Marvis Risk Agent

MARVIS-Agent: all-purpose credit risk agent for model development, validation, data processing, feature engineering, and strategy workflows.

LLM Mart
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ai

It turns local data into governed analysis, models, strategies, and audit-ready deliverables.

CI status Latest release Python 3.11–3.13 MIT License

English · 中文

MARVIS-Agent wide desktop workbench with data, feature, risk, modeling, validation, and strategy workflows

One workbench for local risk analysis and development—from data to strategy and reports.


From a request to a reviewable result

MARVIS is a local-first, governed credit-risk Agent platform—not a chatbot wrapped around a collection of scripts.

Describe the business outcome in natural language. MARVIS asks for missing files and definitions, builds a reviewable plan, pauses at responsibility gates, runs deterministic tools, and returns real datasets, evidence, models, strategy code, and reports.

flowchart LR
    A["Describe the risk goal"] --> B["Agent clarifies inputs and definitions"]
    B --> C["Validated workflow plan"]
    C --> D{"Human confirmation<br/>where required"}
    D --> E["Deterministic tools execute"]
    E --> F["Evidence, artifacts, and reports"]
    F --> G["Review, adopt, and iterate"]

What the current V2 delivers

  • A complete seven-step strategy-development workflow: current and historical evidence, governed dual-population samples, univariate and model evidence, trees, Cross, scorecards, Voting, Strategy Pools, impact measurement, validation, code delivery, and four-format review reports.
  • A governed data-to-model workflow: ingest and join files, analyze and engineer features, train and compare multiple recipes, export PMML, score data, generate model reports, and hand the selected model and supporting evidence directly into model validation. PMML export is available for supported recipes.
  • Conversational risk analysis: MARVIS first asks what to analyze and which fields, units, dates, scenarios, and assumptions apply. It then runs the selected VTG-terminal/annualized-bad-rate or profitability calculation and delivers an audited Excel report. Standard Vintage and roll-rate are separate governed workflows with structured evidence and artifacts.

Why risk teams use MARVIS

Work in business language
Start with the decision you need, not a hand-built chain of scripts and notebooks.
Trust the numbers
KS, AUC, PSI, bad rate, approval rate, profit, and impact are calculated by deterministic platform code—not guessed by an LLM.
Keep data close
Files, task state, evidence, and outputs stay in a controlled local workspace by default.
Retain human responsibility
High-impact actions pause for confirmation, and key governed results carry lineage and audit evidence.

Agent mode and the Manual Workbench share the same validated workflows, tools, schemas, and deterministic calculation kernels.

From the project's README.

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