Explainable Artificial Intelligence – Project results and further development

Some of our project insights have made their way to one of the largest AI and tech conferences in the world: the #GTC21, and also to some of the largest global reinsurance companies: 

Munich Re: https://www.linkedin.com/feed/update/urn:li:activity:6773553849375494144/ 

It is one of the best rated use cases at @
fintech-ho2020.eu ('Explainable Machine Learning in Credit Risk Management'; https://link.springer.com/article/10.1007/s10614-020-10042-0) that inspired these papers both forthcoming in the Journal of Financial Data Science which will the basis for @Munich Re's #GTC talk:

The @Munich Re Markets team will present their work at #GTC21 where @NVIDIA CEO Jensen Huang will host #AI pioneers Yoshua Bengio, Geoffrey Hinton, and Yann LeCun who collectively won the 2018 ACM Turing Award for breakthroughs in deep learning.

@NVIDIA has enhanced the XGBoost open-source library by GPU-accelerated TreeSHAP and they have tested it on a huge data set described in this blog: 
https://developer.nvidia.com/blog/explaining-and-accelerating-machine-learning-for-loan-delinquencies/, similar to the one used at @fintech-ho2020.eu


Jochen Papenbrock.