Elevating companies to data-driven businesses

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Along the entire value chain, financial institutions (asset managers, banks, real estate managers and insurance companies) essentially work with one thing: data. Whether for a better understanding of customer needs for a personalised approach, an optimal utilisation of marketing budgets, an effective mapping of ESG requirements, automated processes in middle and back office or modern risk management - the amount of data available to companies is growing rapidly and technologies offer more and more possibilities at the same time.

Data-driven work offers these advantages

As a result, data is increasingly becoming a production factor. In the future, the financial institution of the future will work digitally and data-driven, from corporate management to the clerks. This enables:

Data-based decisions at all levels of the company through faster, reliable, consistent and transparent information.
New products, services and a personalised customer approach for more relevance to the various target groups.
Process optimisation and automation to improve your own value chain. This can increase competitiveness and reduce costs and lead times.
Changes to the business model and new cooperations through data-driven insights and an exchange of data with other industries to open up new sources of revenue.
Regulatory certainty through efficient use of data and more transparency.

With the development of a data-driven target picture, it is important to look at data end-to-end (E2E) and lay the foundation for the data-driven financial institution via the appropriate building blocks.

Data as a success factor: start your data-driven journey with us.

The six fields of action as building blocks for the data-driven financial institution

On the way to becoming a data-driven organisation, six main fields of action need to be taken into account and designed for one's own organisation. These fields of action can also be understood as building blocks and are put together in a customised way depending on the objective and level of ambition.

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Data-driven organisation" strategy

With the help of the appropriate data strategy, it is determined how the business model can be supported in the best possible way in a data-driven manner, how the organisation will use data in the future and how it will be enabled to work successfully with data on a broad scale through the appropriate data culture.

Data architecture and infrastructure

In order to be able to use data in an integrated way along the entire value chain, it is necessary to design the appropriate data platform. Cloud components and modularisation approaches are increasingly being used to offer flexibility for future business and changes in the market.

Data management

Data management determines how data can be used in a quality-assured manner. Topics such as data governance, data quality and data protection also play a role. Structured data management enables the organisation to work efficiently with data, for example through the use of a data catalogue.

Automation

A structured data layer offers enormous potential for automation, especially in the financial industry. Processes can be automated E2E via integrated approaches of robotics, data & analytics/KI and workflows.

Insights

Approaches from the field of data & analytics/AI, such as machine learning, have now reached a high level of maturity and can be used for a wide range of decision-making problems. This allows insights to be generated for optimising processes along the value chain.

Reporting and planning

Modern approaches in the area of reporting and planning enable better corporate management and mapping of regulatory requirements. At the same time, personalisation and self-service can also be used to gain points at the customer interface.

Rethinking the Finance Industry: Start Your Transformation to Data Driven Business Today

Against the backdrop of the current market situation and the VUCA environment in which the financial industry finds itself, it makes sense to consistently question the previous value creation: differentiating business capabilities need to be strengthened and supporting business capabilities need to be efficiently designed, for example through data-driven automation.

This is precisely where the transformation to data-driven business comes in: The foundation for the future is laid via the appropriate target image. The right use of data enables the balancing act between growth for the future and cost efficiency in operational value creation. In realisation, it is important to harmonise strategy and operationalisation: A strategic target picture serves as a guide for daily implementation.

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