analyzing-embedded-finance
Evaluates embedded finance opportunities with distribution economics and regulatory framework analysis.
Skill by casemark
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/fdu-ins-analyzing-embedded-finance
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About
Use cases: finance
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/analyzing-embedded-finance
What's inside
- Skill name
analyzing-embedded-finance- Description
- Evaluates embedded finance opportunities with distribution economics and regulatory framework analysis. Use when analyzing embedded finance, evaluating BaaS models, or assessing embedded lending/insurance.
- License
- Apache-2.0
- Metadata
- author: casemark
- Instructions
- 77 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Analyzing Embedded Finance Evaluates embedded finance opportunities by mapping distribution economics, BaaS architecture dependencies, unit economics, and the regulatory framework governing non-bank financial product delivery. ## When To Use - Assessing a platform's viability for embedding payments, lending, insurance, or deposit products - Evaluating BaaS (Banking-as-a-Service) provider relationships and sponsor bank dependencies - Analyzing unit economics of embedded lending or embedded insurance distribution - Reviewing regulatory exposure when a non-bank entity originates or facilitates financial products - Comparing build-vs-buy-vs-partner strategies for financial product integration ## Inputs To Gather - **Platform profile**: User base size, transaction volume, vertical focus, existing monetization model - **Embedded product scope**: Which financial products are proposed (payments, lending, insurance, deposits, cards) - **BaaS / sponsor bank details**: Provider name, middleware stack, API architecture, contractual terms if available - **Revenue model**: Interchange splits, origination fees, premium share, interest margin allocation - **Regulatory filings or licenses**: State money transmitter licenses, lending licenses, insurance producer appointments, any pending applications [VERIFY jurisdiction-specific requirements] - **Competitive landscape**: Comparable embedded finance deployments in the same vertical ## Workflow 1. **Classify the embedded finance model** - Determine the product layer: payments (card issuing, pay-in/pay-out), lending (BNPL, line of credit, invoice financing), insurance (embedded warranty, parametric), or deposits/accounts - Identify the platform's role: distributor, co-lender, program manager, or referral agent - Map the value chain: platform → middleware/BaaS → sponsor bank/carrier → end user 2. **Analyze distribution economics** - Calculate customer acquisition cost advantage vs. standalone fintech or bank channel - Model per-user revenue: interchange basis points, loan origination fees, insurance premium share, or deposit spread - Estimate attach rates (what percentage of platform users adopt the embedded product) using vertical benchmarks — e.g., 5–15% for embedded lending in SaaS platforms, 10–30% for embedded insurance at checkout - Compute contribution margin after BaaS fees, compliance costs, and loss provisions 3. **Evaluate BaaS and infrastructure dependencies** - Assess sponsor bank concentration risk — single vs. multi-bank strategy - Review API reliability, uptime SLAs, and data-sharing constraints - Flag middleware vendor lock-in risks (proprietary ledger formats, non-portable KYC data) - Identify fallback options if the BaaS provider exits or loses its charter [VERIFY sponsor bank regulatory status] 4. **Map the regulatory framework** - Determine applicable regimes: state lending/money transmission licensing, OCC true lender doctrine, CFPB oversight, state insurance commissioner authority [VERIFY by state and product type] - Assess Madden v. Midland-style interest rate exportation risk for lending products - Review third-party risk management expectations (OCC 2013-29 / updated guidance, FDIC FIL-44-2008) imposed on the sponsor bank that flow down to the platform - Flag consumer compliance obligations: TILA/Reg Z, ECOA/Reg B, EFTA/Reg E, state UDAP statutes as applicable 5. **Stress-test the model** - Scenario-test revenue under reduced attach rates, higher credit losses, or regulatory fee caps - Evaluate impact of sponsor bank exit or BaaS provider repricing - Assess what happens if the platform loses its distribution scale (user churn, vertical contraction) 6. **Synthesize findings** - Score the opportunity across dimensions: distribution advantage, unit economics viability, regulatory feasibility, infrastructure resilience - Identify the top 2–3 risks and recommended mitigants - Provide a go/no-go or staged-rollout recommendation with conditions ## Output - **Embedded Finance Analysis Report** containing: - Executive summary with opportunity score and recommendation - Value chain diagram (platform → BaaS → sponsor bank/carrier → end user) - Unit economics model with sensitivity analysis - Regulatory exposure matrix by product and jurisdiction - BaaS dependency and concentration risk assessment - Risk register with severity ratings and mitigants - Recommended next steps (licensing, contract negotiation, pilot scope) ## Quality Checks - All revenue assumptions cite a source or are marked [VERIFY] - Regulatory analysis specifies the jurisdiction and product type — no blanket statements - Sponsor bank and BaaS provider details are current; charter status confirmed [VERIFY] - Unit economics model includes loss provisions and compliance cost line items, not just gross revenue - Attach rate assumptions are benchmarked against comparable vertical deployments - Third-party risk management obligations flowing from sponsor bank are explicitly addressed - Analysis distinguishes between current regulatory posture and pending rulemaking (e.g., proposed CFPB rules on data brokers, open banking mandates)
From FDU-INS/Insurance-Skills, Apache-2.0.
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Signals
- Stars
- 80
- Forks
- 18
- Open issues
- 1
- Last commit (this folder)
- May 18, 2026 (5 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- Repository
- github.com/FDU-INS/Insurance-Skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
analyzing-embedded-finance skill. Agent Mart. https://agentmart.dev/skills/fdu-ins-analyzing-embedded-finance (last updated 2026-10-24)