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Finance & Banking5 monthsCapitalView

Real-Time FinTech Analytics Dashboard

Built a real-time financial analytics dashboard processing 10M+ transactions daily with interactive charts, risk alerts, and regulatory reporting.

10M+

Daily Transactions

80%↑

Detection Speed

99.99%

Availability

01Real-Time FinTech Analytics Dashboard: The Challenge

CapitalView's analysts relied on overnight batch reports and Excel models to track portfolio performance. By the time reports were ready, market conditions had already shifted. They needed real-time visibility into transaction flows, risk exposure, and regulatory compliance metrics.

02Real-Time FinTech Analytics Dashboard: The Solution

We built a streaming analytics platform using Apache Kafka for real-time data ingestion, time-series databases for historical analysis, and a React dashboard with interactive D3.js visualizations. The system includes automated risk alerts, customizable report generation, and SOC 2 compliance controls.

03Real-Time FinTech Analytics Dashboard: The Results

Decision latency dropped from 24 hours to under 5 minutes. Risk incidents detected 80% faster. The platform processes 10M+ daily transactions with 99.99% availability and supports 200+ concurrent analysts.

Technology Stack

ReactKafkaTimescaleDBD3.jsAWSDocker

Services Provided

Custom Software DevelopmentEnterprise Systems Development

Outcomes that mattered

The numbers above are the headline. Below is what they mean for the finance & banking operations team — what they stopped doing, what they started doing, and what changed for end customers.

10M+

Daily Transactions

Headline metric — measured against the pre-launch baseline.

80%↑

Detection Speed

Captured 90 days post-launch with the same methodology used during discovery.

99.99%

Availability

Operational impact reported by the client team in their post-launch review.

Why this tech stack

We pick technology based on the production load, the integration footprint and the long-term maintenance reality — not the latest framework on Hacker News. For Real-Time FinTech Analytics Dashboard, the stack we chose:

React

Production-grade choice for finance & banking workloads at this scale.

Kafka

Production-grade choice for finance & banking workloads at this scale.

TimescaleDB

Production-grade choice for finance & banking workloads at this scale.

D3.js

Production-grade choice for finance & banking workloads at this scale.

AWS

Production-grade choice for finance & banking workloads at this scale.

Docker

Production-grade choice for finance & banking workloads at this scale.

Common questions about this case

How long did the Real-Time FinTech Analytics Dashboard build take?+

5 months. We worked with short, regular updates and a working demo at each check-in, so CapitalView saw progress continuously.

What technology did Timeline Digital use to build Real-Time FinTech Analytics Dashboard?+

React, Kafka, TimescaleDB, D3.js, AWS, Docker. We pick the stack based on the production load, integration requirements and the team's long-term maintenance capacity — not the latest framework on Hacker News.

What industry was Real-Time FinTech Analytics Dashboard built for?+

Finance & Banking. The patterns we used here transfer to similar businesses with comparable scale and regulatory requirements. Reach out if you operate in this space and want a similar build.

Can Timeline Digital build something similar for our team?+

Yes. We start every engagement with a paid discovery phase that produces architecture, a clear written scope and a proposal, and we agree the full scope up front. Mutual NDA signed on day one, full IP assignment, no agency overhead. Cost depends on scope, features and integrations — book a free call and we will walk you through it.

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