SettleTrack

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  Dashboard Page

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  Settlement Page1

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  Settlement Page2

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  Risk Analysis Page

SettleTrack — Project Story Inspiration

Trade and loan transactions are executed instantly, but settlement typically takes several days. This delay creates confusion, operational risk, and reduced transparency for traders, lenders, auditors, and regulators. Post-trade processes often rely on delayed and fragmented records, making it difficult to clearly understand the status of a trade after execution.

SettleTrack was developed to address this gap by providing real-time visibility into post-trade settlement, allowing users to track the progress of a trade without relying on manual reconciliation or delayed confirmations.

How We Built the Project

SettleTrack follows a modular system architecture in which each component has a clearly defined role. The frontend presents trade information, settlement status, and risk indicators through a unified dashboard. The backend receives trade data and coordinates system workflows. A blockchain layer securely stores settlement records in an immutable and audit-friendly manner. A machine learning layer analyzes trade patterns to detect settlement risk and abnormal behavior.

Trade data is currently simulated, but the platform is designed to integrate with real broker, exchange, or clearing APIs.

The settlement workflow is:

Trade Execution → Settlement Processing → Final Settlement

SettleTrack tracks each stage of this workflow in real time to improve clarity and trust.

Challenges We Faced

Designing a realistic settlement flow without access to live exchange or clearinghouse data

Maintaining a clear separation of responsibilities between backend services, blockchain storage, and machine learning analysis

Simplifying complex financial settlement processes for better user understanding

Balancing technical depth with simplicity to ensure scalability and commercial viability

What We Learned

Settlement is one of the most critical yet often overlooked components of financial infrastructure. Transparency reduces disputes and operational risk more effectively than speed alone. Blockchain is most valuable when used for immutability and auditability, while machine learning adds value when applied to early risk detection.

What’s Next for SettleTrack

Integration with real broker and clearing APIs

Support for loan trading and secondary markets

Advanced risk detection using larger historical datasets

Regulatory and compliance reporting features

Built With

• ethereum
• fastapi
• node.js
• numpy
• pandas
• postgresql
• python
• react
• redis
• scikit-learn
• solidity
• tailwind
• web3
• xgboost