In modern finance, every second counts. Whether it’s detecting fraud, reporting risk exposure, or understanding customer behavior, data that’s hours old just won’t cut it. Yet many financial institutions still rely on batch ETL pipelines that delay insights and increase operational risk.
Real-time data pipelines offer a powerful alternative, especially when built on top of robust change data capture (CDC). With Estuary Flow, finance teams can stream operational data from legacy databases like Oracle, SQL Server, and PostgreSQL directly into modern analytics platforms like Snowflake and BigQuery — all in real time.
Here are three real-world use cases showing how Estuary Flow enables financial institutions to build fast, reliable, and future-ready data pipelines.
Use Case 1. Risk Reporting from Oracle to Snowflake
The Challenge:
Risk management teams often rely on daily or hourly batch jobs to populate their dashboards and compliance reports. This lag can mean exposure calculations are outdated by the time they’re reviewed, especially during market volatility.
The Solution:
With Estuary Flow, you can build a real-time pipeline that captures CDC from Oracle databases and streams it directly into Snowflake. Any insert, update, or delete in the transaction system is reflected in downstream dashboards within seconds.
Why It Works:
- Estuary Flow's Oracle connector uses log-based CDC for low-latency change capture
- Exactly-once delivery ensures your exposure calculations are accurate
- Schema evolution is automatically handled as new fields are added
Impact:
Regulatory dashboards, VaR models, and Basel compliance tools now reflect near real-time data, improving oversight and enabling faster reaction to emerging risk.
Use Case 2. Fraud Detection with SQL Server and BigQuery
The Challenge:
Fraud detection systems depend on timely access to transaction data. But if your SQL Server instance batches that data into BigQuery every hour, you’re detecting fraud after the fact rather than blocking it immediately.
The Solution:
Estuary Flow captures real-time changes from SQL Server and delivers them to BigQuery continuously. This enables fraud detection models to ingest fresh data in real time and trigger alerts within seconds.
Why It Works:
- Flow uses SQL Server CDC to track row-level changes as they happen
- BigQuery’s streaming ingestion allows immediate availability for queries or ML models
- Pipelines are built with no-code or declarative config — no fragile custom ETL scripts
Impact:
Fraud models catch threats faster. Customer protection improves. And your compliance team gains real-time visibility into suspicious transactions.
Use Case 3. Customer 360 from PostgreSQL and SaaS Apps into Snowflake
The Challenge:
Customer data is often fragmented — part of it in your PostgreSQL app database, other parts in CRM, payment, and support tools. Pulling it together with batch syncs creates delays, inconsistencies, and stale dashboards.
The Solution:
Estuary Flow can unify these data streams, capturing CDC from PostgreSQL, while ingesting API data from key SaaS tools and streaming all of it into Snowflake for real-time customer 360 dashboards.
Why It Works:
- PostgreSQL CDC is natively supported by Estuary Flow
- SaaS APIs (e.g., Salesforce, Stripe, Zendesk) can be ingested using HTTP connectors
- All data lands in Snowflake in real time, keeping dashboards fresh and actionable
Impact:
Customer success teams, marketing, and compliance all work from a live, unified view of every user — driving faster personalization, better service, and more accurate reporting.
The Bigger Picture
What do all three of these use cases have in common?
- Legacy systems (like Oracle or SQL Server) that are hard to replace
- Modern cloud warehouses (like Snowflake and BigQuery) that support real-time analytics
- A need to move faster without rewriting pipelines or maintaining fragile ETL jobs
Estuary Flow bridges that gap. It’s a real-time data operations platform that helps you build streaming pipelines using CDC and declarative config without sacrificing reliability, observability, or governance.
Get Started with Real-Time Finance Pipelines
Whether you’re looking to modernize your risk dashboards, improve fraud detection, or build a real-time customer 360, Estuary Flow can help you get there — without batch jobs or brittle code.
👉 Start building your first real-time pipeline in Flow today.
FAQs
1. How can financial teams enable real-time risk reporting?
2. How does real-time data help prevent fraud?
3. Can I build a real-time Customer 360 without replacing my existing tools?
4. Do I need to replace my current ETL stack to use Estuary Flow?
About the author
Dani is a data professional with a rich background in data engineering and real-time data platforms. At Estuary, Daniel focuses on promoting cutting-edge streaming solutions, helping to bridge the gap between technical innovation and developer adoption. With deep expertise in cloud-native and streaming technologies, Dani has successfully supported startups and enterprises in building robust data solutions.
