The new regulatory framework

The Homes and Communities Agency (HCA), the UK regulator of social housing introduced new regulations that took effect on 1 April 2015. Providers of social housing will now be required to maintain a register of assets and liabilities and to subject their business plans to rigorous stress testing.

One of the two main areas of the regulatory framework affected was the Governance and Financial Viability Standard. The change to this standard represents a significant shift in focus towards a more risk-management approach for housing associations. The new risk based approach aims to ensure that regulated providers (RPs) do not place social housing assets or their own financial viability at risk. This could occur if, for example, lenders enforced their security following a covenant breach or insolvency, or if a regulated provider sells social housing assets to make good an unplanned cash shortfall.

The regulator expects boards to promote a managed risk approach in order to avoid uncontrolled losses. Rather than specifying how providers should comply with the regulations, it is up to RPs to carry out their own assessment of their vulnerabilities.

How to deal with the new framework

You may have a financial model already – if so, you will need to examine it to see if it meets the needs of the new regulations. Below is a summary of the steps for building a new model if you don’t have a suitable forecasting tool at present. This can also serve as a prompt to see whether your existing model is capable of the necessary analysis. Numeritas is offering a free Model Diagnostic Report to housing associations who want to know if their current model is capable of fulfilling the requirements.

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Steps to design a new forecasting model

1. Identify the key drivers of cash movements in your organisation. This will include both quantum and timing of all revenues, costs, funding and debt service

2. Identify factors that could impact the drivers: these include macroeconomic factors, legislation, market and internal factors. Don’t forget to consider the timing of cash payments, not just their quantum.

3. Quantify the possible impact resulting from each of the risk factors – there maybe multiple impacts – for example increased interest rates would increase any unhedged debt service costs, but could also affect property prices and demand for rented accommodation.

4. Financial modelling – use a professional financial modeller to design and build a model capable of processing all the variables to produce forecasts of income statement, balance sheet and cash flow, plus all the covenants of all debt facilities. This is the very minimum output you will need. The model also needs to incorporate the latest balance sheet position as the start point for its forecast. You may also wish to include a number of periods of history for comparison. It is important to use a professional modeller; few accountants or analysts will have received adequate training to enable them to build a suitable model.

5. Multi-variant analysis – The HCA requires RPs to carry out multivariate analysis. This intimidating term means testing the impact of changing more than one assumption. The distinction here is between sensitivities (changing one assumption at a time) and scenarios (testing the impact of changes to several assumptions that could be expected in a given scenario – for example a house price crash). A well-constructed model will have a scenario manager to allow you to set up sets of sensitivities which can be applied all at once, switching between different sets to test each scenario. Finally a word on monte-carlo simulation: This has not been specifically required by the HCA, however it is likely to be raised by some as a possible solution. Monte-carlo simulation or analysis can be used to test the overall range of outcomes that could occur, given the ranges of possible inputs for each assumption. This technique may be more than most RPs will feel is justified, however the good news is, if you decide to take this approach, it is a relatively small additional step once a robust model is in place.

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