Smart infrastructure financing: Why data could be the answer
The way we are financing infrastructure is stuck in the 20th century. Peter Adriaens, a professor of finance in the Department of Civil and Environmental Engineering and director of the Center for Smart Infrastructure Finance at the University of Michigan, wants to change that. With $1 million in financial support from blockchain company Ripple, he is exploring new financial models to develop a sustainable solution to the problem of infrastructure funding.
What is the goal of the Center for Smart Infrastructure Finance?
Adriaens: The way infrastructure has been financed has fundamentally not changed for decades. Public funding is no longer sufficient to finance upgrades and repairs of the nation’s infrastructure. The question, then, is: Are there different ways we can finance infrastructure systems?
The answer is yes. Infrastructure of the future is defined differently from how we used to think of these systems. They are no longer just real assets (physical infrastructure). The information the built asset generates is starting to become more valuable than the built asset itself.
Investing in digital assets follows a very different model from how we have been financing real assets, and yet there is almost no research supporting this. The goal of the Center is to fill this gap by advancing new business and investment models for efficient capital deployment towards smart and resilient infrastructure systems. These new efficient financing models have the potential to (1) reduce the infrastructure finance gap and (2) democratize access to quality infrastructure across rich and poor because the value is extracted in the data markets.
What kinds of data come out of infrastructure systems?
Adriaens: Smart infrastructure systems incorporate sensors that produce highly granular location-specific data with information on their performance and operations. These performance data help value the systems in light of their use, their deterioration and risk, and their contribution to economic value creation. That value is translated into pricing models and incorporated in a token (cryptocurrency) that can be transacted on a blockchain.
Our application use cases include intelligent transportation systems, smart watersheds, transactive energy microgrids, and waste resource recovery facilities. For example, blockchain technologies are starting to power energy microgrids using efficiency data collected from solar panels coupled to energy spot prices on the NASDAQ exchange. Smart stormwater controls using water quantity and quality data from agricultural or urban runoff coupled to weather forecasts can manage drainage and discharge in receiving waters, thus reducing the need for expensive grey infrastructure systems. Transportation infrastructure stress and load data can be fused with high speed video framing of traffic to inform road maintenance costs and leading economic indicators, or help to structure risk transfer contracts. Wearable sensors and energy efficiency data have the capacity to scale grid-adaptive buildings and inform design for the comfort of its inhabitants or users. Drone imaging of deterioration and destruction of infrastructure systems informs capital reserves for insurance and reinsurance companies.
Finance is becoming an extension of the engineering skillset, particularly in the era of financial technology and decision algorithms.Peter Adriaens, Professor of Civil and Environmental Engineering
How will the funds be used?
Adriaens: The funds will help to kickstart the new U-M FinTech Collaboratory, a partnership between the Center for Smart Infrastructure Finance in the Department of Civil and Environmental Engineering; the Center on Finance, Law and Policy in the Ford School of Public Policy; and the FinTech Initiative at the Ross School of Business. We will build multi-disciplinary fintech curricula, as well as engineering and business use cases for cryptocurrencies in new application domains such as smart cities.
As part of the partnership, CEE will host a node in the Ripple XRP (the Ripple cryptocurrency) network that now connects 20 global universities that have received support with their Global Payments network. This CEE node will be used for research purposes and allows our students and researchers to become part of RippleNet, the network that validates blockchain transactions. Ripple is making this XRP Ledger (cryptocurrency account) available for student learning and research.
This is very important for our students. There is a lot of demand from them to learn about blockchains, but we only have a handful of courses in blockchain technology and cryptocurrency. Students have formed a blockchain/crypto club of over 500 engineering and business students and have started to offer training modules to educate their peers to address the needs. This funding will help to unlock new markets, and build a cross-disciplinary educated student pipeline.
Why combine finance with civil and environmental engineering?
Adriaens: Finance is becoming an extension of the engineering skillset, particularly in the era of financial technology and decision algorithms. Data from real asset IoT (internet of things) can be translated into financial IoT metrics. They are essentially design parameters. There’s a lot of benefit to bringing in financing risk and return frameworks to help design smart (data-driven) infrastructure systems across asset classes and uses. For example, social infrastructure (e.g. roads and bridges, schools) has different constraints from regulated (e.g. energy and water utilities, telecoms) or demand-driven (e.g. mobility, smart water and renewable energy) systems. There are cybersecurity and financial performance issues and regulatory constraints that engineers don’t traditionally think about while designing smart systems, but finance professionals do. As a result, designs are not only optimized for functionality, but also for information value and investment grade.
The Department of Civil and Environmental Engineering at the University of Michigan has more smart infrastructure pilot systems deployed under real world conditions than any other school in the U.S. We have sensors in operational water, building, energy and transportation infrastructures. U-M can leverage a tremendous amount of innate capacity to generate data from these systems to inform financial models.
Civil and environmental engineers will need to be trained in digital assets, information valuation and project finance models of the future. We’re already seeing financial services, banking and investment becoming more important employers of engineering and data science talent.
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Department of Civil and Environmental Engineering
GG Brown 2105E
Professor of Civil and Environmental Engineering