Financial Forecasting Platform
Core forecasting modules and high-performance calculation engines for a UK fintech.
Overview
A financial planning and forecasting platform for a London-based fintech, where users model complex financial scenarios across large datasets. I designed the core forecasting modules and re-engineered the calculation engines that power them.
The problem
The forecasting engine was slow and error-prone on large models — recalculations blocked the UI, edge cases produced incorrect figures, and dense dashboards lagged. For a financial product, both speed and correctness are non-negotiable.
My role
As a frontend engineer (Angular + TypeScript), I rebuilt the calculation engines, hardened validation, and rebuilt the data-heavy views for performance, while collaborating in an Agile team with code reviews.
Approach & architecture
- Re-architected the calculation engine and moved heavy computation into Web Workers to keep the main thread responsive.
- Added lazy loading and code-splitting so users only load what they need.
- Used virtual scrolling and trackBy optimizations to render large tables/grids smoothly.
- Introduced client-side caching to avoid redundant recalculation.
- Strengthened validation and edge-case handling to reduce forecasting errors.
What I learned
Offloading computation to Web Workers and being deliberate about what renders (virtualization, memoization) can transform a sluggish data app into a snappy one — often a bigger win than backend tuning. In fintech, validation and edge-case handling are features, not afterthoughts.
Want to build something like this?
I'm open to full-stack and real-time projects. Let's talk.