Knowledge Management of Private Banks as an Asset Improved by Artificial Intelligence Discipline—Applied to Strategic McKinsey Portfolio Concept as Part of the Portfolio Management

Abstract

As first part of the scope of this publishing item it is to demonstrate a possibility to support the evolution of the knowledge management discipline for Financial Services industry with the Artificial Intelligence (AI) technology, e.g. Machine Learning (ML). As one of the banking core capabilities the part of strategic Portfolio Management will be focused as use case along the results out of the step mentioned-before. Knowledge Management (KM) is an essential core part of business development and prospering of each individual, group and organization—this discipline is an asset of each organization to do right the right things on a subject matter expert level. It is a major influencer for the setup of many IT systems with its functions [43, 54]. In addition, an existing well-organized Knowledge Management can help to flatten the shortfalls of professionals whilst the knowledge will be saved, improved and up-skilled. KM in a private bank can divide into an external and internal view—to have a look into the external direction, mainly the customer is in the focus in terms of its requests—the market knowledge. Opposite of them it exists bank internal knowledge more or less aligned with the processes as well as workflow chains to satisfy the mentioned customer demands as well as the bank strategy. Moreover, as one approach the knowledge can be separated into the categories explicit and tacit knowledge based on the SECI model [3]. Yet the exploit knowledge visible in documents, data records of knowledge data bases, workflow descriptions, content explanation is easier to retrieve, maintain and use than the tacid knowledge with its thumb rules, heuristics, intuition. The listed items are examples, there are many expressions of these categories existing, also depends on the industry sector [39]. To improve / scale up to a higher level the knowledge management of the private banks the Artificial Intelligence technology can support to generate new knowledge entities, models, scoring points, measurements, probabilities under the usage of various categories of algorithm [17]. As one of the essential strategic parts of a bank there is to create the own portfolio concept to be ensure the definition of the main indicators, the strategic business units (e.g. Fond business), the appropriate scorings, probabilities drill-downed and related to sub-indicators as well as deviations on the whole business units. The next part of the scope for this article is focused to use the Knowledge Management on the McKinsey “GE-Matrix” or “Nine-box-matrix” adapted for generation of a Strategic Portfolio Management within Private Banking Financial Services. In addition, based on the previous-mentioned aspects this article reflects a short introduction into the possibility for a seamless AI guided workflow circle of strategic portfolio creation based on explicit and tacid knowledge and gives a preview for risk assessment, alternative portfolio model simulations and finally the trade order management related to the regular portfolio revision (re-balancing and upgrading) based on the underlying technology described in this article [24,25,26,27,28].