To implement meaningful and high-quality data analyses, data preparation is of paramount importance. One step in data preparation is feature engineering - an optional process designed to make information implicit in the model explicitly accessible. Feature engineering requires the use of domain or expert knowledge to make the information explicitly available. Feature Engineering is investigated in this blog post against the background of different models using information extraction from temporal data. The consideration of domain knowledge for Feature Engineering seems to be useful and essential for the creation of more detailed analyses, also considering the effort involved.
Apple's strategy of enforcing an identity management system on local devices to store and reuse sensitive customer information is potentially disrupting the exponentially growing and highly profitable identity market. Possible cooperation and mitigation models are discussed in detail in our blog post "Apple Identity Wallet - Disruption as a catalyst for digital transformation".
FINMA is specifying the regulation of stable coins, formulating high requirements and also taking a stand on Libra. The comments cast doubt on the short-term launch of Libra in the first half of 2020, especially as other national regulators (particularly Germany and France) are explicitly positioning themselves on Libra and first members of the Association are questioning their support.
At the same time, the Chinese stable coin developed in the state-initiated DC/EP (Digital Currency/Electronic Payments) project remains largely unnoticed by the media in Europe and the USA. Although the danger of the international central banking system being undermined by DC/EP is not perceived as acute, the "China-Coin" is still controversial due to its potential for political abuse.
The market, regulation and supervision in the USA and Europe, however, have yet to provide their own answer to the gap in supply for efficient, scalable digital currencies addressed by Libra and DC/EP.