What are the possibilities for applications of artificial intelligence and Big Data Analytics in carrying out multi-criteria economic and financial analyses of business entities, analyses carried out on computerised Business Intelligence platforms?
What are the potential applications of machine learning, deep learning, artificial intelligence, Big Data Analytics and other Industry 4.0 technologies in conducting multi-criteria economic and financial analyses of the historical and current performance of economic entities and making predictions about the future development of their business, analyses carried out on computerised Business Intelligence platforms?
As a result of technological advances, the potential for the application of machine learning, deep learning, artificial intelligence, Big Data Analytics and other Industry 4.0 technologies to perform multi-criteria economic and financial analyses of the historical and current functioning of businesses and to make predictions about the future development of their business, analyses carried out on computerised Business Intelligence platforms, is rapidly increasing. New ICT information technologies and Industry 4.0, including Artificial Intelligence, Machine Learning, Deep Learning, Big Data Analytics but also Data Science, Smart Technologies, Cloud Computing, Machine Learning, Personal and Industrial Internet of Things, Autonomous Robots, Horizontal and Vertical Data System Integration, Multi-Criteria Simulation Models, Digital Twins, Additive Manufacturing, Blockchain, Cyber Security Instruments, Virtual and Augmented Reality and other Advanced Data Mining technologies support the management processes of a company, enterprise or financial institution. In recent years, the aforementioned new technologies are helping to improve the management processes of supply logistics, procurement, production, service offering; marketing communication and customer relationship management; risk management; cyber security management; economic and financial analysis management, financial auditing, etc. Therefore, within the framework of the technological advances taking place, including the increasing computational capabilities of successive generations of processors and operational memory installed in computers, increasing disk capacities, storage media, increasing data transfers, etc., the possibilities of applying artificial intelligence and Big Data Analytics in carrying out multi-criteria economic and financial analyses of business entities, analyses carried out on computerised Business Intelligence platforms, are successively increasing. Consequently, the possibilities for the application of multi-criteria analytics carried out on computerised Business Intelligence platforms are also increasing year on year, which also contributes to the improvement of organisational management processes.
In view of the above, I address the following question to the esteemed community of scientists and researchers:
What are the possibilities for the application of Machine Learning, Deep Learning, Artificial Intelligence and Big Data Analytics and other Industry 4.0 technologies in carrying out multi-criteria economic and financial analyses of the historical and current performance of business entities and making predictions about the future development of their business, analyses carried out on computerised Business Intelligence platforms?
What do you think about this topic?
What is your opinion on this subject?
Please respond,
I invite you all to discuss,
Thank you very much,
Best wishes,
Dariusz Prokopowicz
Here are several thoughts:
- Traditional business intelligence (or business performance analytics) focus on the use of KPIs (Key Performance Indicators) and generally take as few variables as necessary to provide reasonably accurate estimates. Depending on the size of the business and the complexity of the KPIs, this form of analysis can be very time consuming. With modern technologies such as AI, ML, and deep learning, this analysis will be much easier.
- Simulations: I expect that we will see far more businesses using analytics to run computational simulations using AI, ML, and Big Data. For example, suppose a company is determining the volume of television units sold at a given discounted price, with the goal of profit maximization. This form of analysis can currently be done relatively quickly, given enough data. However, for large businesses, running this analysis for every product is difficult. Further, there may be certain events/days (such as Black Friday) that cause the accuracy of the current analysis to be significantly diminished. While this form of simulation and analysis may currently be done on an annual basis, for example, it could soon be done in real time (minute by minute).
- Proactive Issue Identification: Currently, business intelligence is really only useful if someone is reviewing the insights gathered and using it to make informed recommendations/decisions. Going forward, I expect that a lot more of this will be automated, with an AI able to not only process the data, but also translate the data to business recommendations.
ML approaches are currently being extensively tested by top market/risk analysis software providers, see e.g. Article Autoencoder Market Models for Interest Rates
It should be noted that while ML shows very promising results, risk assessment processes are highly regulated, therefore any potential novelties need to undergo thorough and time-consuming testing to have a chance of being included in production.
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