The Key Aspect That GIS Solutions in the Banking Sector Must Have for Agriculture
GIS solutions in the banking sector are an important part of success in modern banking. As the World Bank notes, geospatial technology can be used to “map existing financial access points and assess the distribution of financial services by regions in a more granular way – allowing authorities to identify gaps in existing coverage more clearly and with higher precision.”
But with extreme weather events bringing about new reporting requirements and risk management practices, GIS solutions in the banking sector are becoming increasingly necessary – and more robust than ever.
The key to GIS solutions in the banking sector is granularity. By acclimating financial data to account for climate change risk, ag finance institutions can stay ahead of the curve and work to mitigate the risk of water stress and climate change on their portfolios.
This article will show why risk data must be granular in nature to be effective and how GIS solutions can help ag finance professionals account for risks material to their portfolios.
Risk Data Must Be Granular
Understanding risk from a macro perspective and only a macro perspective isn’t sufficient for today’s ag finance institutions. Only by starting at a granular level and then building up to a full view of portfolio risk can ag lenders and investors fully understand this risk and see parcel-by-parcel mitigation options.
Two nearby parcels of farmland with the same macro risk level – for example, a high risk of drought – may exhibit different risk resilience profiles at a granular level if one has more water rights or access to water resources than the other. Even in that case, the parcel-specific risks may diverge even further if one operation depends on a water-intensive crop and the other does not. Or, perhaps a farming operation utilizes water markets or water banking.
The level of insight to be gained deepens with each risk metric and each level grows more essential for ag finance professionals to understand each day.
By being aware of these differences on a granular level, ag finance professionals can make better decisions about loans and investments and can work with borrowers to mitigate these risks when cost-effective solutions are available.
Why Large-Scale Climate Analytics Are Too Broad
Granular datasets can unlock advanced risk analytics and put existing bank data into context in a way that supports water and climate resilience.
Large-scale climate analytics can tell us that California is in drought and that current drought conditions in the American West have lasted longer than the Dust Bowl – but they can’t specific and actionable insights into hyperlocal issues.
That’s because it’s not just about precipitation levels and weather patterns, but about variability in when, where, and how a farming operation can access and maximize the utility of a given amount of water. These are determined as much by regulations, water rights, and water contracts as they are by macro weather conditions.
Drought may blanket the American West, but it doesn’t impact every parcel equally.
In fact, the opposite is true: water is a hyperlocal issue. Because there are so many variables in ag finance – from water rights and water deliveries per parcel of farmland to local regulations, water markets and water banking, crop type topography, natural resilience, and more – it is no longer sufficient for ag finance professionals to make decisions without relying on granular water data.
Additionally, not all impacts may be reflected in measurements of water scarcity alone. Water quality can be impacted by everything from sea level rise to wildfires. Bloomberg Law reports that the U.S. Geological Survey found “increases in nitrates, arsenic, and uranium during the last drought.” Likewise, “Wildfires scorch watersheds, sending soot and other organic material downstream, possibly contributing to algae blooms and making water more difficult and costly to treat.”
In the age of climate change, banks with access to hyperlocal datasets that acclimate into their own will be better able to identify these risks and protect their bottom line.
How GIS Solutions in the Banking Sector Can Help
GIS solutions in the banking sector can help ag professionals adapt to this new reality, by aggregating multiple types of risk data all in one place. By exploring this data in an intuitive, map-based format, users can zoom in and out of specific parcels of land, run reports on borrowers, or toggle different risk layers on and off to gain more granular insights.
Regional risk data, such as the fact that many farming regions in the U.S. are currently in drought, is not enough for ag professionals to make informed lending and investment decisions. Water and climate data must be parcel-specific in order to meet the needs of today’s financial institutions, and it must be stored using a platform that can incorporate real-time updates and third-party datasets.
GIS Connect can help with this process by providing a cloud-based tool that financial institutions can use to collect and manage their data. Users can integrate third-party datasets using a secure API, and search through that data by parcel, borrower, or farming operation to gain hyperlocal insights, generate per-parcel risk scores, and acclimate their data.
In addition to collaborating with colleagues, users can add notes and attachments in order to share insights with borrowers and other external stakeholders. Together, ag finance professionals and growers alike can work to mitigate water and climate risk, creating a more resilient and efficient agricultural sector.
The Bottom Line
Large-scale climate analysis is important for understanding macro-level climate trends and weather patterns. But regional impacts like drought and water scarcity can affect different parcels of land in different ways. In order to reduce financial risk, ag lenders must incorporate granular datasets into their own data and decision-making processes.
With GIS Connect, ag finance professionals can better understand the impact of climate change on their borrowers, by accounting for factors such as water rights, water deliveries, and other parcel-specific datasets that aren’t accounted for in macro-level analysis. By presenting once-siloed data all in one place, GIS tools save banks time and money and improve their operational efficiency.
AQUAOSO is here to help you understand the current state of water risk in agriculture. Contact the team directly to find out more, or download one of the free white papers or cheat sheets from the Resources section.
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