Why does sustainability matter in banking and…
Sustainable banking implies taking the environmental, social, and governance (ESG) effect of banking operations and activities into account. By prioritizing…
Data management is the process of managing the data created and collected by an organization. It starts with policies and tools to ingest, store and organize the data – and the nomination of Business Owners responsible for its quality and uses. It also covers data usages such as Data Analytics (Artificial Intelligence models and Business Intelligence dashboards). Finally, data retention policies and data purge are also an important topic for a Data Management Team.
Those activities are crucial to provide analytical information and help drive decision-making and strategic planning by executives while staying compliant with data protection regulations such as GDPR.
In short, Data Management is about building trust in data.
The main concern is Data Protection: protecting sensitive / confidential data from unauthorized access, data breaches, and cyber-attacks is essential. It requires robust security measures and policies.
Another factor is Data Integration and Data Scalability: more and more data are gathered from heterogenous sources, big data and IOTs. In order to ensure Data availability, it is crucial to scale the organization’s IT systems accordingly.
“Data Democratization” is a trend we hear every day. Having more data available means everyone wants to access it, usually in a way that is fast and user-friendly. Data Management teams around the world are working to set up systems to enable “self-service” data analytics to their users.
Also, Data Quality has always been critical to leverage valuable insights. In the near future, we will see AI Models emerge and take on complex processes like Data Health monitoring.
Banking is one of the most heavily regulated sectors: as such, directives like GDPR and the Cloud Circular (from CSSF*) really boosted Data Management in Luxembourg’s Financial Sector during the last decade.
Also, the rise of Big Data and AI (in Credit Risk, for example) underlined the needs for a mature Data Management System that can provide data in mass, while being performant and ensuring data quality.
*The Commission de Surveillance du Secteur Financier is a public institution which supervises the professionals and products of the Luxembourg financial sector.
1. Understand what data you share and how it will be used.
2. Manage Data Access: Identify your sensitive information and choose which (internet) cookies you want to share, which information you put in your personal / corporate cloud / social network…
3. Make it a habit of clearing data from your old devices such as smartphones, laptops but also connected devices and cloud services.
4. Educate yourself / your children / your employees: As Data communities are growing, it is more than ever simple to become “Data Literate”.
5. Stay Informed on Data Regulations and Data trends.
About the blog:
There is an urgent need for rapid transition to global sustainability. Business and industry have enormous social and environmental impacts. "Why does it matter?" is a bi-monthly blog that aims to elucidate this important topic through the eyes of our experts.
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