Expertise
Business Intelligence in Banking
Data platforms, regulatory reporting automation, and real-time analytics for regulated financial institutions. Built around banking-specific data models, with the lineage and governance supervisors expect.
A bank's data estate is not the same problem as a typical enterprise data warehouse. Banking data is regulated data — every figure has to be traceable from the source system through every transformation to the report it appears on. We design and build the BI layer for banks that need analytics to serve commercial decisions and regulatory obligations equally well — from the data warehouse architecture up to the dashboards business users actually open every day.
What we build
Data warehouse and lakehouse architecture
Modern data platform design for banking workloads — Google BigQuery, or on-premise alternatives where data residency requires it. We design the semantic layer around banking-native concepts (accounts, postings, positions, exposures, settlements) rather than generic enterprise schemas, so downstream analytics map directly to how the business actually thinks about its data.
Regulatory reporting automation
We design the reporting pipeline with full lineage from source system to filed return, so when a supervisor asks "where does this number come from," the answer is one click away. Suitable for institutions modernising legacy reporting estates built up over a decade of regulatory accretion.
Risk and capital analytics
Credit risk, market risk, liquidity risk, and operational risk dashboards built on a common data foundation rather than fragmented spreadsheets. We build for the daily operational view your risk function actually uses, not just the quarterly board pack.
Customer and product analytics
Segmentation, customer lifetime value, product profitability, channel attribution, cross-sell propensity, and retention modelling. We focus on analytics that drive specific commercial decisions — pricing changes, marketing spend allocation, branch or channel investment — with a measurement plan so the value of each model is demonstrable in revenue or cost terms.
Real-time operational dashboards
Streaming analytics for payment operations, fraud monitoring, treasury, and channel performance. Built on Kafka, Flink, or managed equivalents, with materialised views feeding low-latency dashboards. Suitable for operations teams that need to see what is happening right now, not what happened yesterday — and for incident response when minutes matter.
Self-service BI and semantic layer
Power BI, Tableau enablement with a properly governed semantic layer underneath, so business users can answer their own questions without producing fifty conflicting versions of the same metric. We define and maintain the metric definitions, certified datasets, and access controls so self-service does not become self-inflicted reporting chaos.
Why banks work with us on BI
Banking-native data modelling
We model the warehouse around how banks actually work — accounts, postings, positions, balances, exposures — not generic enterprise schemas adapted from retail or manufacturing. Engineers who do not know the difference between a posted balance and an available balance cause expensive bugs in banking analytics. Ours do.
Regulatory-grade lineage and governance
Accuracy, completeness, timeliness, traceability — are designed into the pipeline from kickoff. Lineage is captured automatically through the transformation layer, data quality rules are versioned alongside the code, and metric definitions are governed centrally. Your second line and regulators get the auditability they expect without a retrofit programme.
Integration with core banking and trading systems
A BI platform is only useful if the data flowing into it is correct, complete, and timely. We have hands-on experience integrating with core banking, card processors and payment platforms — including the awkward edge cases around late postings, value-date adjustments, and reversals that less experienced teams routinely get wrong.
Production-grade, not proof-of-concept
We measure success in dashboards business users open daily, regulatory returns filed without manual fix-up, and data quality SLAs met without intervention. Engagements include observability, alerting, runbooks, and handover — not a deck declaring victory at go-live.
Vendor-neutral on the stack
Our recommendations are shaped by what fits your data volumes, latency requirements, regulatory geography, and existing skills — not by partner incentives. Where the right answer is "stay on what you have and fix the architecture," we say that.
Knowledge transfer to your team
A BI platform owned only by the consultancy that built it is a liability. We design our engagements so your data engineers and analysts can extend the platform after we leave — through documented patterns, paired implementation, and explicit enablement workstreams.
Related Services
Solution Design
Technical architecture for regulated financial institutions — the bridge between strategy and implementation. Integration architecture, data design, security and compliance built in, and non-functional requirements specified to the level engineering can actually build from. Vendor-neutral across the platform stack; senior architects with hands-on production experience.
IT Strategy
Multi-year technology roadmaps for regulated financial institutions — current-state assessment, target architecture, vendor and sourcing strategy, business case modelling, and regulatory-driven platform decisions. Led by senior partners with hands-on banking implementation experience, vendor-independent across the cloud and platform stack, with MBAs from London Business School and Columbia.
Work with our Business Intelligence in Banking specialists
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