Our FinTech Expertise

GigaProc - Customized Framework

Greenmedsoft has developed a distributed computational framework called GigaProc.
It can be used for high throughput and low latency data processing.
It provides a means to capture high volume of data, process the data across number of distributed nodes parallelly and persist the data for analysis and reporting.

High Throughput Technology Stack

Our expertise and experience in high throughput distributed platform uses a wide range technologies and systems.

Our Fintech References

Accounting & Taxation Software (SEAMLESS) for a North American Client

Developed the accounting and taxation software.
Built this to scale up with their exponential customer growth.

Outcome:

Customized software solution for fund services efficiency.
Process Optimization through analysis of the existing service workflows, identifying inefficiencies, streamlined service delivery and improved customer experience.
Ensured Data Security Measures by way of robust security measures to protect user information and ensure compliance with data protection regulations.

Bond Trading for a North American Client

Designed and developed a rapidly scalable database structure for management and display of Trading rules, Multi Risk management, Dealer List and ranks, Blotter information, Market Depth, Transactions, Outstanding Positions and Daily P&L and Analytics.
Algorithms for Data anomalies and Cleansing, Trade identification procedure and initiation, Trade exit, Individual Risk Management, Portfolio Management.
Extension algorithms for opportunities to correlate corporate actions, systemic reactions and fundamental data to improve the win-rate, position sizing and create intelligent feedback loops to refine the system.

Outcome:

Provided an architecture which is scalable and performant to handle high volumes both in real time and batch loads.
Capture, process and store structured and unstructured data from variety of reference data sources in real time.
Most of the business logic, starting from data capture/processing to algos, risk management and trade signaling were based on “business rules”. Hence our implementation externalized rules management, to accommodate rule changes on demand, at all possible layers to minimize code changes and dependency on tech teams.

Design of High Throughput and Fault-Tolerant Fraud Detection System for an Indian Client

Designed and developed an ecosystem technology platform to detect fraud in financial transactions while meeting the performance demands of the client.

Outcome:

Helped accelerate business growth, streamline operations, provide risk-adjusted insights, all while staying compliant with regulatory requirements.

OMS & Retail Fracker for Fractional Trading & Flexible trading options for a North American Client

Developed a trading application that was built on hydra framework and a program called Fracker for dealing with fractional shares that allows the customers to own fractional shares and purchase securities in dollar amounts.
Developed and launched ultra-resilient, massive scale, and ultra-low latency algorithmic and high frequency trading systems.
Designed & Implemented a new front to back institutional and retail trading systems, post trade systems, informatics and data processing platform, development environment, operational systems for a hyper growth stage FinTech firm while tactically enhance current state environments and creating an active-active migration strategy
Designed and implemented new ultra-low latency order management and proprietary model engines using both hybrid public clouds for throughput-oriented workloads and bare metal colocation for ULL performance, fault tolerant trading application with deterministic performance (we completed this use case for multiple institutional brokerage firms)
Designed distributed, scale-out architecture to support entire post-trade eco-system with real-time booking, P&L, margin calculations using streaming and aggregation technologies performance (we completed this use case for several firms)
Designed & Implemented equity ticker data time-series data warehouse solution supporting regulatory and compliance reporting.
Designed & Implemented technologies to support data warehouse solution for BI reporting and partner data distribution with S3/Parquet data lakes and data aggregation/federation query capabilities.
Instrumental in building an onshore/offshore TechOps/DevOps model for this growth stage FinTech and brokerage house.
Instrumental in building a SDLC process designed with a “shift-left” model.
Built an end-to-end architecture for a fully automated QA/QC system encompassing code quality, code coverage checks across all stages of the SDLC process in a true agile environment with global development and business teams.

Revamp of legacy technology & assessment in brokerage/data services for a North American Client

We have developed a spring boot application that retrieves data from specific tables in MySQL and transfers it to corresponding Dynamo Our solution incorporates robust checks to validate the successful and accurate transfer of data between the two databases ensuring data integrity throughout the process.

Outcome:

Data migration through multiple databases with effective checks on Data security and transfer.

A Real Estate Investment Portal (Current Engagement)for a North American Client

Developing a real-estate investment portal for the investors/placement agents for our client, a high touch investment advisory and management firm focused on a range of strategies across multiple asset classes and real estate sectors on behalf of its network of institutional and family office investors.
We have divided the real estate assets into several REITs and tokenized the for the sake of portability and enabled exchange of tokenized assets utilizing Solana Ecosystem. This allows for individual investors to become fractional owners along the lifecycle of the investment.

Envisaged Outcome:

Our solution is designed to enhance the real estate /property investors’ ability to analyze, transact, monitor, and make informed investment decisions and also links their investments to the digital economy.