Can machine learning methods help in the process of complex risk analysis?

Risk means the probability that a business will incur losses as a result of an inappropriate decision. Risk can be successfully managed, however, through the correct analysis of phenomena which might increase or decrease the level of risk. Appropriate analysis and the identification of repeatable phenomena are the beginning of the road to risk optimisation. Machine learning methods make it possible to predict the results of decisions based on the analysis of data relating to past events. In this way, it is possible to avoid taking actions that carry excessive risk.

Machine learning supports risk analysis through the combination and exploration of very extensive data resources, as a result of which the scope of investigation is significantly expanded. Continuous progress in these areas results from increasing computing power and the development of machine learning methods. Standard analysis based on statistical models has been enriched by the use of neural network-based machine learning models, enabling much more sophisticated processing of data. The results obtained in this way are determined by a greater number of analysed relationships, and therefore serve to better describe and predict reality.

If you are faced with varying risk in your business, if your operations are associated with constant risk, let’s talk about your challenges! We will gladly advise you how you can deal with these problems using machine learning methods. We will be happy to design and build a unique solution, developed specially to meet the needs of your business.