We have been at the forefront of applied ML techniques since our first genetic algorithm engine went live in 2003. We build ML platforms for a range of situations where they can dramatically improve the efficacy of computational and manual processes. Popular applications are data quality management, simulations, calibration, optimisation, scenario and risk factor generation.
Real value is derived when we collaboratively brainstorm with you to imagine futures uses for emerging technologies. One such example is integrated chat and structured trading using NLP.... another is using NLG to summarise vast swathes of financial reports in summary texts. We build pre-production prototypes to test innovative concepts in practice, creating buy-in with internal and external stakeholders alike - in this field it often takes a multiple socialisations to gain a broad acceptance.
In 2020 we published ground-breaking developments that pave the way for the use of neural networks for modelling purposes, where regulators and clients need to be confident of explaining the model’s decisions.
Our approach to building AI, refined over many years, allows clients to progressively build confidence and create buy-in to the applications of this technology.
You may wish to read some of the following Machine Learning and AI articles by Riskcare: