Our client needed to implement reporting and controls to adhere to Dodd-Frank Act Volcker rule requirements. However, data was siloed across finance, risk and operations.
Our client wanted to avoid developing a tactical point solution as it would result in an inefficient operational process with limited data controls and poor return on investment. But with a fixed regulatory deadline they needed a viable plan.
Kinaesis worked with our client to assess their data maturity and ability to deliver the Volcker requirements using the Kinaesis Enterprise Information Maturity (EIM) matrix. This highlighted the areas that needed to be addressed to deliver the requirements in strategic manner - notably data delivery, data lineage, data frequency, governance and project delivery.
Kinaesis developed an action plan to on-board the data onto our client's strategic data warehouse and develop the reporting required. We also developed a target operating model to ensure that technology and operational needs were addressed.
We conducted data life-cycle walk-throughs to prove that the data and proposed solution were viable. This highlighted critical issues that needed to be addressed early, it also provided project sponsors with a high level of confidence that the project would deliver on time.
We on-boarded the required data quickly ensuring that additional data could be added fast in the future. We embedded data governance and quality control into the operational and change process. We quickly added the data into reporting marts to give users early sight, enabling refinement of reporting and the underlying data in order to meet all requirements.
The project was delivered on time on a strategic platform. The data sourced to deliver the project was made available in the client's strategic reporting platform providing leverage for other reporting needs.
Using the Kinaesis approach we identified data issues early in the project which significantly reduced delivery risk and data sourcing issues were solved early in the project. Data was exposed to users quickly with iterative deliveries using a data-driven on-boarding framework enabling fast effective refinement of reporting and process.
Data quality issues were exposed and fixed through embedded data governance and quality processes.