Data Strategy, Engineering & Analytics
We build the data foundations institutions need and produce analysis from large and complex datasets.
Data strategy and governance
Turning business questions into a plan for what to build and in what order.
Data strategy and governance
Turning business questions into a plan for what to build and in what order.
- Use cases identified and prioritised on value against effort
- Governance covering data quality, ownership, privacy, security and the rules that keep data consistent
- Target operating model for a data function including roles, skills and reporting lines
- Readiness assessment covering what data exists, whether it can be used and what is missing
Data architecture and engineering
Pipelines that handle extraction and reconciliation on a scheduled basis.
Data architecture and engineering
Pipelines that handle extraction and reconciliation on a scheduled basis.
- Automated pipelines pulling from core banking, lending, cards, CRM, channel, rating, early warning, ICAAP and other systems
- Central warehouses and lakes with historical snapshots and full audit trails
- Consolidated customer views, including identity resolution, record linking and de-duplication across sources
- Validation, cleansing and transformation with lineage tracking and role-based access
- On-premise, cloud or hybrid deployment
Business intelligence and reporting
Management and board reporting generated on schedule.
Business intelligence and reporting
Management and board reporting generated on schedule.
- Scheduled and on-demand generation of regular reports
- Interactive dashboards with drill-down covering exposures, rating migration, vintage analysis, sector concentration and NPL trends
- Manual adjustment workflows that remain fully traceable
- Built around Basel III, IFRS 9 and local regulatory requirements
- Designed so new risk areas can be added later
Analytics of complex datasets
Producing reliable measures from large and fragmented datasets.
Analytics of complex datasets
Producing reliable measures from large and fragmented datasets.
- Measures and indicators defined, built and documented over large transactional and administrative datasets
- Behaviour reconstructed over time: how populations move between states, recover, default or comply
- Underlying data issues addressed directly, including duplicates, backdated and deferred effective dates, and records held outside curated layers
- Statistical design and evaluation where an intervention is being tested, including sample sizing and balance checks
- Delivered as production code on enterprise data platforms, documented so your team can maintain it
How we work
Audit what exists, design the target, build and integrate, then monitor, extend and hand over.
Who it's for
CFOs, CIOs, Chief Data Officers, Regulators, Transformation leads