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FinnStrat turns income, spending, and dreams into resilient financial plans, comparing strategies, stress-testing uncertainty, and showing what to change when life goes wrong.

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Inspiration

Financial planning often answers: “Can I afford this?” FinnStrat asks a more important question: “Can I survive this decision when life goes wrong?” The inspiration came from the gap between increasing access to digital finance and uneven financial-planning confidence. The 2019 NCFE survey found that only 27.18% of respondents crossed the minimum financial-literacy threshold. People have income and aspirations, but major decisions, buying a car, land, funding education, or starting a business, are often made without understanding how job loss, emergencies, market declines, or rising loan costs could affect them.

What it does

FinnStrat is an AI-powered personal wealth tracker and planner. Users enter their financial profile and a goal. FinnStrat generates multiple strategies, such as:

  • Saving and buying later
  • Investing while saving
  • Financing with a planned down payment
  • Using a hybrid reserve-first approach Each strategy is evaluated for:
  • Goal completion
  • Monthly contribution
  • Liquidity
  • Debt and EMI burden
  • Investment growth
  • Projected net worth
  • Maturity timeline
  • Stress-test performance Strategies are tested against scenarios such as income loss, market decline, emergencies, rising expenses, and interest-rate changes. FinnStrat identifies when a plan reaches its breaking point, explains why it failed, and helps users understand how changing the contribution, reserve, loan, or timeline could improve resilience. The platform also includes an AI strategy assistant that answers questions using the user’s goal, profile, generated strategies, and simulation results.

How we built it

FinnStrat was built using:

  • React and TypeScript for the frontend
  • FastAPI and Python for the backend
  • SQLite for scenario data and prototype persistence
  • REST APIs for communication between frontend and backend
  • Groq API for the strategy explanation chatbot
  • Deterministic financial simulation logic for projections
  • Responsive CSS for the dashboard and chat experience The engine calculates monthly cash flow, investments, debt balances, EMI payments, net worth, goal completion, and stress breaches. The strategy ranking system evaluates multiple dimensions instead of relying on one overall return. Users can optimize for balanced planning, resilience, speed, wealth, liquidity, or low debt. The chatbot runs through the backend, so the Groq API key remains private and is never exposed to the browser.

Challenges we ran into

One major challenge was building a financial model that was simple enough for a hackathon but still meaningful. We had to handle:

  • Different goal types, including cars, land, education, and businesses
  • Strategies with different maturity timelines
  • Inflation-adjusted goal costs
  • Loan amortization and changing interest rates
  • Existing debt and emergency reserves
  • Combined stress scenarios
  • Detecting when a strategy becomes unaffordable
  • Avoiding duplicate or identical strategies
  • Making complex financial outputs understandable in the UI Another challenge was presenting uncertainty honestly. A strategy with the highest projected wealth may also have low liquidity or fail under combined stress. The interface needed to communicate this trade-off clearly instead of presenting one option as universally correct. We also faced practical integration issues, including API configuration, unavailable language models, response formatting, and making long AI answers readable inside a compact chat panel. Accomplishments that we're proud of

We built a working end-to-end prototype in 24 hours with:

  • User signup and login using username and password
  • Persistent financial profiles
  • Saved goals and goal history
  • Multiple strategy generation
  • Strategy ranking based on user priorities
  • Affordability detection
  • Inflation-adjusted purchase costs
  • Normal and adverse scenario simulations
  • Stress-test breach detection
  • Recovery and breaking-point analysis
  • Interactive strategy comparison
  • Charts with normal-vs-stress overlays and breach markers
  • Strategy-specific AI questions
  • Responsive modern financial dashboard
  • Clear warnings when a recommendation is vulnerable under stress Most importantly, FinnStrat does not simply say which strategy has the highest return. It helps users understand which strategy they can sustain when circumstances change.

What we learned

We learned that financial planning is not just about maximizing wealth. It is about balancing:

  • Growth
  • Liquidity
  • Debt
  • Affordability
  • Flexibility
  • Recovery ability We also learned that transparency is essential when building financial tools. Users need to know which numbers are calculated, which assumptions are estimates, and where a strategy may fail. From a technical perspective, we learned how to combine deterministic simulation logic with AI explanation. The financial engine remains transparent and calculation-driven, while AI helps users understand the results in plain language.

What’s next for FinnStrat

Our next steps are:

  • Add real financial-account and transaction integrations
  • Improve personal spending categorization
  • Add early-warning notifications for liquidity and EMI risks
  • Support multiple existing loans with separate repayment schedules
  • Add more realistic investment and inflation assumptions
  • Improve recovery recommendations after a strategy breach
  • Introduce family and shared-goal planning
  • Add regional-language support
  • Validate pricing through user research
  • Launch a free core product with affordable premium planning at a proposed ₹19 per week
  • Explore transparent partnerships with financial wellness providers FinnStrat’s long-term goal is to make resilient financial planning accessible to everyday Indians. Plan for the best. Prepare for the worst.

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