were actually exposed to was different. And we know that weather is variable, especially sub regions, and all that sort of thing. But also, we have this overlay of increased variability that is coming along with a changing climate. And you talked about before, like sliding the dial up and a two week change made a very significant policy difference. What are your thoughts there about that sort of unpredictability of pricing? There was an article yesterday on the ABC News about insurance policy prices in areas just becoming too much for people. What are your thoughts there in terms of parametric and that idea of pricing a) being hard to know upfront and b) as weather risk likelihoods increase, surely policy prices have to go up.

Tom Ferguson  21:41  
Insurance can be as cheap or as expensive as you want it to be, especially with parametric because you're coming up with metrics. So how much risk do you want to insure, that will reflect the price of the policy, you know. House insurance sense, if you live somewhere where they have recorded a flood two times in every 10 years, of course, your insurance is going to be expensive. If expensive  insurance is your main concern, sell and go and live on top of the hill. Your insurance will be cheaper every time. It's the same in parametric insurance, if you want to insure you're going to get above average rainfall, five years out of 10, then your insurance will be very expensive. But if you want to insure decile one and decile ten or both of them, then it will be cheap because its incidence is so low. So you can make it whatever you like. And I can say I want to make sure we're going to have an 800 mil rainfall this year, we're already at 580. So probably not much point me insuring that because a) we're halfway through the year, and we're nearly there, moisture profile will carry us through anyway. And the chance of us getting 800 mil a year is like two out of 10, it is going to be expensive. The way I can see us pricing these policies, and this is after a bit of experience with them, our main risk is no rain. That's if you look back in history, we are drier than we are wetter. And you can't get too cute with how we work this out. Because you'll drive yourself insane, you won't be able to find an answer. So we've got to be a little bit broad with that and say, Okay, if we don't get 60 mil of rain, every quarter than every quarter is a payout situation. So we pay a premium, every quarter. And that might be a bank guaranteed premium over five years. And if we get our 60 mil great, that's fantastic, we're halfway to average, every quarter, if we get that if we don't, then we know that there'll be whatever the value of the policy will be $250,000 every quarter coming in.

Matthew Pryor  23:43  
That makes me think, you can talk about people's whether it's interest or skill ability, you also refer to the company that you work with, tthey're pretty good at helping out. It feels like there is a kind of role there where the digitally native version of an agronomist should have just as much familiarity with these tools as on the agronomy side because of those increased kind of production risks that everybody's going to be exposed to. Do you think that's where, as this grows, people will source that kind of skill from?

Tom Ferguson  24:18  
As the appetite grows, there will have to be someone sitting in the middle there I suppose. I've asked this of a state agribusiness manager, I said "where do you guys see yourselves fitting into this? We're spending money to ensure that paying back any liabilities to you? And we don't have to do that when the no obligation to do that?" And his answer was "aw look, wait, we really don't know anything about this." And I said, okay, let's put in a different term. If we're spending this money to ensure you're getting your money back, can you give us a cut in our margin, because we're being more responsible. And he said, we've really got no appetite for that. We already know we can get our money back and you're not a risk to us anyway, so it doesn't really matter. And I said that is a really poor answer to what's trying to happen here. Would you lend harder if we had a five year policy to ensure that we had x money coming in? If it didn't rain? He said, no, probably not. I said maybe we should go and find someone who does align with our values.

Matthew Pryor  25:18  
And it's another one of the things we imagine with parametric because it's easy to deliver digitally, is whether or not the extension of parametric style insurance might shift to somewhere else in your supply kind of universe. One of the things that seems at least logical would be: if you're forward contracting your grain, the aggregator or whoever you're striking that forward contract with they know obviously, what grain, what variety, they know where you are, they know roughly what abiotic stresses at what point in your season would represent a risk to them. Can you see a world potentially where we move to that sort of more embedded style of insurance? Like when you check out at a airline booking service and it says, do you want travel insurance with that kind of thing?

Tom Ferguson  26:04  
Yes, that's already happening. But I suppose to put it in broad terms like that GrainCorp, say in the drought a couple of years ago, they had a parametric product where if east coast grain production dropped below X hundreds of 1000s of tonnes, I can't remember exactly what the parameter was, then they received a pay and I think it was somewhere in excess of $80 million.

Matthew Pryor  26:29  
Yeah, I do remember that one. Yep. Yeah. And that was that date, otherwise had a pretty bad time leading up to that, I think. And then that was a significant payday.

Tom Ferguson  26:38  
That was a pretty crafty insurance policy. So they're doing that on their scale in terms that they don't need to come down to individual scale. There's a lot of admin involved in trying to do that. So I can't see how that I suppose it could work is you can never say can't see how it work. We can't say how to work now. But there'd be a solution to it for sure.

Matthew Pryor  27:03  
That's one thing that we often wonder about too, which is it sometimes after people like yourself, start using this product, you actually end up using it in a different way than what you thought you're going to do with it when you started. Because these products often by their nature are actually more adaptable. And then at some point, you'll go ah, wait on, I can do X and Y. Have you had any experiences like that, where you've found that that kind of additional level of flexibility suited a scenario that you wasn't necessarily one of the ones you were thinking about from the outset?

