Data-Centric approach & platform strategy 

Placing data at the heart of the company’s assets and initiating a Data culture

To successfully enter the digital age, financial institutions need to understand their customers’ needs as quickly as possible and make new specific offers available that meet their expectations.

The success of agile data management is linked to the appropriation of the new paradigm by employees and managers. The challenge is to enhance the value of data sharing.

Our approach

Adopting the concept of “Data Self-Service”

The adoption of a Data Self-Service organization requires a willingness to change the way things are done. It is therefore essential to identify at the beginning of the project the business perspectives, concerns and impacts in order to anticipate future problems.

Alignment of financial and technological experts

Identification of stakeholders and their concerns

Measuring the added value

Launching a Pilot Project

Placing the data into self-service

Based on the experiences of financial players who have taken the step towards “Data Self-Service”, the benefits identified are facilitated management, increased efficiency and increased team autonomy.

Putting in data each exchange

 

Making each activity a software solution

 

Disseminating the data

 

Applying advanced algorithms

Platform Strategy

Platforms have become one of the most important business models of the 21st century. The main banking players are now basing their transformation on this type of approach.

Adopting a “platform strategy” eliminates technological obstacles and make it possible to exploit the company’s essential resources.

Eliminate friction  between engineering teams to deliver services to customers faster;

Make business intelligence and capabilities accessible to facilitate innovation;

Experiment with all the company’s resources to test new ideas and remain competitive.

Governance of agile data

Our exchanges with stakeholders in the banking sector showed that the often rigid implementations of data governance have failed.

At the heart of the components of Data Governance, the Data Catalog refers to all data assets. It has therefore evolved to meet the need for collaboration between teams and the need for tasks automation.

To guarantee the success of a Data Catalog implementation, we support our customers in the choice and implementation of this new generation tool that facilitates the deployment of agile data governance.

Download “Data Catalog approach” (FR)



Our case studies

Création d’outils industriels de traitement de données ESG

Data Catalog : Etude de marché et sélection d’un outil / MVP

Shareholding Disclosure (SSD)

Related insights

A l’ère du Digital, les acteurs de la finance ont-ils la bonne approche de la donnée ?

by Pierre Bittner | 12.03.2019 | Article

A “bottom up” and integrated data quality approach

by Pierre Bittner | 04.01.2019 | Article

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