FinGrid App | FinTech Infrastructure Platform

About Client

Our client is a fast-growing fintech startup believed in democratizing financial analysis for retail investors. The client aimed to help small investors with real-time, advanced investment insights. However, their mission faced hurdles due to the lack of a strong online investment consulting platform. As an emerging financial services player, they wanted to simplify the complexities of financial data and make it easy to understand for investors.

Objectives

The core objective was to build a secure and scalable web application as the client lacked a centralized and scalable system that could integrate datasets related to historical equities data, market indexes, and macroeconomic indicators with customizable analytics models. Other objectives were to enable users to visualize stock trends, run custom analytics, and ensure that the application supports a growing user base.

Problem Statement

The client required a robust web-based solution that could process vast volumes of time-sensitive financial data while supporting complex models and data analytics. Existing tools, which client was using, lacked the necessary customization and scalability. The client required a tailored solution that can interpret historical market data and deliver real-time insights to retail investors.

Challenges for the Client

It was difficult for the client to scale solutions according to the increasing number of users. Moreover, it was challenging to get data throughput due to the lack of a cloud-native architecture. The client also struggled with performance bottlenecks caused by monolithic code structures. These shortcomings restrict their ability to deploy frequent updates and support real-time analytics.

As massive and time-sensitive financial data is constantly updated, it is cumbersome to process and visualize it effectively. Other difficulties were running custom scripts and financial models on the move while handling sensitive user data and deploying frequent updates.

Our Solutions

Our experienced Python professionals addressed all the challenges by developing a user-friendly web application. Some of its features include

Interactive Dashboard

We developed dynamic and user-friendly dashboards using React.js. The dashboard utilized WebSocket connections for showing live updates and facilitating users to view real-time changes without refreshing the page manually. Our developers created custom components.

Cloud Deployment

We deployed the web application on AWS infrastructure to ensure reliability, performance, and resilience. The cloud-based architecture included EC2 instances for compute, MySQL for database hosting, and S3 for static file storage and backups.

Robust Security Architecture

We ensured the security of all API communications using HTTPS with SSL/TLS encryption. Our team used JWT (JSON Web Tokens) for authentication and user management. We used rate limiting and input validation for implementing API gateways.

Real-Time Data Integration

Our web developers integrated the application with third-party financial APIs like IEX Cloud using asynchronous Python scripts. This ensured non-blocking data fetches and allowed concurrent API calls. Data was stored in MySQL tables for rapid retrieval.

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Technology Stack

Python

React JS

AWS

MySQL

Outcome

The client got 80 percent quicker data processing than initial prototypes with reduced latency and improved computational efficiency in the final application. The application users spend an average of 25 percent more time on the app because of the intuiitve dashboards and customizable analytics tools. The app successfully handled a 5x increase in user load with zero downtime or compromising on performance. The client was happy to get this web application witnessing significant increase in traffic in the first 3 months of launching.