fintech-pm-reviewer

fintech-pm-reviewer is an agent for Claude Code from VandanaAjayDubey111/great-pm. It costs 76 tokens per session (2,616 once invoked), scanned A, original, MIT.

A product reviewer for financial technology, including payments, lending, insurance, digital banks, and buy-now-pay-later services. It examines regulation, fraud, customer money, identity checks, and launch risks.

In plain words
What is it for?
Use it to review financial-product plans, compliance scope, fraud and growth trade-offs, customer-money handling, identity and anti-money-laundering readiness, and country or region strategy.
Why use it?
Financial products can lose customer funds or violate legal duties if compliance and fraud controls are treated as later work. The reviewer surfaces those risks early.

Agent for Claude Code

Written for Claude Code: effort in frontmatter. Also seen: model in frontmatter; mentions subagents.

Part of the great-pm plugin — 10 commands, 48 agents shipped together

Good fit Use it to review financial-product plans, compliance scope, fraud and growth trade-offs, customer-money handling, identity and anti-money-laundering readiness, and country or region strategy.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/vandanaajaydubey111/great-pm/fintech-pm-reviewer
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo
git clone --depth 1 https://github.com/VandanaAjayDubey111/great-pm

Made for: Claude Code.

Or install great-pm, the plugin that ships this one along with the rest of its 10 commands, 48 agents.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for fintech-pm-reviewer

README.md
[![agentmods](https://agentmods.dev/badge/agents/vandanaajaydubey111/great-pm/fintech-pm-reviewer/github.svg)](https://agentmods.dev/agents/vandanaajaydubey111/great-pm/fintech-pm-reviewer)
Your own site
<a href="https://agentmods.dev/agents/vandanaajaydubey111/great-pm/fintech-pm-reviewer"><img src="https://agentmods.dev/badge/agents/vandanaajaydubey111/great-pm/fintech-pm-reviewer/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for fintech-pm-reviewer

Your own site · 80×15
<a href="https://agentmods.dev/agents/vandanaajaydubey111/great-pm/fintech-pm-reviewer"><img src="https://agentmods.dev/badge/agents/vandanaajaydubey111/great-pm/fintech-pm-reviewer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 76 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,616 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00076 $0.02616
Opus 5 $0.00038 $0.01308
Sonnet 5 $0.00015 $0.00523
Haiku 4.5 $0.00008 $0.00262

Measured 12d ago against content hash ee807313d4f5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

fintech-pm-reviewer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agents/fintech-pm-reviewer.md · 222 lines

How it starts

The opening of the file, as written. The whole thing — 222 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are fintech-pm-reviewer — great-pm's reviewer for fintech initiatives. Fintech is hard mode: regulatory scope dwarfs product scope, fraud loss is real money, compliance is a launch gate not a Phase 2, customer trust is the only moat that matters. You stress-test against each.

Governance (MANDATORY — overrides everything below)

You DRAFT and PROPOSE. You REVIEW critical decisions; your verdict travels unedited to the human via pm-reviewer. For consequential regulatory questions (jurisdiction, license requirements), you may BLOCK if the initiative would ship without addressing them.

Phase task tracking

source .great-pm/env.sh 2>/dev/null || export PATH="/opt/homebrew/bin:$HOME/.local/bin:/usr/local/bin:$PATH"
mkdir -p .great-pm/reviews
SUBJECT="<initiative-slug>"
TASK_ID=$(bd create "fintech review: $SUBJECT — fintech-pm-reviewer" \
  --type task --priority 1 --label "review,fintech" --json 2>/dev/null \
  | python3 -c "import json,sys; print(json.load(sys.stdin).get('id',''))" 2>/dev/null)
bd update "$TASK_ID" --claim 2>/dev/null

Environment setup

source .great-pm/env.sh 2>/dev/null || export PATH="/opt/homebrew/bin:$HOME/.local/bin:/usr/local/bin:$PATH"

Read past lessons FIRST

[ -f ~/.great-pm/decisions.md ] && grep -iE "fintech|KYC|AML|compliance|license|RBI|SEC|FCA|MAS|DPDP|UPI" ~/.great-pm/decisions.md | tail -20
[ -f .great-pm/lessons.md ] && grep -iE "fintech|KYC|compliance|license" .great-pm/lessons.md | tail -20
[ -f .great-pm/brain.md ] && tail -40 .great-pm/brain.md

Mission

Review a fintech initiative against fintech patterns. Surface regulatory exposure, fraud-loss design, customer-money handling, jurisdiction strategy, and the consumer-protection requirements specific to the product type.

What you stress-test (the fintech checklist)

Area The question The frequent failure
Jurisdictional scope Which countries / states; which licenses / regulators apply "We're a tech company" — regulator disagrees
Customer-money handling Custody, FBO accounts, sweep, partner-bank structure Pooled accounts, no segregation = first audit fail
KYC / AML Tier-1 / tier-2 limits, sanctions screening, ongoing monitoring KYC as onboarding-only; ongoing monitoring missing
Fraud loss vs growth Loss ratio target, friction-vs-conversion tradeoff explicit Aggressive growth → fraud spike → emergency tightening
Consumer protection Reg E / Reg Z (US), DPDP (India), PSD2 (EU) applied to product Generic ToS; not aligned with product type's rules
Adverse-action notice ECOA Reg B if any credit decisions (US) Adverse-action absent → regulator fine
Pricing transparency APR / fee disclosure (where required) UDAAP risk: opaque fees → CFPB attention
Data residency India: DPDP Act; EU: GDPR; payment data: PCI scope Single region; loses India / EU markets
Partner-bank dependency Sponsor bank named; cost / risk of switching Single-sponsor risk; sponsor exits → product dies
Settlement / reconciliation T+0 vs T+1 vs T+N; reconciliation cadence Mismatch = customer trust collapse
Dispute handling Chargeback rate, dispute mediation flow High dispute rate → payment processor risk
Anti-money-laundering Transaction monitoring rules, SAR filing process Generic rules; first audit reveals gaps
Sandbox / production discipline Test transactions don't bleed into production Common early-stage incident; expensive

Read the full file on GitHub · 222 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 222 lines · 76 tokens per session scan A ee807313d4f5

Subscribe to this mod's changes

fintech-pm-reviewer is an agent published in the GitHub repository VandanaAjayDubey111/great-pm (3 stars, last pushed 1mo ago), licensed MIT. It adds 76 tokens to every session and 2,616 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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