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Anchors and Catalysts:  

Big Data's Impact on Green Investment Strategies 

· investment,Finance,big data

Last December, I participated in the Global Solutions Summit in Little Rock, AR, focused on 'replumbing financial conduits' for low carbon economies. The summit brought together the Global CleanTech Cluster Association (GCCA), the P80 Foundation, and the Club of Madrid. The gathering of this trifecta of actors represent the technology, finance, and policy dimensions of green growth .

Just last week, the GCCA was represented at the UN Multi-stakeholder Forum on Science, Technology and Innovation for the SDGs in New York. Our representation was a follow up from the December Summit. Again, financial innovation mechanisms were highlighted as being key to scaling low carbon transitioning.

The need for financial innovation is the proverbial canary in the coal mine towards implementing large scale deployment and effective deal sourcing platforms for sustainability

These summits provided a stage to present our work of the past three years on the design of Multi-Asset Renewal Funds (MARF) to transition the country of Finland towards a low carbon economy. The program - a collaboration between Peter Adriaens at the Ross School of Business and Antti Tahvanainen at the Research Institute for the Finnish Economy - was sponsored by the Finnish Fund for Innovation, under auspices of the Ministry of Economic Affairs and Employment.

The objective of the Finnish project (now replicated in Switzerland, Taiwan, Canada and the Great Lakes Region) was to develop, design and validate new financial conduits that would be able to 'mainstream' investment in the green economy at appropriate risk and return specifications. Financial technology proved to be pivotal to achieve this goal.

Digital hubs and big data can scale mainstream investment opportunities in green transitioning and economic growth.

The key actors in the Global Solutions Summit

The GCCA is a Swiss Foundation registered in Zurich. Since 2011, its aim is to build out a digital 'hub and spokes' model connecting 55 economic development clusters in 30 countries. Representing over 10,000 companies across the business cycle - from startups to large public enterprises - the GCCA is building deployment hubs (D-Hub) to connect the needs of large public and private companies with a global digital deal sourcing platform.

The most advanced of these is the Nordic Innovation Accelerator (NIA), a startup located in Lahti, Finland. Not surprisingly, Lahti has been the location of the largest Nordic CleanTech meeting for six years running, the brainchild of Nina Harjula, who is also CEO of NIA.

The origins of the P80 began with the inspiration of HRH Prince Charles, who believed that the world's largest pension and sovereign wealth funds could be encouraged to increase the level of their investments which could benefit the climate and/or sustainable development. Examples of funds include the National Pension Service of Korea, the world's third largest pension fund, and Khazanah Nasional, the investment holding arm of the Government of Malaysia.

The Club de Madrid is the world´s largest, independent group of democratic, political leaders, committed to addressing the challenges of democratic transition and consolidation there where they can make a difference.   Counting Presidents Clinton and Gorbachev, Prime Minister Juppe and 110 others among its members, the Club de Madrid has been committed to advancing sustainable development goals globally.

What is the role for digital hubs and big data to connect these actors?

The Global Solutions Summit focused on new financial conduits and products to attract mainstream investors in the sustainable investment space. The argument is that whereas concessional (below market rate) loans and granting programs are the bread and butter for developmental finance to date, they do not achieve the scale, diversification and risk:return profile sought by pension funds, wealth management, and sovereign wealth funds.

FinTech companies such as Corymbus Asset Management, CrowdValley, NIA, and others are extremely well-placed to capitalize on big data and meet the financing needs of tomorrow. Algorithmic fund design companies argue that the future of funds is defined by quantitative 'deep learning tools', not financial fundamentals. This represents a shift of how financing is done.

A key bottleneck is the need for efficient digital solutions for global deal sourcing, due diligence, asset allocation strategies, and customized fund design.

Take Corymbus, for example...

The company is deploying artifical intelligence (AI) - driven enterprise software platforms to crawl public data and capture information that is algorithmically analyzed to derive predictive risk indicators.  Applicable to startups, SMEs and corporate LOBs, this information is further processed to arrive at an asset allocation strategy.  Whether debt financing, private equity, or mixed investment models, resulting fund structures are hyper-customizable per client objectives.  

Asset allocation and fund design via digital platforms without needing access to business plans, private company financials, and investment round specifics.

Central to the investment strategy is a conceptual and quantitative understanding of emerging industry cluster structures. Big data combined with network theory concepts allow for defining anchor and catalytic industry segments, by industry sector and geographic region.

  1. Anchor industry segments define the structural underpinnings - assets that are leveraged for growth
  2. Catalytic industry segments define value-added technologies and services - assets that drive growth

This approach has been applied to companies in a wide range of low carbon industries, such as smart grid, smart mobility, green chemistry and smart farming. This has uncovered that the industry ecosystems driving green growth are cross-sectoral, and connect communications, software and data processing companies with those delivering electrical equipment, electronics and utilities. This is exemplified for smart grid in the figure.

Sourcing and analysis of companies in anchor and catalytic segments using our proprietary public data algorithmics then map out the investment grade of a deal, in terms of market, industry and management strengths, based on key risk indicators. Much like a credit rating, but underpinned by non-financial-public-data.

For more information on the approach, see our book on 'Financial Technology for Industrial Renewal', or contact [email protected]

Peter Adriaens, PhD. is CEO of Corymbus Asset Management, and Board Member of the Global CleanTech Cluster Association. He leads the Program on Financial Technology for Sustainability (ProFiTS) at the University of Michigan, a collaboration between the Engineering, Law and Business Schools.

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