Because we grew from a front office solution we can handle the data types and asset classes that other solutions can’t. Our platform was built to manage the most sophisticated data management requirements, from pricing complex OTC-traded derivatives and running multi-factor investment models, through to managing risk factors globally for the biggest banks.
That’s not to say we can’t manage the simpler data too. We provide a flexible and comprehensive platform for all types and frequencies of data – millions of assets containing billions of data points are processed each night by our clients. This means all your traded assets in one system, dramatically reducing the complexity of the final solution.
Stores and manages all
data types
Centralises calculations and
validates model outputs
Open architecture, flexible
data model and APIs
Xenomorph provides complete end-to-end data management, from acquisition, normalisation and consolidation, to cleansing, validation and distribution. This process produces centralised “gold copy” data that complies with your data policy for all data types and all asset classes.
Because our platform grew from managing complex data sets and pricing derivatives in the front office, our approach and our technology are very different from other data management solutions.
The flexible and high performance nature of our hybrid database enables the platform to deal with a wide variety of data types in real-time (Tick, Snap, Daily, Static/Dynamic Reference, Transactional, Structured) regardless of volumes and complexity.
We understand that for end user data to be relevant and useful for consumption by downstream systems, external pricing and analytics must form part of the data management process. Third party pricing models can be integrated, either directly within the system, or externally with all the outputs fed back into the data validation workflow providing full lineage and audit.
The system architecture has been designed from the outset to be entirely open so that organisations can utilise (or extend) its capabilities as required to meet their specific business needs. It comes with APIs and SDKs to allow clients to extend the system’s internal capabilities in the areas of data feed connectivity, analytics, pricing and task functionality.
The system has connectors to all major data providers, and can accept data in a variety of formats from multiple sources; our open design makes it easy to add new connections as required. All modes of data capture are supported from traditional overnight batch, to intraday, real-time snap and streaming.
Normalisation rules determine how data is brought in from an external source, or sources, and transformed into the desired format in the database. Consolidation rules can then specify an order of preference for multi-sourced data. Different orders of preference can be set for different instruments (e.g. use one vendor for FX, another for FI etc.) or specific properties (e.g. can prefer sourcing close price from one vendor, reference data from another)
The system includes pre-built objects that have a high degree of business meaning such as curves, surfaces and cubes. Business users can work on these as complete objects in their own right and analyse the complex underlying data structures as necessary.
Derived data can be generated internally using the extensive, built-in analytics provided by the system or integrating with internal and third-party products, including Numerix, FINCAD, Quantlib, R and Python. This enables automatic enrichment of the market data sets in a controlled and centralised way.
Cleansing and validation rules enable the automated processing of all data types. We maintain the relationship between a curve or surface and the underlying supporting instruments, meaning gold copy is not produced until all the supporting instruments have cleared the tests.
The system is highly configurable to suit internal data policy and provides interpolation and proxying rules to maximise STP. Equally exception handling can be automated according to custom logic, minimising and prioritising the exception management process.
Trigger gold copy creation as soon as data becomes available rather than being batched up into a single overnight process. Multiple gold copies can be managed within the system when different validation rules are required for different end-use requirements.
Whether for reports, data consumers or downstream systems the platform provides a variety of methods for extracting and distributing data. These include APIs, an Excel interface, Python and R integration, and a range of file generation options and formats.
All data management processes are controlled by fully configurable rules and workflows. The system comes with a wide range of pre-configured rules and parameters for common tasks or new ones can be created to suit a specific requirement.
Rules can be configured by users, sandboxed for testing, and promoted using maker/checker functionality. Multiple departments and locations can be assigned different asset class access permissions, process timings and rule sets.
Full data lineage is provided through the end-user interface as drill-down screens attached to each data point. All changes to data, validation rules and processes are audited, inclusive of changes to analytics and derived data.
Extensive process audit makes it easy to track backwards to discover how a gold copy data value was created i.e. what sources were used and what rules were applied, including any manual adjustment of data.