Datanalysis Credit Risk

🏢Official
by github · vlatest · Repository

Analyzes financial data to assess credit risk, providing insights for informed lending decisions and mitigating potential losses.

Install on your platform

We auto-selected Claude Code based on this skill’s supported platforms.

1

Run in terminal (recommended)

terminal
claude mcp add datanalysis-credit-risk npx -- -y @trustedskills/datanalysis-credit-risk
2

Or manually add to ~/.claude/settings.json

~/.claude/settings.json
{
  "mcpServers": {
    "datanalysis-credit-risk": {
      "command": "npx",
      "args": [
        "-y",
        "@trustedskills/datanalysis-credit-risk"
      ]
    }
  }
}

Requires Claude Code (claude CLI). Run claude --version to verify your install.

About This Skill

What it does

The datanalysis-credit-risk skill enables AI agents to analyze credit risk data, assess loan default probabilities, and generate insights based on financial metrics. It can process datasets containing borrower information, historical payment behavior, and economic indicators to identify patterns that may indicate potential defaults.

When to use it

  • Evaluating a new loan application by analyzing the applicant’s credit history and income stability.
  • Identifying high-risk customers in an existing portfolio for targeted risk mitigation strategies.
  • Generating reports on overall credit risk trends within a financial institution or market segment.

Key capabilities

  • Analyzes borrower data to predict default likelihood.
  • Processes historical payment behavior and economic indicators.
  • Generates insights and visualizations for decision-making.

Example prompts

  • "Analyze this dataset of loan applicants and identify those with the highest risk of default."
  • "Generate a report on credit risk trends based on the last five years of borrower data."
  • "What factors most strongly correlate with loan defaults in this dataset?"

Tips & gotchas

Ensure that your input data is clean, well-labeled, and includes relevant financial metrics for accurate analysis. The skill may require additional configuration or domain-specific tuning to achieve optimal results on complex datasets.

Tags

🛡️

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Details

Version
vlatest
License
Author
github
Installs
2.2k

🏢 Official

Published by the company or team that built the technology.