Model Build

Our dedicated modelling professionals work collaboratively with clients to scope, design, build, test and hand over robust, user-friendly financial modelling solutions. Leveraging our global network, we bring together the right sector insight and technical skills to solve problems.

Our financial models support a wide range of decisions across the business agenda:

Financial planning and analysis
Business case
Transactions, both buy-side and sell-side
Raising of debt and equity
Restructuring and business optimisation
Business intelligence, management, bank and regulatory reporting

We can develop solutions in Excel, VBA and other technologies such as SQL, Alteryx and Power BI.

Model Review

Our independent model review service gives clients and their stakeholders confidence that the models and forecasts on which they are basing investment or other strategic decisions are robust and free from error.

Our review approach can be tailored to clients’ specific requirements:

A full scope review that provides an opinion if the model is fit-for-purpose
A more tailored limited scope review where we provide our findings graded by severity
A review by a parallel build of a “black-box” system to confirm if it works as expected

Data Analytics

Increasingly businesses understand the value inherent in the data they hold and the potential it has to support their strategic and operational decision-making.

Our unique offering combines data science skills with a team with real-world commercial experience, so we understand the bigger picture and the data.

Descriptive Analytics

Descriptive analytics is the interpretation of historical data to better understand what has driven changes in a business. We can consolidate large and complex data sets, combining business data and other sources, to provide an intuitive way to explore and understand the drivers of value and risk in a business.

We work with sell-side and buy-side teams across the deal lifecycle to maximise value and minimise risk.

Prescriptive Analytics

We develop machine learning-enabled predictive analytics solutions to accurately forecast what will happen based on prior experience. This can be applied across an organisation to optimise decisions and reduce risk in judgemental areas:

Minimise churn by identifying customers who may leave and proactively engaging with them
Reduce credit risk by understanding the key drivers of default to predict individual customer risk
Design cost-effective customer contact strategies by targeting through preferred channels
Understand customer behaviour “clusters”
Automatically identify unusual transactions or behavior