The Cyoda platform can help transform and modernise many areas of finance in this modern data-driven era: investment banks, Clearinghouses, regulators, central banks and retail banks can all benefit.

Today an average tier one investment bank is often dependant on thousands of systems with technology dating back to the 70’s, 80’s and 90’s, often absorbing other systems from mergers and acquisitions. Banks have also traditionally operated in silos building systems with similar functionality for each. It is an immensely complex web of systems.

There are many different types of data: Static data, Trade data, Market Data, settlement data, reporting data, etc. These systems and types of data are more often than not all stored in different formats and even within an organisation a single trade will be stored, processed and reported on using different data models in multiple systems.

The systems that are currently at the core of banks have a fixed data model, they do not scale, are expensive to change and typically lack the transparency about what they do. This means that you could not consolidate systems in a bank using these traditional technologies and often struggle with modern regulatory requirements.

The Global Financial Crisis (GFC) of 2008 resulted in sweeping changes to the way that bank would operate, both in terms of their reduced operating margins but also the regulatory reporting that has been imposed on them. The new wave of post-GFC regulations requires banks to collect more data and report on their bank-wide data presenting systems with new challenges. Each regulation differs, resulting in different processes and data models. The timelines to report are also greatly reduced, requiring accurate timely reporting.

The Cyoda Data platform allows banks to:

  • Ingest the bank’s disparate data to allow it to comply with modern data regulations.
  • Gain real-time knowledge of its global live changing data.
  • Consolidate its systems
  • Modernise the core of it’s operations

In essence, this requires a system that can accurately and reliably process large quantities of data all in different data models with efficiency, as well as reporting on live changing data again with accuracy.

To be able to cut the cost of operations and to move to capitalise on opportunities a bank needs to consolidate its systems and become more agile.  To achieve this a system must be able to cope with the volume of data, the computational requirements to process and report on the large quantities of data and allow for differing use cases.

The Cyoda platform is not intended for the ultra-low latency world of high-frequency trading but can handle the post-execution volumes of such systems.


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Further reading:


STP Processing

Data Consistency

Easy Integration

distributed queries

Scale without limits

Technical Overview