The IT revolution and the increase in computing and storage capacity, together with new business and organizational developments in firms, have led to a general trend towards automation in modeling. In addition, organizations are developing more and more models to manage all company areas, which makes it necessary to evolve towards more automated and efficient development processes.

AutoML and Component Modeling

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This automation involves transforming strategy, developing mechanisms that allow component-based modeling, and incorporating elements such as the use of open-source languages or the migration to flexible technologies with greater computational capacity, usually Cloud-based.

At Management Solutions, we have extensive experience in the development and implementation of advanced analytics techniques, with special focus on the development of artificial intelligence and machine learning algorithms.

Based on the latest trends, much of our work has focused on component-based modeling, a way of modeling that allows you to structure each task into a separate component that can be used flexibly to produce different levels of automation.

Moving towards a component-based approach allows you to standardize the development of each task in the modeling process, also improving the quality of the work and the level of control over it. The focus is therefore on best-in-class development of each component, taking advantage of best practices in each area, and ensuring all components work properly through a single validation process. Thus, the organization can have a set of already developed components available that can be used by different modeling areas with different levels of knowledge, which at the same time improves development efficiency.

In addition, the R&D Data Science team has developed ModelCraft, a Cloud-based tool that delivers component modeling and automates end-to-end model development processes. With over 45 different components, Modelcraft speeds up the pace of our clients’ modeling strategy transformation process.