The customer is a retail bank with a strong focus on domestic clients.
Like any other bank, it requires almost immediate insights into internal and external stakeholder data.
Building a new data warehouse, replacing certain systems, or increasing server capacities would not have been sufficient to meet the bank’s needs. What our client required was an entirely new approach, based on technology that would carry the business into the future.
In the rapidly changing world of retail banking, the majority of client-facing contact is digital.
However, banks still need to maintain a local presence to retain their personal connection with clients. Additional challenges include the fragmentation of client information across multiple systems, frequent client profile changes, reduced profit margins due to low interest rates, and the arrival of FinTechs on the scene.
Regulation is increasing and the level of detail is continuously expanding. More data, shorter timelines and higher frequency are key elements of the data-driven supervisory mechanisms. This increases pressure not only on the departments responsible for delivering data, but also on data owners, IT departments and auditors.
Furthermore, when it comes to the processing of private and confidential information, the standards required to comply with internal policies and external regulations such as GDPR are very high. In searching for a solution, our client’s finance department needed to tackle this increasingly complex problem without interfering with regular operations. They found that traditional methods were not able to produce the desired results, while new technology offered limited proof of value in this particular industry.
A PLATFORM TO CONNECT DATA, PEOPLE, PROCESSES AND SYSTEMS
The Fraxses platform provides enterprises with the means to integrate all of their data into a single, scalable platform.
It has been designed to solve a number of problems, such as siloed data, low performance for high volumes, cross-platform data reconciliations, incomplete data lineage, and the high costs of adjusting or getting new information from data producers to data consumers.
The client implemented the Fraxses platform to answer three key questions:
1. Can data virtualization deliver the same key benefits that have been seen in other industries?
2. How does the Fraxses platform leverage state-of-the-art technology and still connect to traditional data sources and legacy systems?
3. What does it take to adopt this technology from an organisational perspective?
The platform has proven that it is possible to connect seamlessly to multiple data sources (data production) and create multiple layers for data consumption. By applying a metadata approach and keeping data where it belongs, (i.e. connecting rather than collecting), data is only transferred upon request. This ensures the immediate availability of information, and on-the-fly generation of data lineage to ensure fully up-to-date technical and functional documentation. We also applied automated relationship discovery to minimise data analysis effort and maximise data usage effort.
The low-code/no-code approach ensures that business stakeholders with limited technical experience can always understand how their data is being handled/processed. Given the confidentiality and sensitivity of the information, adherence to the client’s data security policies is essential. The platform has specific functionalities, such as row level security, data masking and column pruning, to ensure compliance without hampering performance.
Furthermore, all events are logged, and each activity can be traced back to a specific user. We collaborated with the client’s internal team to establish what platform enhancements would accelerate their development and adoption of this new technology. This included proactively engaging with internal stakeholders from all other domains such as Risk, Marketing, IT and Operations.
In addition, we trained a core team of internal experts to allow for a gradual increase in the number of internal experts and data recipients, and enable adoption of this new way of working.
The client was able to reverse-engineer complex components of its legacy systems to provide data reconciliations on the most granular level, and use the same reconciliations to continuously verify the data processing.
Afterwards, the bank was able to create fully operational modules that prove the performance and scalability from the start (900m cashflow calculations from multiple different systems, fully reconciled with the general ledger in less than 5 minutes).
The platform leverages new technology while serving as the data fabric that connects all types of systems, including in-house developed product systems, databases, APIs, risk models and reporting/visualisation suites.
The platform is connected to more than six thousand tables from over 100 cross-platform databases and flat files. The largest database is >2.000gb in size, and contains key tables of over 2 billion rows and more than 400 columns.
Within days or even hours, the team was able to provide data-driven insights that would normally have taken weeks or months to deliver. All of these insights are reusable for other applications.
All of the stakeholders involved have access to real-time data lineage for the entire data process, from production to consumption, including all connections, filters, calculations and enrichment.
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