Tech Focus: Risk modeling, interactive data visualization, educational components
For Beginners: Focus on explaining 1−2 risk concepts with clear visuals
Create a tool that helps users understand the concept of investment risk through interactive visuals.
Investment Risk Visualizer
06 — 10
Core Features: Visualize index data, simulate past investment scenarios, highlight key concepts
Tech Focus: Data fetching/processing, interactive charting, time-series analysis
For Beginners: Use pre-packaged data and focus on the visualization experience
Build an interactive tool that demonstrates historical market performance and investment outcomes.
Market History Explorer
05 — 10
Core Features: Handle questions about investing basics, provide contextual explanations
Tech Focus: Natural language processing, LLM integration, conversational design
For Beginners: Start with a few predefined questions and expand from there
Create a conversational interface that answers basic money questions and provides personalized guidance.
AI Finance Assistant
04 — 10
Core Features: Expense categorization, interactive charts, "what-if" scenarios for investing
Tech Focus: Data visualization, categorization algorithms, financial projections
For Beginners: Start with manual data entry and focus on the visualization aspects
Build a visualization tool that helps users find money for investing within their current spending.
Budget-to-Invest Dashboard
03 — 10
Core Features: Cover 5−10 essential concepts like ETFs, compound interest, or dollar-cost averaging
Tech Focus: Knowledge representation, conversational UI, gamification elements
For Beginners: Use AI to generate explanations or build a simple quiz format
Create an interactive experience that explains investing basics in plain language.
Finance Concepts Demystifier
02 — 10
Core Features: Process transaction data (CSV upload), calculate spare change, visualize potential growth
Tech Focus: Data processing, basic financial modeling, interactive visualization
For Beginners: Start with a simple UI that calculates round-ups from manual entries
Build a tool that shows how small "round-ups" from everyday purchases can grow over time.
Round-Up Savings Simulator
01 — 10
Choose any track that interests you — or blend multiple concepts! These are starting points, not rigid requirements
Tracks
Deliverables
Working Prototype: Deployed web app or shareable link (no need for mobile apps)
Code Repository: GitHub repo with README.md explaining your approach
Demo: 2-minute video or live presentation showcasing key features
Key Dates & Deadlines
Stay on track with the official hackathon timeline. Don’t miss a moment — from registration to final results:
August 1
Registration Closes
Sunday
August 1
Kickoff on Discord (mandatory check-in)
Friday
(6:00 PM UTC)
August 1-4
Mix energy drinks with coffee to get it done
Saturday
August 4
Project polishing and final submission deadline
Sunday
(6:00 PM UTC)
August 24
Winners announced on our Discord server
Thursday
10pts
Presentation & Documentation
Clear explanation of problem, solution, and implementation
15pts
Financial Education Value
Accuracy and educational merit of financial information
20pts
AI/ML Innovation
Creative application of AI to simplify financial concepts
25pts
Technical Execution
Code quality, performance, effective use of available technologies
30pts
User Experience & Accessibility
User-friendly for non-finance experts and addresses real user needs
Evaluation Criteria
Total: 100 pts
Distinguished Judges
Our panel includes senior leaders from top tech companies — including a Director of Engineering at Google, ML Research Lead at Meta, Principal Product Manager at Amazon, VP of Engineering at Robinhood, and Director of Product at Wealthfront. Their expertise ensures a high standard of evaluation and industry relevance.
Lead Judges
Our core judging panel brings deep expertise from the world’s top tech companies and research institutions. These industry leaders will evaluate finalists, provide strategic feedback, and select the grand prize winners.
Machine Learning Scientist at Sony AI with expertise in generative models and 11 years of research in computer vision.
People's Choice Award Selected by public vote, awarded to the most loved project
Technical Execution For pushing boundaries with creative AI implementation
Best UI/UX Design For exceptional usability and aesthetic value
Special Awards
We're also offering three special category prizes — each with two $100 rewards and one $500 reward.
$200
This award honors strong coding fundamentals and successful project execution
Third Place
$300
Second Place
This prize celebrates strong development skills and effective implementation of creative solutions
$1,000
First Place
This award recognizes the team with the most impressive coding excellence and creative problem-solving
Prizes
From Cash Rewards to Career-Defining Opportunities
Additional Judges
Alongside the lead panel, our extended jury includes engineers, designers, and AI experts from around the globe — ensuring every project is reviewed with care and precision.
Japan
Hana Suzuki
AI Ethics Researcher at RIKEN with 10+ years in responsible AI, algorithmic transparency, and cross-cultural data policy.
LinkedIn
Germany
Thomas Becker
Lead Cloud Architect at SAP, specializing in scalable enterprise infrastructure and data security with 14 years in tech.
LinkedIn
United Arab Emirates
Fatima Al-Mansoori
Head of Product at Careem, with a background in mobility tech and over a decade of experience in platform growth and UX strategy.
LinkedIn
Brazil
Lucas Romero
Senior Data Scientist at Nubank with 11 years of experience in financial modeling, ML ops, and customer analytics.
LinkedIn
France
Chloe Martin
Innovation Strategist at Orange, focusing on digital sustainability, AI adoption in telecom, and user-centric product development.
LinkedIn
South Korea
Daniel Kim
Software Engineer at Samsung R&D, with deep experience in edge computing, IoT platforms, and smart device AI integration.
LinkedIn
Office Hours:
Scheduled sessions with judges and industry mentors
5 — 05
Technical Mentors:
On-demand support via Discord throughout the event
4 — 05
3 — 05
Simplified APIs for market data, sample transaction datasets
Data Sources:
2 — 05
GitHub repos with boilerplate code for different tech stacks
Starter Templates:
1 — 05
"Finance Basics for Developers" and "AI for Financial Applications"
Pre-hackathon Resources
Resources & Support
Vercel, Netlify, or GitHub Pages for frontend
Railway, Render, or Heroku for backend services
Any cloud database with a free tier
Hosting Options
04 — 04
OpenAI API, Anthropic Claude, or HuggingFace for natural language capabilities
Yahoo Finance API or Alpha Vantage for market data (free tiers available)
Sample datasets provided in the starter kit
AI & Data
03 — 04
Node.js/Express, Python/FastAPI, or any language you’re comfortable with
RESTful APIs or GraphQL for data exchange
Serverless functions (Vercel, Netlify) for quick deployment
Backend & APIs
02 — 04
React, Vue. js, Svelte, or plain HTML/CSS/JavaScript
Chart.js, D3. js, or Plotly for visualizations
Tailwind CSS, Material UI, or Bootstrap for styling
Frontend
01 — 04
We’ve designed this hackathon to be accessible with common web technologies. Here are some suggestions:
Recommended Technologies
Organized solely for social good [and fun] and designed by Hackathon Raptors. A non-profit community — UK [C.I.C] — 15 557 917.