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Effective ag risk management requires accuracy. That’s more critical than ever now that extreme weather patterns have shattered the predictive nature of insurers’ and banks’ risk models. As a consequence, their prices go up for farmers, who already exist on thin margins. At the same time, farmers are facing rising input prices. McKinsey research indicates that 67% of farmers cite increased input prices among their top concerns for profitability over the next two years.

Yet, many insurance companies assert that 10-15% of both the underwriting and claims processes in the ag industry face inaccuracies. The insurance industry alone estimates it pays out in excess of $100 million because it can’t accurately measure the cost of claims. And it takes months for farmers to get a claim resolved.

But science-backed damage reporting using artificial intelligence and underpinned by a dense, heterogeneous data set now makes it possible to understand yield loss with a very high level of accuracy for claims approvals. AI and machine learning can generate keen insights all the way down to the plant level, soil type and area to deliver a near real-time understanding of the risk profile for a particular crop, field or entire farmland portfolio. That allows insurance companies and banks to determine the risk profile and more accurately price for each policy and loan. And it helps growers get a pricing structure that better suits what’s transpiring at the field level.

Our experience from more than a decade of work as a data and analytics company with a specialty focus in agriculture has proven that this technology yields 10-15% in cost savings for farmers and improves underwriting and claims speed and cost by up to 15%.

The whole ecosystem wins.

Here are concrete steps that growers, insurance companies and lenders in the agriculture industry, can take to advance their operations with greater accuracy, speed and profitability.


Dig a little deeper

Ag is one of the last great analog industries. It still relies heavily on more traditional time-consuming and manual processes.

And, understandably, farmers who have worked a certain way for decades would have some apprehension about this newfangled technology and what it’s going to do.

But don’t be afraid to look at and start using AI-based products. Ag tech providers who have had AI solutions in place for the last seven to 10 years have demonstrated a high degree of accuracy and stability.

Explore and embrace these technologies – and insist that your financial services providers leverage this critical technology – because these solutions do benefit all.


Find a solution that addresses data fragmentation

The ag industry consists of a very integrated ecosystem of bankers, farmers, insurers and, more recently, sustainability leaders and teams. Each of these groups relies on its own data set. These data sets don’t agree with one another. That has troubled the sector for at least a decade, leaving everyone wondering whose data set best represents what’s happening at the field level.

Seek a partner that provides a single source of truth, sharing AI-driven insights with farmers, lenders, insurers and sustainability teams. This will create a bridge across the ecosystem.

Keep in mind that AI-powered insights are only as good as the data on which they are based. Be sure that the AI insights you plan to act on are based on a dense data set that includes data from and about field IoT sensors, legacy satellite data, yield data, weather data and much more.

The best AI training data is both heterogeneous and very accurate over a long duration, ideally decades. That allows AI to spot anomalies at the field and plant level that other sensors can’t detect – and see them in advance so farmers can act. That benefits everyone in the ecosystem and allows for a light touch instead of a heavy application of water, or other inputs, that ruins budgets and sustainability goals.


Avoid being held captive by a closed ecosystem

John Deere has been on the front foot of the digital farm going back at least 20 years and has done an amazingly great job at it. But it’s a closed ecosystem. For that approach to work well, you need to go all-in with Deere on your tractors, your trailers and all your other farm equipment. That’s going to be expensive.

As John Deere continues building out its proprietary approach to AI and the digital farm, the rest of the industry has moved forward. Now you don’t have to be held captive by one company.

Solutions that democratize the use of AI technology are now available, so everyone can use AI.


Don’t wait

The  U.S. Department of Agriculture’s Risk Management Agency is in the process of evaluating new digital technologies that increase accuracy and decrease risk across the ag ecosystem.

But there’s no need to wait for government agencies to move forward to get started with AI.

Welcome it now. Start leveraging these technologies to benefit yourself and the whole ag ecosystem.

By providing a more accurate understanding of what's happening at the farm and field level, AI allows for crisper and more accurate pricing on the front end and payouts on the back end. This acute accuracy empowers banks and insurance companies to lower their cost of generating loans and insurance policies and provide the appropriate payouts when damage claims are submitted, which equates to hundreds of millions of dollars in savings. Farmers stand to benefit from more affordable loans and policies, and by getting paid quickly for exactly what they lost.

AI is clearly the best way forward.



Agribusiness AI Risk Management

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