Acquiring an energy business - challenges from a financial modelling perspective

Snowy Hydro acquisition of Lumo Energy
It is common knowledge to experts in the financial modelling industry that forecasting assumptions are critical to any valuation model. With energy being one of the most volatile markets in the world, it is necessary to capture variance and mitigation in your modelling.

There are significant regulatory risks to consider when building a financial model for an energy company – some of which include carbon pricing and regulatory outcomes on tariffs. These and other challenges are what we as financial modelling analysts have to consider when large utilities acquire new assets, such as Snowy Hydro Limited's acquisition of Lumo Energy.  

 

 

Snowy Hydro’s acquisition of Lumo Energy and the role of financial modelling

Over the years, Snowy Hydro has evolved from a power generator to an integrated energy business – now providing products for wholesale customers and delivering energy to homes and businesses. Diversification has been an integral part of this process and a key to its success has been the purchase of electricity and gas retailers - Red Energy and more recently, Lumo Energy. With a project of this size and proportion, Snowy Hydro sought support from Corality and we were ready for the challenge.

The fourth largest player in the Australian National Electricity Market

The purchase of Lumo Energy provided Snowy Hydro with 163MW of peaking generation, the company “Direct Connect” and Lumo’s electricity and gas retailing business. With major players Origin, AGL and Energy Australia in the National Electricity Market, a significant deal was in order to be able to compete at this level. This strategic move propelled Snowy Hydro to become the fourth largest competitor in the Australian energy market, giving it greater scale than it could have achieved by growing organically.

 

Financial modelling valuations and scenario analysis supports investment decision

As financial modelling consultants, we were engaged to write the financial model to quantify the value of Lumo Energy as part of a new Snowy Hydro. Following a week of thorough discussions focusing on Snowy Hydro’s analysis, our consulting team built an initial model for the indicative bid.

The next stage of due diligence involved the review of forecasts, budgets, expert reports and other financial documents. What progressed was a more comprehensive model for the final bid, which was then updated and revised for financial close. Having a timely, robust and transparent financial model allowed Snowy Hydro to assess the impact to its bottom line from the acquisition under various circumstances and become successful in its bid for Lumo Energy.

 

The advantages of best practice financial modelling and reducing model risk

We were very pleased with the outcome. It reinforced SMART, our best practice financial modelling methodology and how using a standardised approach can be the difference between a successful investment and a lost opportunity. Thinking about the end user, incorporating powerful analysis and focusing on consistency are some of the key drivers in ensuring your decision makers will be able to use a financial model to its full potential.

 

The new Snowy Hydro Limited – history and services

Founded in 1949 and headquartered in Cooma, New South Wales, Snowy Hydro Limited is an Australian electricity generation company that owns, manages, and maintains nine hydro-electric power stations, sixteen large dams, and two gas-fired power stations located throughout the Kosciuszko National Park in New South Wales and the state of Victoria. Services now include everything from generation, retailing and bulk water management from their portfolio of renewable, hydro, and gas fired generating plants, to cloud seeding, modernisation projects, and more.

 

Corality Training Academy - SMART Campus

Visit our website to take advantage of various training courses and free resources to assist you in reducing spreadsheet risk and efficiently building your models with confidence.

Some of our related training courses for this topic include:

 
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Australian-born, and a PhD in Mathematics, John’s expertise is in financial modelling and analytics, with a specific focus on energy and infrastructure. His models, built to value assets, inform decisions and provide comfort to debt and equity providers, combined with his deep mathematical skills, capture inherent industry economics and embedded optionality.

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