When making financial decisions, it’s important to see the big picture, whether it’s from drones, satellites, or AI-powered sensors.
The emerging field of spatial finance is using AI insights from remote sensors and aerial imagery to help banks, insurers, investment firms, and businesses analyze risks and opportunities to enable new services and products. , helps measure the environmental impact of its holdings and assess post-crisis damage. .
Spatial finance applications include asset monitoring, energy efficiency modeling, emissions and pollution tracking, illegal mining and deforestation detection, and natural disaster risk analysis. NVIDIA AI software and hardware help industries combine business and geospatial data to accelerate these applications.
A better understanding of the environmental and social risks associated with investments will enable the financial sector to choose to prioritize risks that are more likely to support sustainable development. This is a framework known as Environmental, Social and Governance (ESG).
There is a growing focus on sustainable investing. An analysis by Bloomberg Intelligence estimates that by 2025, more than a third of his total assets under management worldwide will be in his ESG assets. And a European Union Space Agency report predicts that the insurance and financial industry will: Over the next decade, he will become the largest consumer of earth observation data and services, with total revenues exceeding $1 billion by 2031.
Several members of NVIDIA Inception, a global program that supports cutting-edge startups, are using GPUs to track water pollution near factories, quantify the economic risk of wildfires, assess post-storm damage, and more. We are using accelerated AI applications to drive these efforts.
Powerful computing for big data
GPU-accelerated AI and data science can quickly extract insights from complex unstructured data, enabling banks and enterprises to enable real-time streaming and analytics of data captured from satellites, drones, antennas and edge sensors. You can set the.
By monitoring aerial imagery freely available from public space agencies, or at higher granularity from private companies, analysts can determine how much water is being used over time from reservoirs, construction Get a clear picture of how many trees are being cut down for How many homes were damaged by the project or by the tornado?
This capability helps audit investments by verifying the accuracy of written records such as government-mandated disclosures, environmental impact reports, and even insurance claims.
For example, investors may track the supply chain of a company that reports that it has achieved net zero on its production line, and that company actually relies on overseas plants that emit coal ash that can be seen on satellite imagery. you may discover that there is Alternatively, sensors that analyze heat emissions from buildings could help identify low-emission businesses for tax credits.
NVIDIA’s edge computing solutions, including the NVIDIA Jetson platform for autonomous machines and other embedded applications, are powering numerous AI initiatives in spatial finance.
In addition to using NVIDIA hardware to accelerate applications, developers are adopting software such as the NVIDIA DeepStream software development kit for streaming analytics, part of the NVIDIA Metropolis platform for vision AI. . It also uses the NVIDIA Omniverse platform to build and operate metaverse applications for detailed 3D visualization of geospatial data.
Property Insurance — From Assessing Risk to Expediting Claims
NVIDIA Inception members are developing GPU-accelerated applications that turn geospatial data into insights for insurance companies, reducing the number of costly site visits required to monitor the status of insured properties.
Luxembourg-based RSS-Hydro uses on-premises and cloud GPU computing to train FloodSENS, a machine learning app that maps flood impacts from satellite imagery. The company also uses NVIDIA Omniverse to animate his FloodSENS in 3D to help the team more effectively communicate flood risk and inform emergency resource allocation plans.
Toronto-based Ecopia AI uses a deep learning-based mapping system to mine geospatial data to help create next-generation digital maps with highly segmented buildings, roads, forests, and more. These maps will power a variety of applications across the public and private sectors, such as government climate resilience efforts and insurance risk assessments. Ecopia uses NVIDIA GPUs to develop AI models.
Based in the San Francisco Bay Area, CrowdAI accelerates the insurance claims process by using deep learning tools to automatically analyze aerial imagery and video to detect assets damaged or destroyed in natural disasters. . The company uses his NVIDIA GPUs for both training and inference.
Anticipate business risks and opportunities
Inception startups also use geospatial data to help government groups and banks quantify investment risks and opportunities. For example, predicting crop yields, detecting industrial pollution, and measuring property land and water usage.
Switzerland-based Pictera supports sustainable finance with its geospatial MLOps platform that enables banks, insurers and financial consultancies to analyze ESG indicators. The company’s AI-powered insights help the financial industry make investment decisions, model risk, and rapidly quantify vulnerabilities and opportunities in investment portfolios. The company uses NVIDIA Tensor Core GPUs and the NVIDIA CUDA Toolkit to develop AI models and process raw data from satellites, drones and aerial imagery.
London-based Satellite Vu is a start-up applying satellite technology to address global challenges, using data from thermal imaging cameras to enable near real-time monitoring of the temperature of any building on Earth. will be These thermal images provide customers with insights into economic activity, building energy efficiency, urban heat island effects, and more.
And Houston-based Sourcenergy uses geospatial data to power its energy supply chain intelligence platform, which can aid market research in the financial services industry. Developed using NVIDIA A100 GPUs, the company’s AI tools will allow investors to create their own real-time models of energy companies’ well inventories and project costs, which companies will share in their quarterly earnings reports. You can gain insight even before.
Learn more about NVIDIA’s efforts here. financial operations, Read more about geospatial AI in investment management Chapter 10 of this handbook.
