La Academic

In digitalization era, banks and financial organizations are rushing their digital transformation. As part of this revolution, financial organizations produce extraordinary quantities of data about their financial and insurance procedures while using unconventional digital technologies (e.g., big data, AI, Internet of Things (IoT)) to gather, study, and fully leverage the generated data assets [1]. Furthermore, recent regulatory developments (e.g., the 2nd Payment Services Directive (PSD2) in Europe) [2] facilitate the sharing of data across financial organizations to enable the development of innovative digital finance services based on novel business models. The latter aim at lowering the barriers for new market players (e.g., payment service providers (PSPs) in the PSD2 context) to develop and roll out new services in ways that increase clients’ fulfilment and generate new income streams. Overall, financial and insurance groups take benefit of big data and IoT technologies with th

Today, ELC would love to share an eBook entitled Multivariate Statistical Analysis in the Real and Complex Domains written by Arak M. Mathai, Serge B. Provost, & Hans J. Haubold and published by Springer. Multivariate statistical analysis occasionally proves to be a difficult subject for students. The problem arises in part from the reliance on several types of symbols namely subscripts, superscripts, bars, tildes, bold-face characters, lower- and uppercase Roman and Greek letters, etc. However, resorting to such notations is necessary in order to refer to the various quantities involved such as scalars and matrices either in the real or complex domain. The first author was seeking means of making the study of multivariate analysis more accessible and enjoyable. There are several Special Features that I’d like to point out from the book: 1. Its most distinctive feature is its development of a parallel theory of multivariate analysis in the complex domain side by side with the