Unpredictable fluctuations and unpredictable risks
Editor’s note: This article comes from the WeChat public account “Future main discussion” (ID: futuretalking) , author Gu Beni. Original title “Focus on agricultural product price risk management under food crisis anxiety”
Due to the impact of the global new coronary pneumonia epidemic, the topic of the food shortage crisis has skyrocketed. Every link in the food system chain, from field production to retail stores, as well as circulation links, has been under tremendous pressure in this epidemic crisis. In addition, the characteristics of food consumer demand in the global market are also changing. The prices of various agricultural products may fluctuate abnormally, and the production, processing and circulation of the agricultural and food industry should make more preparations to deal with risks.
In fact, in recent years, the impact of price fluctuations in the agricultural and food field has become increasingly significant. Before the outbreak, there have been many risk factors that may seriously affect prices, ranging from long-term stubborn diseases to short-term crises; :
1) The climate problem is getting worse. This includes reduced production due to increased extreme weather. 2) Pandemic diseases and insect pests. Such as bird flu, swine fever and locust plague staged in turns. 3) Turbulent international trade environment. For example, economic and trade frictions have led to a surge in soybean prices in Brazil.
From the annual volatility curve of the food price index released by FAO below for the past three years, and the price volatility curve of several major foods in the past year: First, the comprehensive food price fluctuation range is not small, and the fluctuation range during the year 12%, while the single category is more volatile, and the fluctuation during the year can be close to 20%, such as rapeseed between 2019 and 2020. Secondly, price volatility is normal. From the curve of the past three years, the volatility range is not small. Third, it is difficult to find obvious seasonal patterns in price changes, and it is not easy to avoid risks.
FAO Food Price Index
In order to better avoid these uncertainties and even the risk impact of emergencies, a number of startup companies are thinking about agricultural product risk management.
Human-machine combination predicts the price trend
DecisionNext was an American startup founded in 2013. It is a technology company in the field of big data analysis, a service provider of SaaS solutions for commodity price forecast analysis, and its service targets are large customers.Mainly, the agricultural and food industry is one of the two major sectors it focuses on, and the other sector is mining. In 2015, DecisionNext received a seed financing of US $ 2 million, and then received US $ 7 million in Series A financing in 2019. After another 4 years of financing, it may also be related to the dramatic fluctuations in agricultural product prices in 2019, making this direction more valuable.
Meat processing enterprises are a typical customer of DecisionNext. For example, they purchase beef and other raw materials from the slaughterhouse, and process them into various beef products including cooked food, and supply them to retailers for sale. The profit of such a business operation depends to a large extent on each buying and selling decision, and is very sensitive to fluctuations in purchase prices and product sales prices.
This includes both controlling the selling price trend of products so that they can be reasonably priced in the contract, as well as judging the price of the purchase contract. Operators usually need to purchase in multiple batches at different points, then they need to judge whether the current price is high or low relative to the future trend, whether they should increase stocks or sign subsequent contracts in advance. DecisionNext said that most food, meat, agriculture and other industrial suppliers are still relying on experience and even feel that they are making market forecasts.
DecisionNext ’s product value design ideas
DecisionNext combines human empirical prediction capabilities with machine learning related algorithms, neither relying solely on people, nor counting on machines, such predictions will be more accurate, and can uncover unknown links behind market fluctuations Prompt risks to help companies optimize their decisions.
Insurance thinking limits risk to a tolerable range
The annual agricultural product price fluctuation may reach 20 ~ 30%. For example, the risks faced by dairy farmers in this regard are particularly prominent. In the past, price risks often caused a large number of dairy farmers to withdraw from this industry. For farmers, it is within a certain range of price fluctuations that can bear the risk, and insurance thinking can limit the risk to this range. Stable, a British innovation insurance company established in 2016, received 6 million seed round financing in 2019. Developed a commodity price risk platform to provide agricultural food companies with risk protection services due to price fluctuations.
In general, some large farmers or traders have more bargaining power and can better avoid price risks, which is difficult for small and medium-sized farmers. While large farms still account for a minority, there are data that only 1 in the world% Of farmers work on farms over 250 acres. Stable’s risk platform is mainly for medium-sized farmers, who purchase insurance at Stable to limit the price fluctuation risk to an affordable range.
Based on data science and financial technology, Stable provides an Index Insurance product. Index insurance, as an innovative type of insurance, continues to increase its focus. Its compensation is not based on the actual loss of the insured, but on the basis of whether the predetermined external parameters have reached the trigger level to determine the level of compensation.
