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Data Governance Initiatives
From data governance management to Exprivia

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The traditional financial world is going through an era of digital transformation to better meet the needs of a market where change and evolution are no longer transitional, but have become the new normal. The widespread diffusion of mobile devices to access information increasingly in real time, the access to unprecedented wide-scale online competition, together with strong external forces, such as the acceleration in virtualisation due to the pandemic and the overwhelming amount of compliance rules that producers and consumers need to observe at all levels, have generated new requirements for banks and insurers. Lastly, new technological opportunities, such as the momentous shift towards Cloud architectures and the actual advent of A.I., are profound factors that make the evolutionary scenario more difficult.

From an ICT perspective, this has resulted in shifting the focus from Data management to Data governance and from simple checking and reading of the resulting information to advanced Analytics, with predictive and prescriptive purposes, steering ever more towards intelligent automation. Founded 30 years ago with a strong focus on Artificial Intelligence research and operating as Large Enterprise System Integrator, Exprivia has gained considerable experience in its Customers' Data Architectures, with an emphasis on innovation.

Today, it is able to help its financial customers respond to constantly changing and modern challenges, with the agility needed to make protected and reliable Data available at the required speed and to process it with highly advanced technology.

Exprivia's offer:

A sound Data Governance Strategy needs to be flexible and resilient to the changes in internal policies and external regulations and needs to steer the wave of innovation in order to optimise all business processes.

The aim of a good Data Governance Strategy is to instil "Trust" in the data by establishing the basis for making the results of advanced analyses usable and reliable, based on effective and innovative approaches and methodologies, such as A.I..

Exprivia's many years of experience in the services it offers may be summarised in the following macro areas:

  • Data Integration and Ingestion - Acquisition and management of native data (structured, semi-structured and unstructured data) to prepare it for its subsequent transformation independently of business applications and logics.
  • Data Layer Design - Design and development of Data Warehouse/Data-Lake/Data Fabric fed through Data Ingestion from different and assorted sources (legacy systems such as CRM and ERP, feeds, IoT, social media, databases, etc.) for the purpose of achieving a unified view of data.
  • Data Governance - Data management to ensure effective use of information. This includes Data Quality (Cleansing, Scrubbing,…) activities, Data Management, Data Security and Metadata Management through to highly advanced Data Virtualization techniques.
  • Data Virtualization - Logical integration of company data kept in silos in several systems without duplication, providing a central view and making it possible to have a single-entity view, while promoting governance and security. It also enables graphical representation for the creation of operational reporting and dashboards, turning data into useful information for Business and Decision Making purposes.
  • Data Risk Management - The ability to implement a Data Governance strategy alongside the expertise of the Cybersecurity Factory, allows Exprivia to address different Data Risk categories (Breach, Loss, Anonymization, ...) and offer an increasingly comprehensive service.
  • Advanced Data Analytics - Analysis of large amounts of data through the use of advanced techniques, such as Machine Learning, Predictive Analysis, Data mining, etc., with the aim of discovering relationships and correlations, making predictions and generating recommendations.