QuantHacks

Grand Prize

1st Runner Up

2nd Runner Up

Swags/T-shirts

##  Cybersecurity Track

### Quantify the Threat. Predict the Risk. Build the Defence.

Cybersecurity isn't just about preventing attacks. It's about understanding **uncertainty, probability, and potential loss**.

In the Cybersecurity track, participants are challenged to build technology-driven solutions that identify, predict, quantify, and manage cyber risks. Use **machine learning, statistics, probability, data analytics, and actuarial thinking** to tackle problems where the next attack, its likelihood, or its financial impact is uncertain.

You could explore areas such as:

- **Cyber Risk Assessment:** Develop models that quantify the likelihood and severity of cyber incidents.
- **Threat Prediction:** Use historical and real-time data to identify patterns and predict potential attacks.
- **Fraud & Anomaly Detection:** Detect unusual behaviour, transactions, or system activity before it becomes a larger threat.
- **Financial Loss Estimation:** Estimate the potential financial impact of cyber incidents using frequency, severity, and expected-loss models.
- **Cyber Insurance:** Develop tools for cyber-risk pricing, underwriting, claims prediction, or portfolio risk management.
- **Incident Response:** Build systems that help organisations prioritise threats based on probability, severity, and potential consequences.
- **Risk Scoring:** Create data-driven frameworks that translate complex cyber threats into understandable and actionable risk scores.

### The QuantHacks Challenge

Don't just ask:

> **"Can we detect an attack?"**

Ask:

> **"How likely is it to happen, how severe could it be, and what should we do about it?"**

A strong Cybersecurity project should go beyond identifying a threat. It should demonstrate how **quantitative reasoning can improve cybersecurity decisions under uncertainty**.

Whether you're predicting attack probability, estimating expected losses, modelling different threat scenarios, or stress-testing a security system, the goal is to turn cybersecurity data into **measurable risk and actionable decisions**.

**Build the defence. Quantify the risk.**

Cybersecurity

Best Overall Project In Cybersecurity

Best UI/UX in CyberSecurity

##  FinTech Track

### Quantify the Opportunity. Price the Risk. Build the Future.

Finance is fundamentally a problem of **uncertainty, risk, and decision-making**.

In the FinTech track, participants are challenged to build technology-driven solutions that use **data, statistics, probability, machine learning, and actuarial thinking** to solve real-world financial problems.

Whether you're predicting defaults, estimating investment risk, detecting fraud, or helping someone make better financial decisions, your goal is to turn financial data into **better, more informed decisions**.

You could explore areas such as:

- **Credit Risk:** Build models that assess the probability of loan defaults and help lenders make better credit decisions.
- **Financial Forecasting:** Predict market trends, cash flows, revenues, expenses, or other financial outcomes using historical and real-time data.
- **Insurance & Risk Pricing:** Develop models for insurance pricing, claims prediction, risk classification, or underwriting.
- **Fraud Detection:** Identify suspicious transactions and behavioural patterns using statistical and machine learning techniques.
- **Investment & Portfolio Risk:** Build tools for portfolio optimisation, risk measurement, asset allocation, or scenario analysis.
- **Personal Finance:** Create solutions that help individuals plan spending, savings, investments, or long-term financial goals under uncertainty.
- **Financial Stress Testing:** Model how portfolios, businesses, or individuals could perform under adverse economic or financial scenarios.
- **Alternative Risk Assessment:** Explore new data sources and quantitative methods for assessing financial risk where traditional approaches fall short.

### The QuantHacks Challenge

Don't just ask:

> **"What will happen to the money?"**

Ask:

> **"How likely is it to happen, how large could the impact be, and what decision should we make?"**

A strong FinTech project should go beyond displaying financial information. It should demonstrate how **quantitative reasoning can improve financial decisions under uncertainty**.

Whether you're modelling default probabilities, estimating expected losses, forecasting financial outcomes, optimising a portfolio, or stress-testing a financial system, the goal is to transform data into **measurable risk, meaningful insight, and actionable decisions**.

**Build the solution. Quantify the risk.**

FinTech

Best Overall Project In FinTech

Best UI/UX in FinTech

##  EdTech Track

### Understand the Learner. Predict the Outcome. Improve the Future.

Education is full of uncertainty. A student's performance, learning progress, career path, or likelihood of dropping out can all be influenced by countless factors.

In the EdTech track, participants are challenged to build technology-driven solutions that use **data, statistics, probability, machine learning, predictive analytics, and actuarial thinking** to make education more personalised, measurable, and effective.

The goal is to move beyond simply delivering educational content and instead use quantitative reasoning to **understand outcomes, identify risks, and make better decisions**.

You could explore areas such as:

- **Student Performance Prediction:** Build models that predict academic performance using historical and behavioural data.
- **Dropout Risk:** Identify students who may be at risk of dropping out and develop systems for early intervention.
- **Personalised Learning:** Create adaptive learning systems that recommend content, difficulty levels, or study plans based on individual performance.
- **Exam & Assessment Analytics:** Predict examination outcomes, identify knowledge gaps, or analyse assessment patterns.
- **Career Planning:** Develop data-driven tools that help students evaluate career paths based on skills, interests, performance, and future opportunities.
- **Skill-Gap Analysis:** Identify areas where learners are falling behind and recommend targeted interventions.
- **Learning Outcome Prediction:** Estimate the probability of achieving specific academic or learning outcomes.
- **Educational Resource Optimisation:** Use data to determine how teachers, institutions, or students can allocate limited resources more effectively.
- **Student Engagement:** Analyse behavioural patterns to predict disengagement and identify opportunities for intervention.
- **Education Risk Assessment:** Quantify the factors that contribute to poor academic or career outcomes and develop strategies to manage them.

### The QuantHacks Challenge

Don't just ask:

> **"How can we help students learn better?"**

Ask:

> **"What factors influence a student's outcome, how likely is a particular outcome, and what can we do to improve the probability of success?"**

A strong EdTech project should go beyond simply creating another learning platform. It should demonstrate how **quantitative reasoning can improve educational decisions under uncertainty**.

Whether you're predicting student performance, modelling dropout risk, identifying learning gaps, building personalised recommendations, or evaluating career outcomes, the goal is to transform educational data into **measurable insights, actionable interventions, and better outcomes**.

**Understand the learner. Quantify the risk. Shape the outcome.**

EdTech

Best Overall Project In EdTech

Best UI/UX in EdTech

QuantHacks

QuantHacks

QuantHacks$1,250

QuantHacks

$500 (Open): Grand Prize

$250 (Open): 1st Runner Up

$125 (Open): 2nd Runner Up

$125: Cybersecurity

$125: FinTech

$125: EdTech

Multiple Prizes (Open): Swags/T-shirts

QuantHacks$1,250

QuantHacks

$500 (Open): Grand Prize

$250 (Open): 1st Runner Up

$125 (Open): 2nd Runner Up

$125: Cybersecurity

$125: FinTech

$125: EdTech

Multiple Prizes (Open): Swags/T-shirts