A New Model of Risk Assessment Presented by Alessandro Nova
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A New Model of Risk Assessment Presented by Alessandro Nova

WITH THE MONTE CARLO SIMULATIONS, AN EPOCHAL REVOLUTION IN THE PROBABILISTIC RISK ASSESSMENT OF BUSINESS PLANS HAS ARRIVED

The paradigm in business risk assessment is radically shifting from deterministic models to richer and more complex probabilistic models. “This is an epochal change”, says Alessandro Nova, professor of Corporate Finance. In April 2019, he presented together with Maurizio Poli a probabilistic assessment model for business plans at #MINE, the knowledge sharing event of SDA Bocconi School of Management. The model is based on a dataset of 60,000 companies over 6 years. It can verify the degree of reliability of the assumptions underlying a business plan and the degree of risk faced by lenders through the Monte Carlo simulation, which enables estimations of unknown parameters by means of stochastic variables.
 
“Unlike existing models, it allows us to estimate not only single variables, but a perfectly congruent system of variables”, professor Nova says. “It allows us to reconstruct the relationships between the distributions of variables and the distributions of ‘downstream’ variables, through a cascading process. This is an extremely effective model in long-term simulations. Being perfectly congruent, it does not just evaluate the reliability of a business plan, but it is able to identify critical variables”. The probabilistic model is a useful tool for small and medium sized enterprises, which in Italy have a low bent for strategic planning, and even more so for financial investors and private equity funds interested in determining the reasonableness of business hypotheses. “Banks could use it too. The new reporting standard IFRS 9 requires the business plan assessment. Many banks do not have the necessary know-how to do so. This model will help them to readily verify the reliability of business plans and to determine the default probability and the analytical measure of loss”.

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