Keywords

This final part summarizes the third volume, with all its data-related aspects including architecture patterns for streaming, special databases (like graph or document-based databases) and some specific aspects of distributed ledger and self-sovereign digital identities (SSI). Furthermore, the part summarizes the whole book series.

1 Summary: Volume III—Data Storage, Processing and Analysis

This final part summarizes the third volume, with all its data-related aspects including architecture patterns for streaming, special databases (like graph or document-based databases) and some specific aspects of distributed ledger and self-sovereign digital identities (SSI). Furthermore, the part summarizes the whole book series.

Data is important! And so is an ability to process and analyze data in the best and most efficient way at minimum cost. So far, the vision of a head of digital transformation and the vision of managers target the implementation of a data-driven business model. But is a data-driven business model the holy grail of our time? Are the Big Tech and fintech companies so successful because they are data-driven?

The success of the Big Tech and fintech companies originates from the customer-oriented approach and—this is only true for Big Tech—deep pockets allowing them to follow the customer-oriented approach with a long-term perspective. Customer-oriented approaches can leverage data to understand the customer needs and deliver at the right time and via the best channel.

The data volume has significantly increased, and there is an improved ability to access and process unstructured data as well as new and differently structured data (like connected graph databases). Text processing and the whole universe of natural language processing enable the institutes to better understand the client and get a more comprehensive picture of the client’s needs and desires. Additionally, the integration of external data can provide further insights and helps by identifying the customer needs and desires.

Data protection in the form of regulations or self-sovereign digital identities (SSI)Footnote 1 is not contradictory to the customer-oriented needs and desires exploration. The connection between data protection and the identification of customer-oriented needs will stay a connection charged with tension.

In comparison to the other volumesFootnote 2 of the book series, this volume is by far the most technical. The technical view is important to understand the potential and the ways to leverage the technology, which is one of the key skills for successful digitalization.

The major benefits of the new technological innovations are primarily found in outside digitalization. The use cases in inside digitalization are already clear. They can improve the process, reduce the workload for the internal departments and reduce costs.

Data processing will improve with the help of streaming technology and the new architecture patterns (Lambda, Kappa and Delta Lake). The ability to store and handle mass data is at hand and special database types—like in-memory databases (IMDB)—can speed up mass data handling. The variety of frameworks providing models for analyzing data is overwhelming and completes the toolset (see [Liermann, Overview Machine Learning and Deep Learning Frameworks 2021] for details).

The tools are there, but they have to be put in the right business context to leverage them. The book series “The Digital Journey of Banking and Insurance” with the two additional volumes can provide support for a successful institute-specific digital journey.

2 Summary: The Digital Journey of Banking and Insurance

Digital transformation is an irreversible process, already started by most of the institutes. Even those who claim to be not so affected by digital transformation (like corporate banking) already entered this one-way street a long time ago. “Our business is so special, there is no alternative to us” sounds like whistling in the dark. Open banking will enable existing and new market participants to compose the most suitable solution for niche market segments and at scale.

Institutes will differ when it comes to the speed they choose on the digitalization path. It is not clear that an early start will guarantee and define the winner (or the group of survivors). An institute that sets up a highly advanced technology infrastructure but fails to bring technology and business together (missing the opportunity to leverage technology) will crash out in the middle of the race (and will not deliver value to the customer). Culture and the ability to change are very important for a successful digital journey that generates results.

Some institutions still puzzle over the important steps to take. A wise selection in the periodization is required, so that the one-way street does not turn into a dead end eventually. The journey has to be an individual one. The individual way will always be driven by the institutes’ strengths and the customer alignment most institutes have. Customer needs and desires can and will change. To stay customer-oriented and customer-aligned, the institute must stay close to the customer (otherwise the institute enters the mass of homogeneous products and economies of scale).

Data and personal touch points (closeness to the customer) will allow an understanding of the needs and how these needs can be met. Deep and comprehensive data analysis can help to understand the customer not only at a point in time but also in a period of time. This means identifying the customer journey, either by data or by expert judgement, and determining the client’s situation. This is mapped to the different customer journeys that, at a certain point in the journey, will demand a solution or a set of solutions served by the institution to the customer. The time dimension in this predictive case and model generates the need for advanced models, raises the data volume and causes challenges in the data processing. The time dimension brings complexity, but it can help to identify customer opportunities early on, and at best earlier than the competition.

When speaking about leveraging technology, there is always a target (improving processes, reducing costs in inside digitalization or getting closer to the customer and understanding the needs better to sell more). The impressive ideas originate from thinking outside the box, leaving the pattern with which we perceive the world. An organization that can establish a culture that lets people think outside the box, go new ways in understanding the customer and be able to use technology in different contexts than what it was designed for: such an organization is well-prepared for the changes to come.