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financialLLM

financialLLM is a domain-focused AI assistant for payments, fraud, risk, and financial product design, built to run locally using Ollama.

It’s designed for:

  • 🧠 Engineers & architects building payment gateways, wallets, and checkout flows

  • 💼 Risk, compliance & fraud teams working on transaction monitoring and policy design

  • 📊 FinTech product managers & founders exploring new financial products and flows

The goal is to provide a local, privacy-friendly copilot that understands:

  • Payment flows (card, APMs, wallets, payouts)
  • Fraud patterns and risk mitigation strategies
  • Compliance constraints around KYC / AML / transaction monitoring
  • Financial product, pricing, and experimentation ideas

Capabilities

  • 💳 Payments & Checkout Design

    * Explain how payment flows work (auth/capture, 3DS, redirects, webhooks).
    * Help design new checkout experiences and integration paths for merchants.
    
  • 🕵️ Fraud & Risk Reasoning

     * Brainstorm risk rules, signals, and features for fraud detection models.
     * Explain trade-offs between approval rate, chargebacks, and user friction.
    
  • 📑 Compliance & Policy Drafting

       * Draft policies, playbooks, and process docs for risk/compliance teams.
       * Summarize regulations at a conceptual level (KYC/AML-style workflows).
    
  • 📈 Product & Metrics Thinking

     * Help define success metrics (conversion, uplift, loss rate, etc.).
     * Suggest experiments or product changes to improve outcomes.
    

⚠️ Not legal or financial advice. Always validate outputs with your own legal, compliance, and finance experts.

Getting Started

Install via Ollama

ollama pull bharathreddyjanumpally/financialLLM

Run an interactive session:

ollama run bharathreddyjanumpally/financialLLM

Call it from your own tools:

curl http://localhost:11434/api/chat -d '{
  "model": "bharathreddyjanumpally/financialLLM",
  "messages": [
    { "role": "user", "content": "Design a risk-aware checkout flow for a digital goods marketplace." }
  ]
}'

Recommended System Prompt

You can embed something like this in your Modelfile or first message:

You are financialLLM, an AI assistant specialized in payments, financial products, fraud, and risk.

Your goals:
- Help design and reason about payment flows and checkout architectures.
- Help risk & fraud teams think about signals, rules, and model features.
- Help compliance and product teams draft policies, docs, and plans.

Constraints:
- Do NOT give personal investment advice or guarantee returns.
- Do NOT give legally binding compliance or regulatory advice.
- Focus on conceptual clarity, trade-offs, and practical best practices.
- When unsure, say so and explain what extra data or expertise is needed.

Example Prompts

1. Payment Flow Design

I’m building a payment gateway for online merchants. Explain a typical card payment flow (auth, capture, settlement) and suggest an API design with key endpoints. Include how to handle retries, idempotency, and webhooks.

2. Fraud & Risk Brainstorm

_I run a marketplace for digital collectibles. List 15 potential fraud patterns and risk signals I should monitor, grouped by:

 * user behavior
 * device/network
 * transaction patterns
 * merchant behavior

For each, suggest how I might measure it._

3. Policy / Process Draft

Draft a “Transaction Review & Manual Approval” runbook for a small risk team. Include: triage steps, what data to check, when to approve/decline, and when to escalate.

4. Product Metrics & Experiments

We want to increase our checkout conversion rate without blowing up fraud losses. Propose a set of experiments and levers we can pull, and explain the key metrics and trade-offs for each.

Prompting Tips

  • Be specific about context. Mention whether you’re a PSP, marketplace, SaaS platform, or merchant.

  • Describe your constraints. Regions, payment methods, target customers, or compliance boundaries.

  • Ask for formats. For example: “Give me a table of risk signals and business impact” or “Summarize this in bullet points for leadership.”

Limitations

📡 No live data access The model cannot see your production systems, bank accounts, or customer data. It only reasons over text you provide.

💰 Not investment advice It should not be used to pick stocks, crypto, or other investments.

⚖️ Not a substitute for lawyers or regulators Use it to draft and brainstorm, then confirm with legal/compliance professionals.