In the aftermath of the financial crisis, a stricter regulatory approach to capital adequacy and risk management has created an increasingly intricate reporting environment for the financial services industry around the globe.
Faced with numerous challenges, financial institutions need a reporting architecture that is both scalable and flexible and provides a transparent control mechanism in a strong data quality framework.
Enter Data Virtuality!
Cumbersome manual processes
The financial services industry still heavily relies on manual processes, such as spreadsheets, to collect and prepare the data for ad-hoc treasury risk reportings. However, this approach is immensely time-consuming, chaotic, and inflexible. As a result, financial institutions cannot act quickly enough on the data or, worse, might obtain outdated and invalid information.
Lack of transparency/traceability
Because the data collection and preparation processes are so chaotic, it’s often unclear where the data is coming from, whether and how it was modified during the acquisition process, who is responsible for the source data, etc. The result: poor data quality, meaning missing, invalid, inaccurate, or unutilized data that slows down the reporting and analytical processes.
Disparate data sources and varying data formats
For their reportings, financial institutions have to analyze huge and complex data sets. One big challenge is that the data sources they use are spread across internal and external systems which makes it difficult to consolidate them. To make matters worse, the data formats often also vary between the different source systems and differ from regulatory standards.
Limited control over the proliferation of sensitive data
Antiquated systems, high data latency, and unclear data lineage also have a huge negative impact on data governance, and especially the protection of very sensitive data. Moreover, most financial institutions physically store and replicate the data that is involved in regulatory reporting and compliance with little to no control over which type of user can access the data. This brings them into direct conflict with data protection laws such as the European Union’s General Data Protection Regulation (GDPR).
HOW DATA VIRTUALITY ENABLES YOU TO OVERCOME THESE CHALLENGES
WHAT YOU CAN ACHIEVE WITH DATA VIRTUALITY
6 KEY BENEFITS
No Physical Storage
Data Virtuality collects the data in a virtual layer without the need to copy or move it to a central location. This ensures regulatory compliance (especially with regards to the GDPR) when dealing with protected data.
Access Real-Time Data & Combine It with Historical Data
With Data Virtuality, financial institutions can capture, process and interpret even the most time-sensitive data in real time, and combine it with historical data as well as various data structures.
Better Data Quality and a Single Source of Truth
The data is cleaned in the virtual layer, ensuring a high data quality and a single source of data truth.
Restricted Data Access
Since very sensitive data is involved in regulatory reporting and compliances, Data Virtuality enables restricted data access depending on the type of the user.
Ease of Use
With Data Virtuality no special technical expertise is needed. Only SQL. So even for business users it is a walk in the park to get the data they want.
Save Time and Cut Costs
Data Virtuality minimizes and simplifies the effort-intensive, physical transfer of data, effectively removing lengthy data movement delays. In this way, compliant reports, e.g. for special requests or crisis situations, can be produced quickly and easily.
RELEVANT KEY FEATURES
A CENTRAL DATA MODEL
200+ READY-TO-USE CONNECTORS