Quantitative Due Diligence on an Energy Analytics Platform
Independent technical DD that de-risked a strategic platform investment decision.
An institutional investor was weighing a strategic investment in a third-party energy risk and analytics platform — and needed an independent, technically credible view of what it was actually buying. We ran a comprehensive quantitative due diligence engagement and delivered a findings-and-risk report that put the decision on solid ground.
The Challenge
The platform in question offered cloud-based analytics for energy and commodity markets — price simulation, portfolio and risk management, and valuation of thermal assets, storage, renewables, and structured contracts such as PPAs — serving utilities, retail energy providers, merchant asset owners, and commodity traders. Before committing capital, the investor needed to understand the technical reality behind it, not the sales narrative. Marketing materials and high-level demos rarely reveal how market data is sourced and processed, how the simulation and valuation models are designed, where coverage is thin, or how heavily the platform leans on third-party dependencies.
The investor had the commercial and financial picture but lacked the in-house quantitative and energy-markets expertise to interrogate the platform itself. Getting that assessment wrong — in either direction — carried real cost.
The Solution
We ran a comprehensive quantitative due diligence engagement, examining the platform across the dimensions that actually drive its value and its risk.
1. Market data & methodology
We evaluated how the platform sourced, processed, and validated its market data — forward and spot prices, demand, and renewable generation — and scrutinised the methodology behind its price-simulation and valuation outputs to understand what was robust and where modelling assumptions were doing heavy lifting.
2. Model design & coverage
We reviewed the design of the platform's simulation, risk, and asset-valuation models — including their treatment of sub-hourly granularity, renewables and storage economics, and structured transactions — and assessed coverage across markets and asset classes: where it was strong, where it was thin, and how well it would hold up against the investor's intended use.
3. Dependencies & architecture
We mapped the platform's third-party data and vendor dependencies and its cloud technical architecture to surface concentration risks, lock-in, scalability limits, and the engineering realities behind the product.
Scope of assessment
Market-data sourcing and methodology, simulation and valuation model design, coverage and limitations across markets and asset classes, third-party data and vendor dependencies, and cloud technical architecture — assessed independently and reported with a clear-eyed view of strengths, weaknesses, and risks.
The Results
We delivered an independent due diligence report with detailed findings, a structured risk assessment, and strategic recommendations. It gave the investor a clear, technically grounded basis for its decision — replacing the vendor's narrative with an objective view of the platform's modelling, data, and architectural strengths, weaknesses, and dependencies, and de-risking a significant strategic commitment.