Kinaesis Clarity Control
An agile control capability covering key analytical processes and data management related to risk and financial reporting within financial services.
BCBS 239 and other regulatory initiatives require that financial services firms demonstrate governance, accuracy and completeness around their calculated and reported numbers. To meet this goal, institutions need better understanding and control around the key processes that contribute to their management information. Once this understanding has been documented and signed off, institutions will be required to demonstrate a continuing governance process to maintain compliance. The challenge to an organisation is to implement this governance in a way that brings the greatest possible value.
This is made more challenging by the way analytics, reporting and MI have been implemented in many firms. In the race to provide numbers for key management or regulatory reports, the shortest route to implementation is often chosen. But this drive to meet deadlines can create multiple versions of the truth, complex dependencies between data stores, and the lack of a clear baseline from which to drive insight and knowledge.
Many firms have made attempts to implement higher levels of control key over key analytical processes, data governance, issue tracking, change management and metadata management. However this has often been at the cost of lower agility and higher operational overhead.
Legacy agility vs control trade-off
Kinaesis has developed a control model to support the process of managing key analytical processes that contribute to risk and financial reporting for financial services firms. Kinaesis Clarity Control is a suite of tools, models and processes that contain everything you need to roll out a BCBS 239 compatible data governance model.
The model integrates into existing practices, first baselining the current implementation and then providing tooling around data quality, issue tracking, change management and meta-data management. This work coupled with the roll-out of an effective operating model, establishes governance and control around your analytics and reporting, as well as enabling a process for change.
Kinaesis Clarity Control delivers a new paradigm of agile change with embedded control
Clarity Control is a suite of tools, models and processes that together deliver a comprehensive agile data governance and change management model.
- Principles: The foundation of our approach is a set of principles tested in multiple large-scale BCBS 239 implementations.
- Operating Model: A flexible operating model describes roles and responsibilities which must exist in any compliant institution. We work with your team to map existing staff roles onto the operating model.
- Processes: The backbone of the control model is a set of processes that describe key steps toward compliance – from data quality review, to software change control and data release management.
- Data Quality Control: We bring a set of best practices for the data quality lifecycle, with a focus on meaningful tolerance checks and comprehensive lineage tracking.
- Data Production Control: Detailed but low-overhead control of data production is achieved via customisable workflows, which can be hosted locally or externally.
- Reports and Dashboards: The final layer of the control model consists of the adoption of reports and dashboards, that give business an actionable view of data quality and areas of risk – and demonstrate to regulators the integrity and completeness of overall governance.
- Kinaesis Clarity Control is a combination of software and professional services
- It provides you with the control necessary to manage a financial services reporting function.
- Using the Kinaesis Enterprise Information Maturity (EIM) model and the Kinaesis Clarity Control toolset we will baseline your existing implementation quickly
- We will then establish a best practice operating model and control framework utilising the Kinaesis Clarity toolset
- Kinaesis Clarity Control tooling will close critical gaps around data quality, issue tracking, change management and metadata management.