November 17, 2025

Best Hackathon Project Ideas for Finance [With Source Code]

What kind of project can make you stand out in a finance hackathon where numbers, data, and accuracy matter the most? Picking the right idea often decides how strong your final presentation will be.

Finance projects work best when they solve real problems like budgeting, fraud detection, saving, or investment planning. Exploring the right finance hackathon project ideas helps you build something useful, impressive, and achievable within the event time.

This guide brings simple and practical ideas that you can build fast and showcase with confidence.

Top Finance Hackathon Projects – Overview

Here’s an overview of the 10 best Finance hackathon project ideas:

S.No.	Project Title	Complexity	Estimated Time	Source Code
1	AI Based Expense Classifier	Easy	6–8 hours	Get Started
2	Personal Budget Planner App	Easy	7–10 hours	Get Started
3	Loan Eligibility Predictor	Medium	10–12 hours	Get Started
4	Real Time Stock Sentiment Analyzer	Medium	12–14 hours	Get Started
5	Fraud Transaction Detector	Medium	12–16 hours	Get Started
6	Crypto Price Tracker with Alerts	Medium	15–18 hours	Get Started
7	Smart Tax Calculator	Medium	18–22 hours	Get Started
8	Investment Portfolio Rebalancer	Hard	20–26 hours	Get Started
9	Credit Score Simulator	Hard	22–28 hours	Get Started
10	AI-Powered Financial Advisor	Hard	28–36 hours	Get Started

Key Focus Areas in Finance Hackathons

Finance hackathons usually reward ideas that make financial systems simpler, safer, and more efficient for everyday users. Here are the main areas teams are expected to focus on:

Personal Finance Management: Solutions that help users track expenses, savings, and budgets with clarity.
Investment Insights: Tools that simplify market analysis and guide users with meaningful recommendations.
Fraud Detection: Systems that identify unusual transactions and protect users from financial risks.
Financial Education: Apps that help beginners understand money management and make informed decisions.
Transaction Automation: Faster and smarter ways to handle payments and routine financial tasks.
Risk Assessment: Models that evaluate creditworthiness and financial stability for users or businesses

10 Best Finance Hackathon Project Ideas

Choosing a good idea is the first step toward creating a strong project at any finance event.

To help you get started, here are the best finance hackathon project ideas that are practical to build, easy to pitch, and valuable in real-world financial scenarios.

1. AI-Based Expense Classifier

A smart tool that automatically categorises user expenses by analysing descriptions, amounts, and spending patterns. It helps users understand where their money goes without manually sorting transactions.

Duration: 6–8 hours

Difficulty Level: Easy

Tech Stack Required: Python, Flask, React, Scikit Learn

Implementation Steps:

Build expense upload module
Train a simple classifier model
Display category-wise charts
Add history view

Key Features:

Auto categorisation
Spending insights
Visual analytics

Learnings:

Basics of ML classification
Data cleaning
Simple finance dashboards

Real-World Application:

Personal budgeting
Bank expense analytics

Get Started

2. Personal Budget Planner App

A simple budgeting app that tracks income, savings, and monthly spending through clear dashboards. It helps users plan their finances and stay within limits using alerts and insights.

Duration: 7–10 hours

Difficulty Level: Easy

Tech Stack Required: React Native, Firebase

Implementation Steps:

Add income and expense forms
Create monthly budget logic
Build analytics screen
Add low budget alerts

Key Features:

Budget limit alerts
Savings suggestions
Monthly reports
Learnings:
Data structuring
Cloud integration
UI planning for finance

Real-World Application:

Student budgeting
Salary planning

Get Started

3. Loan Eligibility Predictor

A model that predicts whether a user is likely to get a loan based on income, credit behaviour, and financial history. It gives fair and fast loan assessment insights.

Duration: 10–12 hours

Difficulty Level: Medium

Tech Stack Required: Python, Flask, Logistic Regression, HTML CSS

Implementation Steps:

Prepare dataset
Train prediction model
Build form for user inputs
Show approval probability

Key Features:

Instant eligibility score
Simple UI
ML-powered decisions

Learnings:

ML training workflow
Working with financial data
Building web ML apps

Real-World Application:

Bank pre-screening
Online loan platforms

Get Started

4. Real-Time Stock Sentiment Analyzer

An app that pulls market news and social media posts to analyse investor sentiment for selected stocks. Users receive a quick view of positive or negative trends.

Duration: 12–14 hours

Difficulty Level: Medium

Tech Stack Required: Python, NLP, Tweepy, Flask

Implementation Steps:

Collect news and tweets
Apply sentiment analysis
Show charts and scores
Add stock search module

Key Features:

Real time sentiment
News filtering
Visual trend output

Learnings:

NLP basics
API integration
Market data handling

Real-World Application:

Investment research
Trading signals

Get Started

5. Fraud Transaction Detector

A system that flags unusual or suspicious transactions based on amount, frequency, and user patterns. It adds an extra layer of safety in digital payments.

Duration: 12–16 hours

Difficulty Level: Medium

Tech Stack Required: Python, Anomaly Detection Models, MongoDB

Implementation Steps:

Load transaction history
Build anomaly detection model
Mark suspicious entries
Display fraud alerts

Key Features:

Outlier detection
Fraud alerts
Pattern analysis

Learnings:

Anomaly detection
Risk scoring
Secure model design

Real-World Application:

Banking security
Payment systems

Get Started

6. Crypto Price Tracker with Alerts

A simple tool that monitors cryptocurrency prices and alerts users when prices cross chosen thresholds. It supports fast tracking and personalised notifications.

