Creating a Revenue Model
February 12, 2025
An initial public offer (IPO) is a method of selling securities wherein the entire lot of securities is offered for sale to the general public. An IPO is often used by companies when they want to sell their securities to smaller investment organizations and even retail investors. In the past few years, IPOs have seen […]
In the previous article, we have already learned that the money market is a market for assets that can act as close substitutes for cash. Most of the assets sold here have a very short maturity and the purpose of this market is to ensure that people who have excess cash can connect with people […]
Pension funds across the world are facing a significant financial crisis. This is because, for a very long time, they have been investing heavily in equities since the interest rates offered by debt funds were quite low. However, in the recent past, the equity markets have sharply declined. As a result, the asset values of […]
The European economy is facing a significant downturn. There is a looming financial crisis in Europe which has been caused by excessive borrowing in the past. However, it is unlikely that this borrowing will stop in the near future. This is because the immigrant crisis in Europe is draining its resources making borrowing inevitable. In […]
The modern world is globalized. This means that free movement of goods, services, people as well as capital is allowed across the globe. This has important implications for governments. A globalized system means that tax systems can no longer work in a vacuum. The tax systems are continuously interacting with other tax systems, whether the […]
Financial modeling is an intensive technology process. This means that at the present moment also, financial models use the latest technology in order to ensure that the most up to date results are available during the simulation. However, with the passage of time, technology is also advancing rapidly.
Improvements like machine learning, robotic process automation, and artificial intelligence are bound to have an impact on the future of financial modeling as well.
In this article, we will have a closer look at some of the ways in which technology is likely to impact the financial modeling process.
At the present moment, a lot of point of sale data needs to be collected manually. This makes the process expensive, cumbersome, and prone to errors. Manual collection of data is necessary since sensors and processors have not become so ubiquitous. However, with the passage of time, the internet of things is enabling sensors and processors to be inserted in almost every device.
Hence, companies are producing large quantities of data which describe their processes without even trying! At the present moment, machines equipped with sensors are expensive. However, in due course of time, this technology will become cheaper. This will have huge implications for financial modeling.
For instance, right now, companies make vague estimates about their electricity bill. Devices fitted with sensors will allow companies to know exactly how much electricity is being consumed by which device. Therefore, companies will be able to forecast their electricity expenses more accurately and also control them, if required.
It is very likely that in the future, devices will be pre-programmed to input data directly into financial models. This will help bypass the expensive and time-consuming process of data collection and collation.
At the present moment, financial models deal with a limited amount of data, and hence the complexity is also limited. This is likely to change in the future. As mentioned above, in the future, many devices will directly interface with the financial model. Therefore, financial models will start facing a problem of an abundance of data.
The next challenge would be to identify meaningful patterns in the data, which will enable decision making. This is where big data can help. At the present moment, big data is only used to mine customer or supplier data. However, as financial data grows in volume, this technology will find a new application in financial modeling.
At the present moment, financial modeling is limited by the skill of the person creating the model. There are many problems in financial modeling, which include multiple variables and complex interactions between them. As a result, the human mind is not capable of understanding these relationships and expressing them in mathematical form.
However, computers are capable of performing such complex calculations. Hence, ideally, computers should be able to create better models given that they have the ability to do millions of calculations in no time.
Right now also there are many ready-made templates which are used by companies to create financial models quickly. However, these templates are primitive and still require a lot of interference from humans during the customizing process.
The future is likely to have fully automated financial models which can be used out of the box without any need for any further manual intervention.
Right now, human beings interpret the data from the models. They are the ones who understand the failure or success of the model and then make the relevant changes.
In the future, financial models are likely to have artificial intelligence. This means that the computers will be able to understand the success or failure of their own model. This will be done when the system compares the actual results to the ones projected by the model.
At the present moment, the problem is that computers do not have the full range of data. To make correct calculations, computers must have a wide range of data which encompasses possible successes as well as extreme failures.
However, the statistical methods right now are not so advanced that such data can be provided to the models. It is likely that this problem will be solved in the future.
Computer-generated models will be pre-programmed with every possible output which will help the model correct itself without any manual interference. Just like self-driving cars, financial models of the future will be able to fully function without any intervention by a qualified human.
The fact of the matter is that an enterprise is a complex organism. There are so many interactions within the enterprise at so many levels that it cannot be understood completely without the help of a detailed model.
Advanced technologies in the future will help us understand this complex environment and make difficult decisions. The computational base of modeling has already been established.
It is now time to create an ecosystem wherein data gets automatically fed into the system, and the system learns from its mistakes. Building artificial intelligence into financial models is the real challenge facing the financial modelers of today.
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