Mastek Transforms a Central Bank’s Legacy Monetary Policy Forecasting Environment with Databricks Powered Economic Lakehouse
For central banks, forecasting in monetary policy is critical for managing economic fluctuations, market expectations, and interest rate risks to achieve price stability and liquidity compliance. Efficient and effective forecasting is vital as any lag in monetary policies adversely impact the economy and the ability of banks to plan ahead for future economic conditions and potential disruptions
With forecasting shifting towards more complex data models to address today’s uncertainty, transforming the forecast process to support agile decision-making is what central banks aim for.
As the client’s strategic data modernization partner, Mastek is transforming the monetary and forecasting ecosystem with an Azure-based economic lakehouse leveraging ADF 2.0 + Databricks
Client Snapshot
The monetary policy committee of an influential nation’s central bank, our client makes critical decisions on interest rates and quantitative easing to manage inflation and support the nation’s economic growth.
Challenge
The central bank was constrained by fragmented legacy systems with several specialist modelling languages (such as Julia, Dynare, Stata) to manage a highly complex and regulator-critical monetary policy forecasting environment.
Hampered by their existing manual workarounds, limited traceability, governance, and auditability, the client was looking for a scalable, secure, and future-proofed economic data and modelling platform.
Solution
Mastek used their nexus™ method to address the client’s requirements and implemented the project in three phases. Robust quality management, change control, and regulatory assurance were ensured through all stages.
The discovery phase involved 4-week immersive workshop sessions with the client’s subject matter experts covering forecasting processes, modelling techniques, data flows, NFR/FR, and regulatory constraints.
Design and solutioning was the second phase where collaborative blueprinting was achieved across architecture, migration, business change, governance, and processes.We are currently delivering the final phase of implementation. This involves agile delivery of a cloud-native, Azure-based economic lakehouse using Azure Data Factory (ADF) 2.0 and Databricks, following the Medallion Architecture, which organizes data into bronze, silver, and gold layers for improved data quality and analytics. Microsoft Purview provided enterprise-wide governance, metadata, lineage, data quality, sensitivity labelling, and audit trails.
It was a notebook-driven execution of complex economic and monetary models – and its secure and compliant architecture were completely aligned to the central bank’s regulatory standards.
Impact
- Scalable, future-ready forecasting and near-casting platform
- Improved transparency, auditability, and regulatory confidence
- Reduced reliance on manual workarounds and undocumented processes
- Clear migration path from legacy systems to cloud-native analytics
- Strong alignment across business, technology, and compliance stakeholders
Share: