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Simulation-based digital twins represent an effort to provide high-accuracy real-time insights into operational physical processes. However, the computation time of many multi-physical simulation models is far from real-time. It might even exceed sensible time frames to produce sufficient data for training data-driven reduced-order models. This study presents TwinLab, a framework for data-efficient, yet accurate training of neural-ODE type reduced-order models with only two data sets.

Correlations between test errors of reduced-order models and distinct features of corresponding training data are investigated. Having found the single best data sets for training, a second data set is sought with the help of similarity and error measures to enrich the training process effectively.

Adding a suitable second training data set in the training process reduces the test error by up to 49% compared to the best base reduced-order model trained only with one data set. Such a second training data set should at least yield a good reduced-order model on its own and exhibit higher levels of dissimilarity to the base training data set regarding the respective excitation signal. Moreover, the base reduced-order model should have elevated test errors on the second data set. The relative error of the time series ranges from 0.18% to 0.49%. Prediction speed-ups of up to a factor of 36,000 are observed.

The proposed computational framework facilitates the automated, data-efficient extraction of non-intrusive reduced-order models for digital twins from existing simulation models, independent of the simulation software.

The purpose of this paper is to analyse and investigate how intensified regulatory requirements related to outsourcing have influenced and changed the outsourcing activities of German financial institutions.

The study involved interviewing 11 outsourcing experts in the German financial sector, including four of the five largest banks in Germany. In coding and analysing the collected data, this study adopted the approach of a qualitative content analysis framework.

The study found that the revised legal requirements have had a significant and potentially negative impact on the efficiency of outsourcing, leading to a necessity for German financial institutions to internally realign their outsourcing managements. The study further revealed practical realigned methods German financial institutions executed to meet the legal requirements.

The impact, meaning and relevance of legal requirements in the outsourcing environment of German financial institutions has been relatively under-researched from a qualitative perspective and focused on other primary fields of investigation like outsourcing decisions and outcomes. This study has, by adopting a qualitative approach, addressed the identified gap by providing first-hand insights and new knowledge.