ORGANIZED BY LIAS

27 AUG – 25 OCT 2026

100% ONLINE HACKATHON

QuantHacks

London Institute of Actuarial Studies (LIAS)

CODE•QUANTIFY•INNOVATE

A national-level online hackathon sitting at the intersection of Technology, Data, Probability & Statistics, Risk, and Decision-Making.

The QuantHacks Mandate:

“Build something useful. Quantify the uncertainty. Defend your decisions.”

REG: 27 AUG - 15 SEP

HACK: 23 - 25 OCT

~30 COHORT TEAMS

1-4 MEMBERS / TEAM

QuantTerminal CLI

3 TracksCyber, FinTech, EdTech

~150 PoolApplication Review

~30 TeamsFinal Hack Cohort

100% OnlineTeams & Zoom

Initializing 3D QuantBot Scene...

3D Co-Pilot: QuantBot

WebGL 3D

ORGANIZED BY LIAS

About QuantHacks

QuantHacks is a national-level online hackathon organized by the London Institute of Actuarial Studies (LIAS), bringing together students, developers, data enthusiasts, and aspiring actuaries to solve real-world problems through technology, quantitative reasoning, and actuarial thinking.

Pillar 01

Technology

“Gives you the tools.”

Build scalable applications, modern pipelines, AI models, and real-time interactive interfaces.

Pillar 02

Data

“Gives you evidence.”

Ground decisions in empirical observations, historical records, and quantitative telemetry.

Pillar 03

Quantitative Thinking

“Gives you a way to reason about uncertainty.”

Model risk distributions, forecast probabilities, stress test assumptions, and optimize payoffs.

THE QUANTHACKS PHILOSOPHY

Beyond the Flashiest Interface:
Reasoning Through Uncertainty

A conventional hackathon can be won by building the flashiest interface in the room. QuantHacks is looking for something different.

We look for teams that don’t simply show static data, but quantify the risk, acknowledge model limitations, and use technology to guide high-stakes decision-making under uncertainty.

What you build with technology and data is up to you.

The 5 Core Quantitative Questions:

What is uncertain?

Can we measure it?

Can we predict it?

What happens if our assumptions are wrong?

Can technology help us make a better decision?

WHAT CAN YOU BUILD?

Challenge Tracks

Three tracks under the umbrella of actuarial science, risk, and quantitative decision-making. Pick one that excites you.

💡 These are areas of exploration, not restrictions. Teams are encouraged to formulate their own problem statements with a meaningful quantitative/risk connection.

Probability, Risk & Incident Forecasting

Cybersecurity & Cyber Risk

Quantitative Cyber Risk, Threat Modeling & Insurance Analytics

Example projects you could build

01A cyber-risk scoring engine that predicts attack probability from vulnerability telemetry
02An actuarial loss model that prices cyber insurance premiums using Monte Carlo simulation
03An anomaly detection system that forecasts security incidents before data exfiltration

THE QUANTITATIVE EDGE

More Than a Polished Interface

The quantitative component in your project should actually improve the decision being made.

Probability & Statistics

Distribution fitting, Bayesian analysis, hypothesis testing

Empirical Decision Logic

Risk Modelling & Actuarial Math

Loss tail distributions, Value-at-Risk (VaR), TVaR

Empirical Decision Logic

Predictive Analytics & ML

Classification, regression trees, gradient boosting, neural nets

Empirical Decision Logic

Expected Value & Expected Loss

Actuarial payoff matrices, risk premiums, reserve estimation

Empirical Decision Logic

Frequency & Severity Modelling

Poisson processes, Gamma/Pareto loss severity estimation

Empirical Decision Logic

Monte Carlo Simulation

Stochastic path generation, multi-scenario trials

Empirical Decision Logic

Scenario Analysis & Stress Testing

Black swan simulations, macroeconomic shock testing

Empirical Decision Logic

Forecasting & Time-Series

ARIMA, Prophet, GARCH volatility forecasting, trend projection

Empirical Decision Logic

Golden Principle for Participants:

“A simple model that answers the right question is better than a complicated model that exists only to decorate a slide.”

You do not need to build an unnecessarily complicated mathematical model. Focus on clarity, validation, and sound reasoning under uncertainty.

LIAS Actuarial Standard

STOCHASTIC JOURNEY PATH

The QuantHacks Timeline Trajectory

Follow the serpentine quantitative roadmap from registration opening to the final online pitch defense.

QUANTBOT TRAJECTORY HUD

CLICK TO WARP TO MILESTONE

QuantBot Co-Pilot • Step 01

QuantBot: "Registration is LIVE! Form your 1-4 member squad and submit your problem concept on Devfolio."

27 August 2026

REG OPENS 27 AUG

Devfolio ApplicationsRegistration Kickoff

Registration Opens

Registration opens exclusively through Devfolio. Teams submit their application, proposed approach, and team formation of 1 to 4 members.

