Data Acclimation

FinTech for Ag Finance Institutions to

Future-Proof Their Businesses

US agriculture is under threat. As a changing climate wreaks havoc on once-bountiful cropland, decades of business-as-usual are coming to an end. With worsening droughts alone expected to cost U.S. agriculture $10-14 billion annually, the profits of growers – and returns for their financial backers – face mounting uncertainty.

A new landscape of water and climate risk are phasing out old risk mitigation methods in agricultural finance. That is, traditional loan and investment risk identification and mitigation tools and methodologies lack the specificity and speed needed for ag finance institutions to understand how water and climate risks truly affect their portfolios.


Large-scale, blanketing climate analytics do not provide portfolio-specific granularity. Risk data that pinpoints exactly how drought, wildfires, and more impact every unique parcel in a loan or investment portfolio will set ag lenders and investors apart. Each borrower has their own risk profile and portfolios should be built on a thorough understanding of each one, not an overarching region as a whole. There must be granularity.


Data acclimation integrates the right risk analytics into existing portfolio data. By mobilizing and unlocking insight-rich data, ag finance institutions can not only reduce this uncertainty but actively work to mitigate the associated risks.


The answer is data acclimation:

Data acclimation is the process of geospatially contextualizing company data with third-party physical and material risk data, such as water and climate analytics, for the purpose of better understanding the impact of risks on loans, investments, and customers’ businesses.


This modern approach to data management unlocks new depths of risk discovery and empowers ag lenders and investors to reshape their portfolios by monitoring and mitigating climate and water risks.

With the harvests and parcel valuations of growers at greater risk than ever before, ag finance institutions that do not acclimate their data expose themselves to uncertain returns and higher default rates. Those that utilize data acclimation, on the other hand, will be poised to outmatch their competition.

Water risks and climate change force the name of the game to be granularity, speed, and connectivity. These add up to create a consistent and accurate understanding of risk in agricultural loan and investment portfolios.



What Is Data Acclimation?

By breaking down the aforementioned definition into its component parts, the form and function of data acclimation become clear.


1. “Data acclimation is the process of geospatially contextualizing company data”

Data acclimation is a service that enhances proprietary financial records. By situating first-party data geospatially, data acclimation makes mapping borrowers and customers easier than ever before.


2. More importantly, the geospatial format empowers business by “contextualizing company data with integrated physical and material risk data, such as on water and climate,”

Data acclimation links geospatial data on key climate and water risk indicators to the newly geospatialized company records. In doing so, it produces a data map of parcel-by-parcel portfolio risk.

Consolidating disparate datasets on water rights, soil quality, wildfires, groundwater, and much more, acclimation merges information that was once extremely difficult to access with portfolio data owned by a financial institution – allowing that institution to do more with the data they already have.


3. Ultimately, the process enhances data management “for the purpose of better understanding the impact of risks on loans, investments, and customers’ businesses.”

Water and climate risks can make or break an ag portfolio. 2020 saw $931.6 million in agricultural damages from wildfires across California, Oregon, Washington, and Colorado. Due to lack of water, 1 in 10 acres of cropland in the San Joaquin Valley are projected to discontinue production by 2040. Most concerningly, the two to three years after a period of drought see significant increases in delinquency rates.

Those without a deep understanding of their risk will be blindsided. Those with a deep understanding can build resilience and peace of mind. Data acclimation is the first step along this journey.

Geospatial data management empowers ag lenders and investors to easily identify both the climate and water risks present in a parcel, but also the best strategies to mitigate their impacts. Modern decision support is how sustainability becomes actionable. A holistic understanding of portfolio risk primes businesses to take effective, measurable, and reportable steps towards mitigation.


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The Digital Transformation in Banking Is Good for Agricultural Finance

Almost all the banks in a survey conducted by Forbes Magazine reported that they had some form of digital transformation strategy. As new elements of risk continue to present themselves in agriculture, ag investors can look to the digitization of banking services in a positive light.

Traditional methods of data collection like spreadsheets were once sufficient for the needs of risk analysts. Now, more analysis requires a higher level of granular data that cannot be done in a timely manner that is respective to the volatility of today’s climate. A digital transformation in banking means having a better toolset in the face of mounting risk factors and reporting compliance.

Financial institutions that use digital technology can also reap the added benefits of a stronger relationship with their buyers. It can also make the process of loan decisions smoother by acclimating material risk factors into a geospatial layer. Ultimately, a digital transformation in banking will give financial institutions a better opportunity to assess risk and streamline their loan decision process.

How to Identify and Mitigate Ag Risk Using a Data Management Platform

For finance professionals that deal with a wide range of data to mitigate risk, maintaining an accurate understanding of factors that could impact a harvest remains invaluable. Available solutions to aid analysts in these endeavors exist in the form of fintech with specialized platforms, specifically, a data management platform.

