Data Platforms Built for Financial-Grade Reliability
Audit-ready data warehouses, real-time fraud detection, and regulatory reporting pipelines. Built for banks, insurance companies, and fintech firms where getting the numbers wrong is not an option.
The Problem
Financial Data Challenges We Solve
Regulatory Reporting Burden
SOX, Basel III, Dodd-Frank, IFRS 9. Every quarter your team spends weeks assembling regulatory reports from disconnected systems. Manual reconciliation, copy-paste errors, and the constant fear that one number is wrong and the auditors will find it.
Real-Time Fraud Detection Gaps
Your fraud detection runs on yesterday's data. By the time the batch job finishes and the alert fires, the money is already gone. You need sub-minute detection, but your legacy systems were not built for real-time.
Legacy Mainframe Data
Core banking on DB2, COBOL programs nobody wants to touch, AS/400 systems running critical processes. The data is there, but extracting it without breaking production is a constant tightrope walk.
Audit Trail Requirements
Auditors want to trace any number back to its source. Your star schema overwrites history. You cannot tell them what the data looked like last Tuesday at 3pm. Every audit becomes a scramble to reconstruct what happened.
Multi-Source Reconciliation
Payment processor says one thing, the ledger says another, and the CRM has a third number. Monthly reconciliation takes your team 8 days of manual cross-referencing. Discrepancies pile up faster than you can investigate them.
How We Help
Financial Data Engineering That Auditors Respect
Snowflake Financial Data Warehouse
A single, governed warehouse for transactions, positions, risk, and compliance data. Snowflake's separation of compute and storage means your regulatory reporting jobs do not compete with your analytics queries. Time Travel gives you point-in-time access for any audit question.
Real-Time CDC Pipelines
Change data capture from mainframes, core banking systems, and payment processors with sub-minute latency. We use Talend CDC and Snowflake Streams to capture every transaction change in real time. Fraud alerts fire in seconds, not hours.
dbt Regulatory Reporting Layers
Transformation layers built in dbt with version-controlled SQL, automated tests, and full lineage tracking. Every regulatory calculation is documented, tested, and traceable. When the auditor asks how you computed a number, you show them the dbt model, not a spreadsheet.
Power BI Executive Dashboards
Real-time dashboards for risk exposure, P&L, compliance status, and fraud alerts. Row-level security ensures each business unit sees only their data. Refreshed in minutes, not days. Built for the executives who actually need to make decisions.
Data Vault Modeling for Audit Compliance
Data vault 2.0 methodology that keeps a complete, auditable history of every record change. Hubs, links, and satellites with hash keys, load timestamps, and source tracking. Nothing is ever overwritten. Auditors can trace any number to any point in time across any source system.
Proof It Works
Financial Services Projects With Real Numbers
Regional Bank — 48-Hour Reporting Lag to Real-Time Fraud Alerts
A bank with 1,800 employees was relying on batch processing for fraud detection with a 48-hour lag. Monthly reconciliation took 2 analysts 8 full days. They had 23 SOX findings. We deployed Talend CDC to capture transaction changes in real time, built Snowflake Streams and Tasks for processing, and created dbt transformation layers for fraud rules and regulatory calculations.
SaaS Finance Team — Single Source of Truth with dbt & Snowflake
A 600-employee SaaS company had 47 different Excel models for revenue recognition. Month-end close took 12 days. Three different departments reported three different ARR numbers. We consolidated everything into Snowflake with dbt transformation layers, automated 280+ tests, and delivered a single source of truth that auditors called the best data environment they had seen.
Ad-Tech Company — Redshift to Hybrid Architecture
An ad technology firm processing 8 billion impression events per day was spending $47K per month on a Redshift cluster that locked up for 20+ minutes on analytics queries. We built a hybrid Snowflake architecture with Snowpipe and AWS Kinesis for ingestion, cutting monthly costs by 60% while eliminating query contention entirely.
Our Stack
Financial Data Technology
Financial Data Questions
We Hear Every Week
We use data vault modeling which gives you a complete, auditable history of every change to every record. Every load is timestamped, every source is tracked, and nothing is ever overwritten. On top of that, we build dbt transformation layers with automated tests that validate regulatory calculations, and Power BI dashboards with row-level security so auditors can trace any number back to its source.
Yes. We have migrated financial data from DB2, COBOL-based mainframes, and AS/400 systems into Snowflake. We use CDC pipelines through Talend to capture changes in real time without impacting mainframe performance. The key is running both systems in parallel during transition so nothing breaks and auditors stay happy.
In our banking project, we took fraud detection from a 48-hour reporting lag to 90-second alerts. The architecture uses Talend CDC to capture transaction changes, Snowflake Streams and Tasks for real-time processing, and dbt models that apply fraud rules. The exact latency depends on your source systems and the complexity of your fraud rules, but sub-2-minute detection is achievable for most setups.
Data vault is a modeling methodology designed for auditability and flexibility. Unlike star schemas that overwrite history, data vault keeps a complete record of every change with timestamps and source tracking. For financial services, this means you can answer any auditor question about what data looked like at any point in time, trace any number back to its source system, and add new data sources without redesigning the warehouse.
Ready to Modernize Your Financial Data Platform?
Tell us about your regulatory requirements, source systems, and where the current platform is falling short. We will map out an audit-ready architecture with realistic timelines.
Schedule a Financial Data Assessment