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This project uses decision tree logic to generate insights, identify proxy security IDs using nearest neighbor methods, and streamline risk analysis for financial datasets.

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Bond Risk Analyzer

Overview

The Bond Risk Analyzer automates the review of bond-related exceptions, focusing on resolving BondCalc (Risk Calculation System) failures and validating risk analytics. It uses decision tree logic to streamline exception handling and improve efficiency.

Key Features

Automated Exception Handling: Identifies and resolves bond-related issues, including BondCalc failures. Proxy CUSIP (Security Identifier) Generation: Dynamically identifies proxy CUSIPs based on bond attributes (e.g., security type, coupon type). Risk Validation: Checks attributes like Static Yield, Model OAD, and YTM for consistency. Data Processing: Outputs structured summaries of exceptions, including root cause analysis.

Technical Details

Language: Python Libraries: pandas, datetime Input: Excel file (test.xlsx) with bond exception details. Output: Summary of exceptions with statuses, root causes, and proxy CUSIPs.

Usage

Clone Repository: git clone https://github.com/huacenxu/bond-risk-analyzer.git cd bond-risk-analyzer

Run Script: Place test.xlsx in the data/ folder and execute:

Sample Input Data

CUSIP AladdinClient NewRiskClient StaticYield ModelOAD YTM ExceptionDescription
ABCD1234 ClientA Risk001 1.5 0.3 0.5 BondCalc Failure

Output: Displays a DataFrame of processed exceptions. Results can be exported as a CSV.

Next Steps:

Add advanced logic for handling additional bond attributes. Integrate predictive analytics for exception handling. Connect with upstream systems for root cause analysis.

About

This project uses decision tree logic to generate insights, identify proxy security IDs using nearest neighbor methods, and streamline risk analysis for financial datasets.

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