BI for banks, wealth managers, and insurers — risk dashboards aligned to Basel III, regulatory reporting that survives examination, customer analytics across business lines, and the governance discipline that holds up to model risk management review.
A regional bank stands up a BI program and within a year has 200 dashboards across business lines. The next regulatory examination asks pointed questions: which dashboards inform capital decisions, who validates the underlying data, what controls exist around the calculations, when was each one last attested by the business owner, how do the numbers reconcile to the official ledger, and where is the documentation that shows the dashboards aren't producing decision-making that should fall under model risk management. The BI team can answer for 20 of the 200 dashboards. The other 180 were built informally by analysts in business lines, with no governance, no validation, and no documentation. The exam finding makes its way to the bank's risk committee and the BI program gets paused for remediation. This is the predictable outcome when BFSI BI is treated like commercial reporting.
BFSI BI done right is built like a regulated system from day one. Governed semantic layer with documented metric definitions and lineage. Data validated against the ledger with documented reconciliation. Access controls aligned to data sensitivity and user role. Model risk management integration for any dashboard that produces decisioning numbers. Regulatory reporting automation that holds up to examiner scrutiny. And the change control process that tracks who changed what and why. None of this is glamorous, but all of it is what separates BI that survives examination from BI that gets paused after the next exam.
BI for the risk metrics regulators care about — RWA composition, CET1 ratios, LCR, NSFR, IRRBB, and the sensitivities that risk committees review. With the lineage and validation that supports examination questions and model risk management documentation.
Automated regulatory reporting for Call Report (FFIEC 031/041), CCAR/DFAST submissions, FR Y-9C, FR Y-14, and the state and federal insurance reporting cadences. With the audit trail and reconciliation discipline examination cycles require.
Customer analytics that joins data from retail banking, lending, wealth, and insurance for relationship profitability, cross-sell propensity, and attrition analysis. With privacy controls aligned to GLBA, CCPA, and similar financial privacy regulations.
BFSI BI delivered audit-ready: governed semantic layer with documented metric definitions, dashboards reconciled to the ledger and risk system of record, integration with model risk management for decisioning dashboards, automated regulatory reporting workflows, role-based access controls, change control processes, and the examination response toolkit that gets the program through the next regulatory review.
The full Business Intelligence Consulting practice across industries.
All BFSI technology services from Xylity.
Industry-specific consulting across the verticals we serve.
Power BI tends to win in Microsoft-heavy institutions because of the M365 integration, the licensing model for high-user-count BI, and the governance capabilities in Power BI Premium. Tableau wins in some institutions on visualization sophistication. Qlik is less common but strong in some European banks. We help you decide based on existing stack and audience.
By identifying which dashboards produce numbers used in decisioning (capital, credit, pricing, risk) and bringing those into model governance with documentation, validation, and periodic attestation. Most dashboards are reporting and don't trigger MRM; the ones that do need to be governed accordingly. We help draw the line and build the governance.
Yes. Pre-qualified BI developers and analytics engineers with banking, wealth, and insurance domain experience — risk metrics, regulatory reporting, model risk management, and the SQL discipline to build models that survive examination. 92% first-match acceptance.
Governed semantics, model risk management integration, ledger reconciliation — BI built like the regulated system it is.