This study was conducted by Business Engineering Institute St. Gallen powered by 4CAST Consulting on behalf of Contovista, Viseca, smama and e.foresight. In the form of semi-structured interviews, 14 experts from Swiss retail banks were questioned in 60 - 90-minute interviews.
Contovista - smama - Viseca - e.foresight - Business Engineering Institute St. Gallen, October 2020
Structure of the study
With a focus on the use of customer data in Swiss retail banking, the expert interviews on data-driven banking were conducted in the following topics:
«Why»-question: The expert evaluates the relevance of the potential seen in or for Data-driven Banking specifically for “his” bank. A period from 2020 to 2025 is considered.
«How»-question: The expert evaluates the adoption and implementation level of Data-driven Banking for his own company. A period from 2020 to 2025 is considered.
The adoption of the relevant-assessed topics is classified in the categories CULTURE, VISION, STRATEGY und PROJECT. The level of implementation in digital transformation is classified into the categories OPTIMIZE, DEVELOP und RENEW.
«What»-question: The expert evaluates concrete use cases and data used? For this purpose, the application categories DATA FOUNDATION, INSIGHT & ACTIVATION, OMNICHANNEL ENGAGEMENT und DATA PRODUCTS, as well as the data categories PERSON, PROFILE, TRANSACTION, INTERACTION und BEHAV-IOUR are applied.
«What is achieved»-question: Subsequently, the achieved or expected success of the measures is considered by assigning use case categories to the maturity levels REPORT, ANA-LYSE, OPTIMIZE, EMPOWER und INNOVATE.
Executive Summary
The future of retail banking begins with the customer. Their behavior is changing, some-times dramatically, led by customers who want to integrate seamless digital banking solutions into their daily life. These changes are rapidly spreading to all segments and age groups. More and more people are demanding simple, trustworthy products and services from financial institutions - or companies that provide such services - that put them first.
Data-driven means that progress in an activity is compelled by data, rather than by intuition or by personal experience.
Data-drivenness is about building tools, abilities, and, most crucially, a culture that acts on data.
Data Monetization through (new) business models is the highest form of data-driven business. The digital economy uses personalized data to offer new, customized services and products and to create a unique customer experience. Monetization takes place by offering data products.
In such an environment, customer data is a decisive factor in building and maintaining positive, sustainable relationships with customers. Correctly resolved and managed customer identities (content-based 1st-party identity) across all interaction channels are the starting point for a relevant and personalized customer approach and can lead to long-term relation-ships. The data-driven application of artificial intelligence and machine learning methods allow a direct connection between customer data and the resulting actions. A very important secondary condition is, of course, data protection, security and privacy at all times, both when storing and using personal and customer data.
“Data-driven" describes the bank's ability to respond directly to a customer action.
Two relevant capabilities must be established for this purpose:
TRUSTED DATA IN NEAR REAL-TIME – the immediate collection of data from millions of (mostly) mo-bile customer actions into a trustworthy inventory of integrated and historical customer data and profiles.
NEAR REAL-TIME BUSINESS ACTION – to model the bank's analysis and decision-making process (including segmentation and personalization) for immediate activation of a business action, when new data from customer actions arrive.
To do this, millions of the increasingly mobile customer actions have to be enriched into a trustworthy inventory of integrated and historical customer data and converted into customer profiles. Furthermore, a personalized business action has to be determined analytically and also be played out directly to the customer.
This study has interviewed experts from Swiss retail banks and provides an integrated view on this widely discussed topic. For the entire data-driven cycle from customer action to data management, insight determination, activation back to the business action, questions are classified according to business potential and relevance. Subsequently, it is shown how topics that are considered relevant in the period under consideration are adopted in corporate culture and / or strategy and implemented in projects.
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