Corp Finance Tools - Specialty & Regulatory

Perform specialty finance and regulatory calculations with 128-bit decimal precision.

7|1|Updated Feb 9, 2026
One-click install
npx skills add https://github.com/fall-development-rob/corp_finance --skill corp-finance-tools-specialty-regulatory
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: Corp Finance Tools - Specialty & Regulatory
Source: https://github.com/fall-development-rob/corp_finance/tree/main/.claude/skills/corp-finance-tools-regulatory
Command: npx skills add https://github.com/fall-development-rob/corp_finance --skill corp-finance-tools-specialty-regulatory

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Institutional teams and analysts face fragmented, error-prone spreadsheets and inconsistent models when performing specialty finance, regulatory, and compliance calculations across private credit, insurance, FP&A, fund structuring, and bank/regulatory reporting. This Skill centralises deterministic, production-grade MCP tools that deliver repeatable valuations, regulatory capital metrics, reserve estimates, and structured outputs with 128-bit decimal precision to remove ambiguity and auditability gaps.

Core Features & Use Cases

  • Comprehensive toolset: 94 MCP tools spanning unitranche/direct lending pricing, loss reserving, Solvency II SCR, Basel capital, CECL provisioning, transfer pricing, tax treaty optimisation, fund structuring, carbon markets, and private wealth analytics.
  • Structured, auditable outputs: Every tool returns JSON with result, methodology, assumptions, warnings, and metadata to support audit trails and downstream automation.
  • Chaining workflows: Built workflows for multi-step analyses (e.g., price unitranche -> model syndication -> produce investor returns; estimate IBNR -> compute SCR -> produce regulatory report).
  • Real-world example: Run unitranche_pricing to compute FOLO economics, feed the borrower leverage metrics into direct_lending for amortisation and IRR, then produce a syndication_analysis for arranger economics.

Quick Start

Use the corp-finance specialty tools to run unitranche_pricing on the provided loan terms and return the structured JSON output including methodology, assumptions, and warnings.

Frequently Asked Questions about Corp Finance Tools - Specialty & Regulatory

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I calculate Solvency II SCR and Basel regulatory capital without spreadsheet errors?

Specialty finance calculations for Solvency II SCR and Basel regulatory capital use deterministic MCP tools that return structured JSON with methodology and assumptions, replacing fragmented spreadsheets with auditable, 128-bit decimal precision outputs.

Can I model unitranche pricing and direct lending amortisation in a single workflow?

Yes, built chaining workflows allow you to run unitranche pricing to compute FOLO economics, feed borrower leverage metrics into direct lending for amortisation and IRR, then produce a syndication analysis for arranger economics.

What is the best way to structure private credit fund models and ESG compliance reporting?

Private credit fund structuring and ESG compliance reporting are handled by 94 centralized MCP tools covering transfer pricing, tax treaty optimisation, carbon markets, and private wealth analytics, delivering structured outputs with audit trails.

Does this approach support CECL provisioning and insurance loss reserving with full auditability?

CECL provisioning and insurance loss reserving calculations return structured JSON containing results, methodology, assumptions, warnings, and metadata, ensuring full auditability and supporting downstream automation for institutional teams.

How do I ensure 128-bit decimal precision for monetary math across FP&A and bank analytics?

All monetary math across FP&A and bank analytics uses 128-bit decimal precision within the MCP tools to remove ambiguity and auditability gaps, returning structured JSON outputs for repeatable valuations and reserve estimates.

When should I use a structured JSON MCP tool over traditional spreadsheets for specialty finance calculations?

Use structured JSON MCP tools over traditional spreadsheets when performing multi-step specialty finance analyses like estimating IBNR, computing SCR, and producing regulatory reports, ensuring deterministic results without error-prone manual modeling.