Tom Ferguson  27:39  
Ah hail, traditional hail, we al know how traditional hail and fire insurance, we had a conversation about hail and it's already happening parametrically. So it's very hard to independently measure hail size and intensity that's done after the fact with traditional hail and fire someone assessor comes out has a look and generally try and take them to the worst part of the paddock. So you don't get excessed out of your pay out. But with the parametric insurance growing, they are trialling hail sensing pads in orchards in the States. And that's measuring intensity and size of hail. So we are hopefully going to be trialling that this year on one paddock, we're just working out what it'll cost traditionally compared to what it'll cost with these sensing pads. And yeah, we'll do a trial on it this year I never ever thought that would be a possibility. Because how do you measure hail size, intensity, and standing out in or saying that your crops wiped out the next day.

Matthew Pryor  28:40  
And that was another thing that seemed pretty fundamental in terms of just the economics of how parametric insurance could eventually work that you don't need an assessor to go out go out there, right? You don't need somebody to come and estimate the actual loss that occurred. It's simply: the event did or did not occur. And you have previously agreed that you'll get paid when that event happens. It'll be a whole lot cheaper to do that at large scale. If lots of people want to jump on board.

Tom Ferguson  29:10  
Yeah, absolutely. We're not waiting around for an assessor or with the multi peril running a header through a paddock to get yield data to say that you didn't have enough there to bother harvesting it. Like that's antiquated, isn't it? So yeah, it is adaptable to big scale. That's exactly right. Because you don't need that manpower. It's where the data comes in. If everyone can trust the data and has a platform for trusting the data, then there's no reason it can't be scaled very quickly.

Matthew Pryor  29:35  
A kind of final question. You briefly touched on what the future of parametric might look like you've obviously had more experience with it than most and you've referred to needing kind of strong service providers who can help. Looking a little further ahead do you have a vision for what the future parametric can be? You touched on the hail thing? Is there stuff that's further out on the horizon that you're pretty keen to see?

Tom Ferguson  30:01  
I hope I don't know the answer that question. I'm glad I don't because there's someone smarter than me thinking about it somewhere. Hopefully the options are endless if you can find a way to measure it independently and the reinsurer is happy with it. That's the only limits.

Matthew Pryor  30:18  
One of the things that we've also thought a bit about there is almost like the emergence of kind of really specialised reinsurers, that the more data you can get access to, the more likely it seems that you can build pretty specific models that aren't just generally about weather but are specifically might be kilos of weight gain, and in a particular breed of cattle on a grassland system. Do you see it going that far, potentially?

Tom Ferguson  30:45  
I don't think it can go that far. I am, again, not being negative, I hope it could get to that. But just from what I know of how the reinsurers like their data, that's not going to be measured. And it's not going to be specific and independently measured, unless it's a walkover weighing system or something like that. I think probably where it's going to stay until there's enough uptake in that situation is well, that producer knows what he can do if he's got grass as far as weight gain goes, grass productions is by rain and sunlight. So if we don't have rain, we don't get grass, we don't get weight gain. So I think if you're measuring that weight gain to that point, you'll be able to work it backwards and go but rain is the easiest one at the moment. If they want to come to the party and do walk over weighing or some sort of an algorithm to work that into a policy that I'd love to see that that'd be great.

Sarah Nolet  31:37  
This conversation was so absolutely jam packed with insight it was honestly hard to choose. But a couple of things that Tom mentioned have really stuck with us. First, I really liked the distinction Tom made between his land business and his production business and the trap that it's easy to fall into of subsidising an unnecessarily high risk production operation with the margins and equity of a land business. It seems that this conscious division of the businesses help Tom understand the need and the opportunity in limiting his risk on the farming side, which is helping him make both sides of his business be more successful.

Then I love the idea that the greatest risks to Tom's farm are weather and emotion. Especially because those two things are so often caught up together. Tom has been able to use parametric insurance products to mitigate his risk on both fronts. But it's taken a lot of effort and learning.

Which brings me to a final takeaway about how important the data, the knowledge and the deep understanding of his business have been in Tom's journey into the parametric insurance world. Despite the significant upside that's possible with these products, I think it's clear that they are not for the casual dabbler in my mind to pressures or when alter that over time. On the one hand, I think economic and financial pressure will continue to favour farmers like Tom and disempower others who don't want to make the investments in data and know how. On the other hand, I also think the current wave of ag tech we're in will require and maybe even bring with it a serious upskilling for farmers and their teams of staff and advisers. So that's it for another episode of AgTech So What. Thanks to my co host and co founder Matthew Pryor and thanks to our guest and listener at Tom Ferguson. And of course, thank you for listening. For more information on any of the resources mentioned in this podcast, please visit our website tenacious dot ventures. I'm Sarah Nolet, catch you next time.

Key takeaways