Indices in index insurance generally refer to indicators that characterize the intensity of a disaster, such as drought level, earthquake magnitude, product price, etc. The Stable platform will provide quotations according to the type, quantity and time period of the commodity to be insured. The premium level also depends on the minimum and maximum prices set according to a certain price index set by the farmer. It is said that the average premium contract of Stable is 3,000 pounds, which can increase 1,000 contracts per month. However, transactions with huge amounts are not handled here. Presumably, the risks of those single transactions with large amounts are difficult to balance effectively even with ordinary insurance companies. The Stable platform can also provide other financial services, such as commercial loans.
Stable collects data from more than 40 countries around the world so that customers can match their local risks. Stable currently serves more than ten countries, including the three largest markets: the United Kingdom, Brazil and Australia. The types of Stable insurable products have been expanded from 15 categories in 2019 to more than 3,000 now.
Unicorn in pursuit of price fair start
Farmer ’s Business Network (FBN), a unicorn company, has been born in the direction of agricultural product price fairness. FBN’s original intention was precisely because American farmers faced the dilemma of low agricultural product prices and high input costs. Because suppliers adopt complex bundling sales, zone pricing and frequent customer loyalty programs and other sales strategies, it is difficult for farmers to evaluate the true market price when purchasing raw materials.
Some studies say that the difference in purchase price of the same raw materials can reach 300%, and the regional difference within an hour ’s drive is as high as 40%. FBN uses data science and machine learning technology to create an independent, impartial, and objective agricultural information network platform, which mainly serves small farmers and helps them use data to improve farm income. Users can use FBN’s services to share or review the input raw material costs, including seeds, fertilizers, and other chemical substances required by the soil. Unnecessary investment increases costs.
Reference to grain price data provided by FBN
FBN collects data from more than 14 million acres of cultivated land in the United States and tracks harvest, planting density, application time, prices, and other variables related to hundreds of seeds, chemicals, and agricultural products. Therefore, in terms of selling price, farmers can use the market average to evaluate their prices and weigh their cost control space.
FBN’s current FARMERS FIRST® product functional section
FBN was founded in 2014 in California, the United States, and is also one of Google Venture ’s investment projects. The last round of financing was in E round in 2019, with an amount of 175 million US dollars. Including providing financial services to farmers.
Risk monitoring to avoid food shortages
Agrimetrics is committed to providing data services for the agricultural and food industry. Recently, it issued a warning to people that the impact of the epidemic will force people to face food shortages. Compared with the situation after the financial crisis in 2008, there was also a serious food shortage problem, which caused people in some countries and regions to have to endure hunger. Will the global food system collapse under the pressure of this crisis? Agrimetrics is working with Microsoft to develop an AI system for predicting when food shortages will break out, and has recently received financial support from the British government. Its core technology is mainly artificial intelligence and satellite image technology with a resolution up to 13 times the industry standard. It can identify 2.8 million farmland boundaries in the UK and connect it with more than 1 billion additional data points, including weather and soil composition Wait.
Agrimetrics UK startup company, founded in 2015, Unilever and BASF are its early customers. Agrimetrics creates data marts connected with knowledge graphs, where it is easy to share data. Agrimetrics believes that the food system is quite complex, and many changes have intrinsic connections that are imperceptible, and information needs to be obtained from the roles of the global food industry system. Therefore, the data sources of the Agrimetrics data mart run through the entire system, Including government departments, retail supermarkets, farmers and consumers, etc. Multi-dimensional data can be aggregated, and in the past, these data were often island-like, and its value could not be better tapped.
Agrimetrics data market architecture overview
Agrimetrics provides regional ecosystem data services
Agrimetrics ultimately hopes that through data value mining, it can help the entire agricultural production to increase output and reduce costs. In other manufacturing industries, data value mining can increase output by 50% and reduce waste by 20%. Agrimetrics believes that the agricultural field also Can be so. It can be seen that the operation of Agrimetrics is to basically avoid the risk of food shortage through risk monitoring.
In summary
For the agricultural and food industry, the risks caused by price fluctuations may be unbearable. The reasons behind this come from several sources: shortages caused by various reasons; excesses caused by various reasons; opaque price information; tariffs, trade restrictions , Agricultural subsidies and other policy impacts.
The direction of agricultural product risk management will receive more attention under the impact of the global epidemic. The above-mentioned European and American startups have all received external financial support in the past year. Their entry points, some tend to cure the symptoms, and some tend to cure the root cause, but all put their core capabilities on data acquisition and value mining. Collect data from as many sources as possible, combined with machine learning technology, in order to gain a more accurate insight into changes, get early warning of risks, and avoid unpredictable blows.
About the Author:
Long-term engaged in innovative business research, and provide strategic consulting for technology entrepreneurship team. Master of management, nearly 20 years of experience in consulting and financial media. Co-founded Arterial Network VCBeat in 2014. He is a special author of China Europe Business Review, Titanium Media and other famous media. Exchange WeChat: gugreaty; WeChat public account: future discussion