Novuna
Data Platform Modernisation & AI Strategy
Migrating from on-premise Oracle to Azure cloud, building scalable data engineering and business intelligence, and shaping AI strategy for enterprise adoption.
The Challenge
Novuna, one of the UK's most trusted finance providers and part of Mitsubishi HC Capital, needed to modernise on two fronts. Their on-premise Oracle data platform had become a bottleneck, unable to support the volume and variety of data services the business demanded. At the same time, the organisation was exploring machine learning and AI but lacked a coordinated strategy to move from experimentation to enterprise adoption, particularly across vehicle solutions where significant manual processing persisted.
Legacy Data Platform
An on-premise Oracle data platform constraining innovation and scalability, unable to support the growing demand for data services across Group functions including consumer finance, vehicle solutions and business finance.
Manual Processing Overhead
Significant manual processing across business units, particularly in vehicle solutions, where bespoke client processes and legacy compliance requirements drove extensive grey-layer workarounds.
AI & Innovation Readiness
Emerging data capabilities and ML use cases (such as propensity modelling for arrears) needed strategic direction to scale beyond isolated experiments into enterprise-wide capability.
Our Approach
We deployed a blend of technical consultancy and engineering expertise across two complementary programmes. On the data platform side, we migrated existing Oracle services to Azure and built entirely new greenfield data engineering services. In parallel, we consulted with Novuna's technology leadership to shape their AI strategy, ensuring Novuna are in a good position to leverage future capabilities.
Technical Solution
Azure Data Platform Migration
Migrating existing Oracle data services to Azure cloud, removing on-premise constraints and unlocking scalability
Greenfield Data Services
New data engineering services built from scratch to meet evolving business objectives beyond what legacy platforms could support
Power BI Reporting
Business intelligence solutions providing group-wide visibility into operations, enabling data-driven decision making across all business units
AI & Innovation Strategy
Collaborative workshops shaping Novuna's approach to ML, automation and AI adoption, from propensity modelling to process optimisation
FinOps & Cost Visibility
Supporting better measurement, reporting and chargeback of IT costs to business units, driving efficiency and accountability
Requirements-Led Delivery
Close collaboration with stakeholders across Group functions ensuring every solution maps to real business outcomes
The Impact
Across a year-long partnership, we delivered four projects spanning data migration, new service development and reporting. Novuna's data platform moved from on-premise Oracle to Azure cloud, unlocking the scalability and flexibility the business needed. Group functions gained access to accurate, accessible and timely data through modernised Power BI reporting.
The combination of migration and greenfield development meant Novuna wasn't just moving existing capabilities to the cloud. They were building genuinely new data capabilities. The AI strategy work gave technology leadership a structured approach to scaling ML and automation from isolated experiments to coordinated enterprise initiatives.
Enablis are very collaborative and proactive in their approach. Their associates have been brilliant at turning around defects quickly and the level of skill and attention to detail has been second to none.
Novuna
Long-Term Value
Modern Data Foundation
Novuna now operates on a scalable Azure data platform supporting continued innovation.
- •On-premise Oracle constraints removed, now cloud-native on Azure
- •Scalable data engineering foundation supporting new services and ML workloads
- •Power BI reporting providing group-wide business intelligence
AI-Ready Organisation
The strategic work positioned Novuna to scale AI and automation beyond isolated experiments.
- •ML capabilities maturing, propensity modelling for arrears now in development
- •AI strategy providing structured path from experimentation to enterprise adoption
- •Process optimisation opportunities identified across vehicle solutions and consumer finance
Related Capabilities
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