Fintech companies operate in a world of numbers and sales metrics, which can make real-time weather conditions seem irrelevant. However, anything that influences business operations and revenue is critical intelligence for business leaders. Understanding the weather’s role in economic trends enables fintech companies to improve operational efficiency, accurately forecast sales, and mitigate risks posed by extreme weather events and climate change. These are among the most compelling reasons to incorporate a weather API into your management practices.
Climate Risk Management
A recent article in Energy Economics outlines the increasingly crucial role of fintech businesses in building resilience throughout the energy industry. Fintech businesses act as a stabilizer, backing critical projects to diversify energy holdings. By investing in certain projects while withdrawing funds from others, these companies advance energy resilience.
Because fintech companies gatekeep access to capital, they can assess the potential risk-versus-reward of a startup based on climate change assessments. This prevents wasted resources and directs money to projects that can make a true difference. For example, fintech companies have played a pivotal role in helping the disadvantaged secure capital for local initiatives, which include infrastructure investments that will protect communities from flooding or hurricanes.
Fintech can also help banks and insurance companies accurately price their policies based on potential climate risks. The insurance world has already been forced to adjust premiums to reflect increased flooding risk, but other dangers may have flown under the radar, such as sinkholes caused by aquifer depletion. Through high-quality data, fintech companies can better identify potential risks and reduce insurance losses.
Agricultural Commodities
Agriculture is one of the industries most vulnerable to both short-term weather variations and long-term climate shifts. One bad season could spell disaster for a small farming operation, while drought can completely shift the prices for common goods like hay or corn.
Fintech companies can use weather projections to analyze the potential loan performance for a given location, preventing serious losses while shaping which commodities reach the market. For example, a savvy fintech company can back loans for certain operational decisions that are projected to perform well in the next season. Not only can this improve loan performance, but it can also play a vital role in protecting the local economy and environment by discouraging poor planting decisions.
Assessing Sustainability Initiatives
“Greenwashing” has been a problem in numerous industries. This is the practice of claiming that a business is supporting the environment through sustainability initiatives while actively causing more harm. For example, a company may promise to plant a certain number of trees per product sold, but it plants non-native species that die and need to be replaced.
Real-time weather data holds businesses accountable for these claims and can reveal deceptive business practices. If a company advertises that it uses recaptured rainwater for its operations, but the region has not had sufficient rainfall in the past three months, the fintech company can investigate and find that its client is actually having water shipped in from another region.
Through this weather data, fintech companies can force transparency in sustainability initiatives while directing capital toward more beneficial projects, like green bonds or renewable energy.
Operational Resilience
Operational resilience has become an increasingly significant aspect of the global economy as climate shifts make old business models obsolete. The modern economy requires diversified, multi-sourced products and agile operations that can quickly adjust if conditions deteriorate in one location.
Weather and climate data can identify potential risks in different areas, helping fintech companies workshop diversification options and avoid dangerous investments. This data can also reveal supply chain bottlenecks that may cascade into serious issues, such as if a hurricane hits a port or wildfires destroy a warehouse. Through this information, fintech companies can support resilient and sustainable business models that prevent unacceptable revenue losses.
Predictive Analytics
Weather plays a massive role in retail trends, which can only be revealed through high-quality weather data. For example, winter drives high demand for certain products, such as at-home entertainment, while lowering demand for in-person experiences like movies or sporting events. Understanding this connection helps fintech companies forecast sales throughout the year and prepare for sales losses before they hit.
Conclusion
Fintech companies seeking to improve their profit margins and reduce uncertainty should explore Visual Crossing’s API tools, which provide access to a wealth of weather and climate data that is easily integrated into management software and dashboards.
From real-time weather conditions to historical data, the API provides clean, standardized data for any location on the globe from high-quality sources such as the National Weather Service.
Peyman Khosravani is a global blockchain and digital transformation expert with a passion for marketing, futuristic ideas, analytics insights, startup businesses, and effective communications. He has extensive experience in blockchain and DeFi projects and is committed to using technology to bring justice and fairness to society and promote freedom. Peyman has worked with international organizations to improve digital transformation strategies and data-gathering strategies that help identify customer touchpoints and sources of data that tell the story of what is happening. With his expertise in blockchain, digital transformation, marketing, analytics insights, startup businesses, and effective communications, Peyman is dedicated to helping businesses succeed in the digital age. He believes that technology can be used as a tool for positive change in the world.
