"China Phone Number Risk Control Systems and Fraud Prevention" matching MCP servers:

Exposes account risk status from a fraud detection pipeline, returning risk scores, flagged transaction history, and LLM-generated explanations via the get_account_risk_status tool.

Enables AI agents to investigate synthetic fraud cases by pulling transactions, running deterministic rules evaluations, pivoting across devices, and recording auditable case files with provenance.

MCP server for k-prevention, enabling AI assistants to access decrypted financial data, run Monte Carlo simulations, optimize scenarios, and manage scenarios locally while preserving end-to-end encryption.

AI-powered fraud detection and investigation platform that exposes tools for querying, scoring, and investigating financial applications using LangGraph, MLflow, and SQLite in-memory.

MCP server exposing Interactive Brokers' portfolio risk analysis, including model greeks, implied volatility surface, what-if margin, and a local stress engine for P&L curve analysis.

Analyzes Korean DART (Financial Supervisory Service) public disclosures to detect unfair trading risk signals, enabling users to query and evaluate corporate risk through natural language.

Provides live China PBOC Loan Prime Rate (LPR) data for 1-year and 5-year benchmark lending rates, including historical monthly announcements and the latest print with reference dates. Enables querying current and recent LPR rates via MCP tools.

Enables querying China-to-Western biotech licensing deals, NMPA drug approvals and policy updates, and CSRC securities penalties, all extracted from public SEC, HKEX, and government filings without an API key.

Provides keyless access to HKEX and CNINFO exchange disclosure feeds, enabling search and retrieval of Chinese biotech licensing deals and Hong Kong/STAR IPO financing filings.

Detects financial fraud and AI agent transaction risks using machine learning, behavioral biometrics, network graph analysis, and agent-to-agent protection.

Stablecoin risk intelligence MCP — 13 tools covering CCI concentration risk, reserve drift, depeg probability, and risk scoring for RLUSD, USDT, USDC, EURC. Real-time monitoring with SAFE/CAUTION/AVOID verdicts. MiCA Art.25/35 relevant.

Enables querying China's official foreign exchange reserves, balance of payments, and external debt data from SAFE's English-language data pages, including publication-date metadata for freshness.

Enables users to query financial data and compute credit-risk metrics like Altman Z-Score and loan default probability through natural language.

Enables AI agents to assess credit default risk, run what-if scenarios, and evaluate portfolios through natural language, backed by an explainable XGBoost model.

An MCP server that enables AI-powered fraud detection on financial transactions using rule-based and statistical analysis tools, with sample data and Gradio dashboard.

A natural-language interface to a credit risk database, with SQL guardrails that enforce read-only, allowlisted access to tables and columns.

Enables Claude clients to score borrower default risk, explain predictions with SHAP, compare applicants, and inspect model metadata through natural conversation. Serves a trained XGBoost model locally over stdio or remotely over HTTP with API-key authentication, keeping confidence transparent by reporting which inputs fell back to training-set defaults.

Provides an LLM agent with extreme value statistics tools for tail risk analysis, including peaks-over-threshold GPD fitting, VaR and Expected Shortfall estimation, return levels, threshold-stability diagnostics, and out-of-sample VaR backtesting.

Enables mortgage risk assessment and underwriting by calculating DTI, LTV, credit risk, income stability, and asset sufficiency, and by aggregating these factors into a loan recommendation with conditions and compensating factors.

Provides AI agents with quantitative risk tools such as VaR, expected shortfall, GARCH volatility, backtesting, stress testing, tail risk analysis, and credit scoring using synthetic or user-supplied data.