Duration: 15–18 hours

Difficulty Level: Medium

Tech Stack Required: Node.js, React, CoinGecko API

Implementation Steps:

Integrate price API
Build price watchlist
Add custom alert logic
Display charts

Key Features:

Live price updates
Custom alerts
Multi coin support

Learnings:

API polling
Alert scheduling
Crypto market basics

Real-World Application:

Trading alerts
Market monitoring

Get Started

7. Smart Tax Calculator

A tax assistant that calculates tax based on income, deductions, and regime selection. It helps users plan tax savings with quick suggestions.

Duration: 18–22 hours

Difficulty Level: Medium

Tech Stack Required: React, Node.js, REST APIs

Implementation Steps:

Build tax slabs logic
Add input forms
Show tax amount
Suggest savings options

Key Features:

Regime wise comparison
Savings tips
Clean result summary

Learnings:

Finance logic modelling
Form based apps
Real user flows

Real-World Application:

Salary planning
Tax filing preparation

Get Started

8. Investment Portfolio Rebalancer

A tool that checks the weight of stocks, bonds, and mutual funds and recommends rebalancing based on user goals. It helps maintain long term stability.

Duration: 20–26 hours

Difficulty Level: Hard

Tech Stack Required: Python, Pandas, Streamlit

Implementation Steps:

Add portfolio inputs
Analyse weight distribution
Suggest rebalancing
Show long term projections

Key Features:

Goal based insights
Portfolio analytics
Simple recommendations

Learnings:

Portfolio theory
Data visualisation
Financial modelling

Real-World Application:

Wealth management
Robo advisory tools

Get Started

9. Credit Score Simulator

A simulator that shows how actions like paying bills, missing payments, or taking loans affect credit score. It helps users understand credit behaviour clearly.

Duration: 22–28 hours

Difficulty Level: Hard

Tech Stack Required: React, Firebase, Scoring Algorithms

Implementation Steps:

Build scoring model
Add financial actions
Update score dynamically
Show score improvement tips

Key Features:

Real time score changes
Behaviour based learning
Scenario testing

Learnings:

Credit scoring logic
Dynamic UI updates
User education flows

Real-World Application:

Banking education
Credit improvement apps

Get Started

10. AI-Powered Financial Advisor

A recommendation tool that analyses income, expenses, risk and goals to provide personalised investment suggestions. It acts like a basic automated advisor.

Duration: 28–36 hours

Difficulty Level: Hard

Tech Stack Required: Python, ML Models, React

Implementation Steps:

Collect financial inputs
Run risk profiling
Suggest investment mix
Display actionable plan

Key Features:

Personalised advice
Dynamic risk scoring
Simple action plan

Learnings:

Recommendation models
Risk analysis
Finance AI systems

Real-World Application:

Robo advisors
Wealth management

Get Started

Examples of Top Finance Hackathon Winners

1. HARBINGER 2023 – Inclusive Digital Services – One of the winning teams developed “DrishtiPay,” a financial payment solution designed for visually impaired users. The project focused on secure OTP and NFC based transactions to improve accessibility in digital payments.

2. Open FinHack 2024 – International FinTech Hackathon – The winning team “Frankey” created a flexible financial platform that supported both consumer and business use cases. Their solution stood out among participants from multiple countries for its clean design and strong financial workflow.

3. Sustainable Finance Live 2023 Hackathon – Winning teams “We Succeed Together” and “Team Thrive” built tools that combine ESG metrics with practical finance insights. They focused on sustainability scoring, carbon tracking, and ethical financial decision support.

4. LTS Cyber and FinTech Hackathon 2023 – Student teams built secure financial applications as part of a combined cybersecurity and fintech challenge. The winning project demonstrated strong safety features and practical use in modern digital banking.

Final Words

Finance hackathons reward ideas that solve real problems with simple, clear, and impactful solutions.

With the right project scope and strong execution, you can build a functional prototype that impresses judges and provides real value to users.

Use these ideas to stay focused, work faster, and present a project that stands out from the competition.

Frequently Asked Questions

1. What are the best Finance project ideas for hackathons?

The best Finance project ideas for hackathons include budget planners, fraud detectors, investment tools, tax calculators, and credit score simulators that solve real user needs effectively.

2. How do I choose the right Finance project for a hackathon?

Choosing the right Finance project for a hackathon depends on your team skills, available data, time limits, and selecting a problem simple enough to build quickly.

3. Which Finance domFinancens are most popular in hackathons?

Finance domains most popular in hackathons include personal finance, fintech automation, investment analytics, fraud detection, credit scoring, and financial education for beginners.

4. Where can I find open datasets for Finance hackathon projects?

Open datasets for Finance hackathon projects are available on platforms like Kaggle, Google Dataset Search, World Bank Data, IMF Data, and public market APIs.

5. Can beginners participate in Finance hackathons?

Yes, beginners can participate in Finance hackathons by choosing small, manageable ideas and focusing on simple features rather than complex financial modelling.

6. What tools and frameworks are commonly used in Finance projects?

Tools and frameworks used in Finance projects include Python, Flask, React, Firebase, Pandas, and basic ML libraries for building dashboards and simple predictions.

7. How can I complete an Finance project quickly during a hackathon?

Completing a Finance project quickly during a hackathon requires limiting features, using ready APIs, preparing clean datasets, and dividing work clearly within the team.

Thirumoorthy

Thirumoorthy serves as a teacher and coach. He obtained a 99 percentile on the CAT. He cleared numerous IT jobs and public sector job interviews, but he still decided to pursue a career in education. He desires to elevate the underprivileged sections of society through education