What does the Future have in Store for Financial Modeling?

The data from the models is currently interpreted by humans. They are responsible for analyzing the model's success or failure and making any necessary changes. Artificial intelligence is likely to be incorporated into financial models in the future.

Fremont, CA: Technology is an integral part of financial modeling; therefore, current economic models use the latest technology to ensure that the most recent results are available during simulations. Financial modeling is more likely to be impacted as technology advances, such as machine learning, robotic process automation, and artificial intelligence.

Technology is likely to impact financial modeling in the following ways:

Automated data collection

Most point-of-sale data is collected manually in the present state of operations, and it is an expensive and tiring task that is prone to errors throughout its work. Manual collection of such data was inevitable as the use of sensors and processors was not a common sight to behold, which is being replaced slowly and steadily by the Internet of Things-assisted sensors and processors in almost every aspect of working. The use of IoT-assisted devices helps companies produce and process large quantities of data, even though the initial cost involves implementing such complex machinery. In time, the expense associated with the systems may subside. This can lead to developing cheap, practical strategies that may be used extensively. Companies with electrical sensors can detect the electrical cost associated with working the machinery.

Big data in financial modeling

The present scenario of operations involving financial models deals with a limited amount of data which is seen to be in the process of acquiring change as the interaction with complex machinery and sensors are on the rise. Financial models would soon be challenged by the abundance of data with the inputs from the machinery in order to determine the pattern that would directly affect the process of decision-making. The inclusion of big data into the working can resolve the issues to a large extent as it can handle the influx of large quantities of data over a short period of time.

Automated model development

Financial models are limited to the skills of the person undertaking the process of development at the present moment and are largely affected by the problems caused by various factors, such as multiple variables and complex interactions between them. Such complex calculations are not easily understood by human minds and, as a result, fail to express them in their mathematical form. Computer-generated algorithms and programs are capable of identifying and performing such complex calculations, and thus they are expected to generate better models with their skills. Firms are keen on using pre-generated templates for the creation of models, which are quite outdated and primitive in their working structure and usage and require extensive human interaction in their operational duration.

 Automated model updation

The data from the models is currently interpreted by humans. They are responsible for analyzing the model's success or failure and making any necessary changes. Artificial intelligence is likely to be incorporated into financial models in the future. By doing so, computers will be able to understand the success or failure of their own models. The system will do this by comparing the actual results to those projected by the model.

Computers do not currently have access to all types of data. A computer must be able to process a wide range of data, including possible successes as well as extreme failures, in order to make accurate calculations. As of now, statistical methods are not advanced enough to allow such data to be incorporated into models. There is a good chance that this problem will be solved in the future.