A Data Management Platform is a term that is used to describe a tool that is described by Microsoft as:

“Simply put, a DMP is a platform that helps you collect, organize, and activate data from various sources and put it into a usable form.”

In the agriculture industry, data must go beyond simply being collected. It has to be broken down and facilitate better business operations. DMPs have the functionality of pooling information from multiple sources and producing new insights. Ag lenders can examine first-party data with respect to third-party data (crop history, drought levels, water rights, etc.) brought in by the DMP. Having the right DMP can grant ag lenders a more holistic view of risk with the portfolios they manage.

The Best Enterprise Data Management Today Comes from Data Acclimation

In the past, enterprise data management processes contributed to siloed datasets that hindered the ability of ag finance professionals to perform analyses of risk data sets. These methods also made it time-consuming to just arrive at a better understanding of risk patterns within a parcel of land. Ag lenders can now use modern enterprise data management tools with GIS platforms that utilize data visualization capabilities and create better risk mitigation strategies.

This post highlights data acclimation as the best enterprise data management solution because it:

“…brings financial institutions’ own data to life alongside other datasets. By using a cloud-based data management system, ag finance institutions can maintain their own data securely, while making it easy to share information across the entire organization and with external stakeholders.”

With data acclimation, financial institutions are in a better position to identify material risk within portfolios.

How Data Acclimation Enhances Resilience Planning in Agriculture

Resilience planning is one of the main jobs financial analysts carry out. It requires an accurate analysis of risk factors and the development of strong contingency plans, created to combat any negative impacts that may arise. However, this can be made difficult due to the industry’s proximity to water and other climate risks.

Another challenge is the siloing of data. This takes away valuable time that could be used to actively assess risk scenarios and thus, delays the speed of planning. When done correctly, resilience planning enables ag professionals to confidently navigate the challenges with the risky sector.

With the endless amount of data available and the time-sensitive nature of resilience planning in today’s climate, data acclimation confronts the challenges normally encountered by financial professionals. By integrating data that was once kept separated, identifying trends and patterns of risk becomes easier to extract.

Understanding Wildfire Risk in Agriculture Through Data Management

Wildfires have quickly come to represent a most pressing material risk in the agricultural industry. As areas of California are often victim to wildfires and have a high propensity to water risk, wildfire risks may also be considered water-risk adjacent because of this proximity.

Professionals face the growing need to incorporate wildfire risk data into their loan and investment decisions. By using data management processes like data acclimation, ag finance professionals are able to geospatially view data and review risk statistics. Contextualizing material risk with geospatial data can elevate risk assessment and deliver a more comprehensive image of the resiliency within a portfolio.

Data Management Tools Outcompete the Status Quo

Much of the data essential for informed decision-making in the ag sector remains trapped in isolated datasets and incompatible formats. To use a thematically resonant metaphor, information is siloed. Not only are data on water rights, soil quality, and wildfires often kept separate, the spreadsheets, onion papers, and cross-organization analog tools in US ag can cause confusion, miscommunication, and risky decisions.


Data Acclimation uses data management tools to de-silo the info ag professionals need.


This can be done by integrating third-party water and climate risk data, financial institution-owned portfolio data, and borrower data. Rather than spending time and money to manually compile disparate datasets and process them for comparison, a data acclimation service handles aggregation automatically.

The right data management tools can save time and money by providing up-to-date, holistic context that easily integrates with portfolio records. Once implemented, finance professionals can spend less time fighting their data and more time using it to compete.

New Groundbreaking Trends in Data Management in Banking

With a continuously growing amount of data, finding the best way to navigate through it can be resource taxing. Financial institutions that want to retain a level of competitive advantage should look for new capabilities fintech has to offer data management in banking.

When proprietary data is collected, it lacks the pieces that can convert it into being actionable. Integrating first-party and third-party data maximizes the value of the information and builds a more refined view of assets.

As regulatory bodies continue to look for more standardization and sustainable practices, those who don’t capitalize on a data-centric approach will get left behind.

What Is Data Visualization and Why Is It Crucial to Mitigate Risk in Ag Finance?

The various dimensions of risk all must be considered together. Therefore, they should be displayed together. Data visualizations transform the utility of a dataset by allowing finance professionals to process multiple interacting factors simultaneously. Using location, shape, size, color, etc, a well-designed visualization can translate a complicated mess of varying data fields into a story read effortlessly by the eyes.

Water and climate risk pose both acute and chronic risks to financial portfolios, particularly in agriculture. Rather than painstakingly checking values from each indicator with different parcels, a software-generated data visualization can give a near-instant overview of a parcel’s risk portfolio.

