Creating a Revenue Model
February 12, 2025
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In the world of banking and high finance, modelling or financial modelling is a term used to describe the process of forecasting and estimating risk and return as well as predict how the future would be in financial aspects.
Financial Modelling is critical to the success of the finance industry as it not only helps bankers and financiers have a grip on their investments and portfolios but also helps them to peer into the future to understand how their past and present choices make the difference between success and failure in the future.
Indeed, without modelling, it would be impossible for bankers and investments wizards to offer new investment and financial products to their customers as they cannot make profits unless they know for sure how the investment is going to turn out in the future.
This is the reason why Bankers and Investment Specialists swear by their models as it helps them to be in business.
Moreover, even Sovereign Debt is modelled and ratings of nations prepared based on the models developed by the bankers. High Finance cannot do without Financial Modelling as a tool.
Having said that, there are numerous occasions in which Financial Models have spectacularly failed as was evident during the Great Recession of 2008 when the entire financial system was close to collapse as bankers and financiers failed to not only anticipate the crisis but also to estimate the extent of damage done to the Global Economy on account of their investment decisions.
As financial models work by extrapolating the present indicators and risks into the future, anticipating what happens next is an important element of modelling.
However, it is not always the case that such predictions and models are accurate as more often than not, the probabilistic scenarios do not work out as planned and more importantly, the Known Unknowns of the economic and financial system wreak havoc on even the best modelled plans.
This is the reason why in recent years, bankers and financiers have turned to ways and means to improve their modelling using sophisticated tools and technology.
Indeed, it is believed that as technology improves so will the ability to model the future as well.
Moreover, in the present times, Algorithmic Modelling has taken over with the result that it is mostly Artificial Intelligence that is used.
So, how are models prepared and how do they work and help the bankers and financiers?
To start with, modelling is done based on past returns for the risk appetites and the present value of such investments and the probabilistic returns in the future for such investments.
This means that data from the past and the present is used to model the future returns and whether the investments would turn out the way they are modelled.
This requires knowledge of not only risk and return patterns but also information about a broad range of indicators that help bankers understand how their decisions regarding investments would turn out in the future.
In other words, models are useful as they help bankers and their clients understand what a certain sum of money invested now would yield in the future and how such investments can be broadly impacted by the Known and Unknown risks.
Indeed, this is where astute modellers succeed as they not only have the data at their disposal but also use Gut Feeling to make informed decisions about the Known and the Unknown risks that can impact the investments. So, the past informs the present which in turn shapes tomorrow.
Having said that, there has been much criticism in recent years of the models and the tools and technologies used by the bankers and financiers to prepare models.
These criticisms are aimed at how models these days are over reliant on technology and how machine learning driven modelling, though rigorous does not take into account the Human Element.
In other words, there are many who believe that modelling has become too mechanistic and disconnected from the everyday realities of the majority.
However, the fact that bankers and financiers are in the business of making money for their clients and for themselves is touted as the reason why the above criticism is invalid.
On the other hand, there is some element of truth to the naysayers as Debt Rating and Sovereign Risk and Return Models impact the lives of Billions of People and hence, there is an ethical and social case to be made for responsible modelling.
In other words, while models for the rich and wealthy can be free from emotional factors of modelling, the same cannot be said of the financial models which are prepare for nations and which impact the lives and livelihoods of the poor and needy.
Last, it is a fact that models often incorporate feedback about the past investments and the present values so that there can be better forecasts.
However, this does not always work as intended as some of the decisions might be the victims of conscious and unconscious bias of the modellers.
This is where a thorough review of the models is often needed as multiple layers of checks and balances ensure objectivity and transparency.
Moreover, cross checking enhances the reliability of models as well.
To conclude, Financial Modelling is an extremely critical element of Banking and Finance now and in future.
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