The global energy crisis of 2022 was not just an energy-sector issue — it became a financial shock with direct implications for markets, consumers, and policy. For investors, banks, and Fintech platforms, the crisis raised urgent questions: how do commodity
shocks ripple into electricity prices, and how can technology help us model and respond to them?
In my recent MBA dissertation, “The Impact of the 2022 Energy Crisis on UK Electricity System Prices: A Commodity Market Analysis”, I set out to explore this exact question. The research is now publicly archived on Zenodo (DOI
link) along with a regression-ready dataset (DOI link), making the data and findings openly available to both academic and industry audiences.
The Commodity-Electricity Link
Using daily data from 2021–2023, I applied multiple regression models to understand how fluctuations in commodities influenced the UK’s electricity system price.
The results confirmed what many energy traders felt in real time: oil and gas prices had significant spillover effects on the UK electricity market, especially at the height of the 2022 crisis. Gas prices, in particular, exhibited a strong positive correlation
with electricity system prices, underlining the UK’s dependence on gas for power generation.
Why This Matters for Fintech
Fintech thrives on building tools that reduce friction, manage risk, and anticipate shocks. Electricity prices may seem far removed from payments or retail banking, but in practice:
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Risk Models and Hedging: Commodity volatility directly affects energy suppliers, utilities, and corporates with large energy exposures. Fintech risk engines can use regression-ready datasets like this one to simulate price movements and
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Sustainable Finance: With ESG-linked financing on the rise, investors need robust methods to evaluate how crises impact green vs. traditional energy portfolios. This requires transparent, replicable models.
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Consumer Platforms: Price spikes filter down to consumers through energy bills. Smart budgeting and personal finance tools can integrate forecasts to help households anticipate cost shocks — a space ripe for Fintech innovation.
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Operational Resilience: Regulators like the UK’s FCA and EU (through DORA) are pushing financial institutions to stress-test resilience. Datasets linking commodity and electricity shocks provide valuable input into these exercises.
Open Science as an Enabler
One of the key contributions of this research is not just the findings, but the decision to make the dataset openly available. Fintech is a data-hungry industry, and transparency matters:
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Researchers can replicate and extend the models.
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Fintech startups can test AI/ML forecasting approaches on a real-world energy dataset.
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Policy professionals can assess the financial-system implications of commodity crises.
This open-data approach aligns with a broader Fintech trend: the blending of open finance and open science to create ecosystems where innovation thrives.
Lessons for the Future
Three key insights emerge for the Fintech and finance community:
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Interconnectedness is the new norm. Energy prices can no longer be treated as “external” to financial markets. Commodities, FX, and electricity prices are tightly coupled.
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Data is infrastructure. Having clean, regression-ready data is as important as having trading platforms or risk systems. Without structured datasets, even the best AI models fail
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Transparency builds trust. By sharing not just conclusions but also the underlying data, researchers and practitioners enable accountability and accelerate innovation.
From Crisis to Innovation
The 2022 energy crisis underscored the vulnerabilities of energy markets, but it also highlighted opportunities for Fintech. Platforms that can integrate cross-market data — from commodities to carbon, from FX to electricity — will be better positioned to
serve customers and manage systemic risks.
By contributing open, citable research and datasets, I hope to bridge the gap between academic analysis and industry application. For Fintech professionals, the challenge is clear: use these insights not only to react to crises but to build systems resilient
enough to withstand the next one.
Full paper (DOI): https://zenodo.org/records/17046850
Replication dataset (DOI): https://zenodo.org/records/17047146