Granular datasets covering an entire ag portfolio contain so much information it can be difficult to make sense of. Visualization makes it accessible, showing risk factors and their potential financial impacts more clearly and more quickly than numerical or textual methods.

Why Ag Finance Needs Map Data Visualization for Risk Mitigation

Geospatial data becomes most accessible when displayed in a geographic medium. Interactive map data visualizations that take advantage of accurate, granular data have the power to turbocharge risk analysis. Previously opaque data can offer clarity, insight, and drive smarter decision-making in the hands of an analyst empowered by a dynamic mapping tool.

Maps derive power from their dynamic layers. Superimposing climate risk data on financial data produces a map of climate-induced financial risk. By comparing parcels through layers such as water rights, wildfires, groundwater, or soil quality, ag finance professionals can identify potential liabilities and corresponding strategies for mitigation.

Moreover, maps are easily digestible and mutually intelligible. Location-based context for data that is easily accessible to loan officers, appraisers, risk professionals, and farmers, makes a map worth a thousand email exchanges.

The Benefits of Interactive Data Visualization In Ag Finance

Reading and sifting through data can be a challenging task, making just trying to find the right data feel like searching for a needle in a haystack— only the haystack continues to grow exponentially by the day. Interactive data visualization aims to remedy this exact problem. What was once otherwise-static info is transformed by visual depictions into clear images of risk that effectively and efficiently communicate granularity.

Interactive data visualizations that are created with granular location-based data make managing a diverse portfolio painless for risk professionals. Farm Credits can use this to mitigate risks in a way that causes minimal disruption to the business, decreasing time being spent in the wrong places.

The Best Data Visualization Tools for Ag Finance Risk Management

Financial institutions have long since been providing valuable information to their stakeholders. Still, legacy practices no longer meet the growing needs of the climate within the modern agricultural industry. Forward-thinking individuals know the power in having the ability to identify patterns succinctly.

  1. Data Un-Siloing and Aggregation
  2. A Geospatial Aspect
  3. Compatibility Features for Financial Institution’s Existing Risk Management Practices

Data visualization tools derive concise information from datasets that were once siloed and provided little value on how to mitigate risk within an existing piece of land. However, by using data visualization tools that have these three features, ag lenders will be better positioned against the competition.

Fintech for Data Collection in Risk Management for Ag Finance

Ag professionals handle copious amounts of data every day all throughout different profiles. This data is crucial to their risk management process as it can provide valuable insights with specific granularity. However, because there is such a large gap between the information that should be easily accessible, gathering the necessary data can be challenging to acquire.

Fintech tools aggregate data so that ag finance analysts can assess existing information housed within their institution alongside climate analytics. That is, by leveraging modern capabilities that use data acclimation, what was once a time-consuming and expensive process can be transformed into one that speeds up the loan process and streamline appraisals.

Improving the way data collection in risk management is done to create new insights within a portfolio may be used to conceptualize ways of mitigating overall risk. Utilizing data acclimation to collect relevant risk data and accessing it in an un-siloed format empowers ag finance institutions to stay nimble and competitive in a changing financial landscape.

Decision Support Fintech Can Save Ag Lenders Time and Money

In agriculture, data is key for making decisions that pertain to risk. Unfortunately most of the time this information is not standardized and kept separate. This circumstance negatively impacts the productivity of financial risk analysis and increases the susceptibility of portfolios. With water and other climate risks continuing to change the ag industry, there is an increased need for decision support tools that can gather and analyze disparate data.

Everyday advancements in technology have allowed professionals across all industries easier access information that was once costly and resource-intensive. Decision support does exactly that— providing aid to key decision-makers. Decision support fintech helps analysts parse the complexity and scale of risk.

A financial institution may have portfolios that consist of hundreds of parcels, making it extremely difficult to effectively manage how risks present themselves in each piece of land. Decision support services continually monitor dynamic changes and risk within portfolios, allowing institutions to dedicate more time and resources towards developing a more holistic picture of risk.

21st Century Executive Reporting Requires the Right Data and Fintech

Capturing a holistic view of agriculture risk situations has been revolutionized over the last few years, with the help of new technologies. Administrative bodies are expanding executive reporting standards, making it clear that companies must deliver actual risk situations to stakeholders. With reporting, the probability of something getting lost in the shuffle is reduced by providing a transparent report of current operations.

For ag finance professionals, this means clearer visibility into climate risks across entire portfolios. Through this understanding, highly-informed loan decisions and parcel valuations can be made. Fintech solutions can help break down big data and help lenders not just standardize the executive reporting process— but mitigate the risks as well.

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