New Groundbreaking Trends In Data Management In Banking

With each passing year, technology introduces new methods of revolutionizing the way society handles data. But with a seemingly immeasurable amount of data being collected, it can be hard for financial professionals to make the best use of the information they already collect. 

Forward-thinking financial institutions are looking to fintech to help make data management in banking more practical and efficient.

Cloud-based Data Management in Banking

An article from Forbes details different trends in data management that businesses can utilize in streamlining their risk management.

One of the seven trends is the expansion of cloud computing services. Storing data in the cloud frees up time and allows for the allocation of other valuable resources. It also makes the process of sharing files and general collaboration painless, given that anyone with some form of internet connection can readily access the information. The author specifically mentions,

“Cloud analytics services provide data models and advanced analytics tools that businesses would otherwise have to build themselves. Now organizations only have to pay for what they use… Data management is far from static, and in the new decade, every data-driven organization must find ways to collect, analyze and make business sense of their ever-growing data assets… the evolution toward public cloud-native services makes data analysis accessible, affordable and nontechnical.”

On the financial side of things, Yahoo! reports that the market for predictive analytics will increase to $28 billion dollars by 2026, up from this year’s figure of $10.5 billion.

The Financial Stability Oversight Council Report

In October of 2021, the U.S. Financial Stability Oversight Council (FSOC), released a report focusing on the financial implications and risks posed to the economy as a result of climate change. This council’s responsibilities include “monitoring financial regulatory proposals and developments, and making recommendations…and identifying gaps in regulation that could pose risks to U.S. financial stability.”

In the report, FSOC highlights the need for more robust practices within data management in banking. Recognizing that climate change is a growing threat to the stability of the nation’s economy, the document discusses ways certain industries are challenged by and help contribute to associated threats in the climate.

On the subject of combating these challenges, the council calls for financial professionals to start utilizing more robust practices:

“Investors, market participants, and regulators need better data and information… to assess climate-related financial risks and their potential effects on the financial system…This information will be used to help gauge risks to individual institutions and markets and to financial stability.”

The USDA credited $136.1 billion directly to American farmers in 2019. Industries that rely on agriculture amounted to 5.6% of the U.S’ GPD in 2019. When the financial security of the nation’s economy as a whole is threatened, that, of course, includes the ag industry.

FSOC shares, 10% of Greenhouse Gas emissions, or GHG, are directly attributed to being a result of the agriculture industry. Moreover, the U.S has committed to reducing GHG emissions “50-52 percent from 2005 levels and set a goal of a net-zero emissions economy by 2050.”

This means that as new legislative interventions continue cracking down on climate-related risks— “meeting these targets will require significant changes across the economy… Sectors of the economy that are GHG-intensive, which include the energy, transportation, manufacturing, and agricultural sectors, likely need to undergo significant structural changes.”

Regulatory entities continue to expand their pursuits of sustainable practices and ag financers that don’t adopt a data-centric strategy will get left behind.

Data Analysis and Data Management in Banking

Proprietary collected data typically does not have the level of depth for it to be actionable. Syncing third-party info helps maximize the value of collected data and builds a more refined picture of assets.

However, as it stands, information is either too scattered, lacking in profoundness, or does not have a method of standardization— and in most cases, it falls into all those categories.

When data is presented in this manner, it is effectively rendered useless.

While the dangers of climate change become more uncertain, ag finance professionals will need more advanced ways of identifying, monitoring, understanding, and mitigating these risks.

Focusing solely on the bigger picture discounts the uniqueness a single parcel of land can contain. Loan portfolios can be made up of many individual parcels, each with its regulations, practices, and threats. All these facets contribute to building a distinct level of granularity that becomes a factor in the risk profile of the overall portfolio.

The right data management fintech provides context to relevant information that was previously kept separate and analyzes them together. With these advanced analytics, risks are more identifiable and can be further analyzed in real-time for additional visibility.

When all these pieces of information are acclimated into one space, the info can be leveraged by professionals to bolster risk management and build resilience plans. Data management in banking enables ag lenders to identify and report on exactly what puts their portfolios at risk.

The Bottom Line

With administrative officials keeping the best interest of the nation’s economy in mind and asserting their mission for sustainable change, ag finance businesses will have to understand that there is an overlap in financial and climate risk.

GIS data management fintech saves investors time and money by supercharging the foundation for their risk management in banking.

Powered by securely acclimating first-party info with third-party, GIS Connect is a fintech data visualization tool that geospatially delivers proprietary data in an accessible way. By delivering datasets through secure APIs, aggregated data, and a bird’s eye view— research portfolios on a map and easily build financial resilience through granular risk analysis.

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