Registration opens on 27 August 2026

Open to students, professionals & international participants

Teams may consist of 1 to 4 members

Model Focus:P(A \cap B) = P(A)P(B|A)

Step 01

27 August 2026

Registration Opens

Devfolio Applications

P(A \cap B) = P(A)P(B|A)

15 September 2026

Registration Closes

Selection Evaluation Pool

\text{Score} = \sum_{i=1}^7 w_i \cdot c_i

Step 02

15 September 2026

HARD DEADLINE

Selection Evaluation PoolApplication Deadline

Registration Closes

Registration officially closes. QuantHacks will accept up to approximately 150 registrations/teams for structured evaluation.

Registration closes on 15 September 2026

Up to ~150 registrations/teams accepted for review

Evaluated across 7 weighted criteria: Problem (20%), Quant Relevance (20%), Feasibility (15%), Team (15%), Innovation (10%), Impact (10%), Previous Work (10%)

Model Focus:\text{Score} = \sum_{i=1}^7 w_i \cdot c_i

16 October 2026

~30 TEAMS SHORTLIST

Final Cohort SelectionCohort Announcement

Shortlisted Teams Announced

The final hackathon cohort of approximately 30 teams is announced. Selected teams prepare for the 3-day online build and pitch event.

Shortlisted teams announced on 16 October 2026

Final cohort consists of approximately 30 teams

Teams onboard to official online event infrastructure

Model Focus:N_{\text{final}} \approx 30

Step 03

16 October 2026

Shortlisted Teams Announced

Final Cohort Selection

N_{\text{final}} \approx 30

23 October 2026

Hackathon Day 1

Sprint Kickoff

dX_t = \mu X_t dt + \sigma X_t dW_t

Step 04

23 October 2026

DAY 1: BUILD & MODEL

Sprint KickoffBuild Day 1

Hackathon Day 1

Teams begin building their solutions, developing their models, testing their ideas, and working with their teammates.

Main build period officially begins online

Develop quantitative, risk, and machine learning models

Test probability assumptions and engineer core solution pipelines

Model Focus:dX_t = \mu X_t dt + \sigma X_t dW_t

24 October 2026

DAY 2: SUBMIT & LOCK

Validation & SubmissionBuild Day 2 & Lock

Hackathon Day 2

Teams continue development, validate their solutions, prepare their demonstrations, and finalise their submissions.

Continue system development and validate quantitative models

Prepare working prototype demonstrations

Finalise project documentation and code submissions on Devfolio

Model Focus:\text{VaR}_\alpha = \inf \{ l \in \mathbb{R} : P(L > l) \le 1 - \alpha \}

Step 05

24 October 2026

Hackathon Day 2

Validation & Submission

\text{VaR}_\alpha = \inf \{ l \in \mathbb{R} : P(L > l) \le 1 - \alpha \}

25 October 2026

Final Pitches & Results

Live Online Judging

\mathbb{E}[\text{Impact}] \to \max

Step 06

25 October 2026

PITCHES & RESULTS

Live Online JudgingJudging Expo & Awards

Final Pitches & Results

Selected teams will present their projects to the judging panel online through Microsoft Teams or Zoom. The final format and results will be announced.

Final pitches conducted online via Microsoft Teams or Zoom

Present project methodology, quantitative reasoning & prototype to LIAS jury

Closing ceremony and announcement of results and track winners

Model Focus:\mathbb{E}[\text{Impact}] \to \max

Online Event Format

The Hackathon Sprint: 23 – 25 October 2026

The hackathon will be conducted entirely online. Final pitches will be conducted online through Microsoft Teams or Zoom.

23 October 2026

Hackathon Day 1

Teams begin building their solutions, developing their models, testing their ideas, and working with their teammates.

• Initial Modeling & Sprint Kickoff

24 October 2026

Hackathon Day 2

Teams continue development, validate their solutions, prepare their demonstrations, and finalise their submissions.

• Validation & Submission Lock

25 October 2026

Final Pitching & Results

Selected teams will present their projects to the judging panel online. The final format and exact pitch duration will be announced before the event.

• Live Judging on Teams / Zoom

Registration opens 27 August 2026 and closes 15 September 2026.

EVALUATION FRAMEWORK

Selection & Judging Criteria

QuantHacks uses a structured, transparent evaluation system designed to identify teams with genuine quantitative and technical capabilities.

CRITERION #120%

Problem & Idea Quality

Problem clarity, significance, understanding of target users, and quality of the proposed approach.

CRITERION #220%

Quantitative / Actuarial Relevance

Demonstration of risk, probability, statistics, prediction, forecasting, expected outcomes, and uncertainty reasoning.

CRITERION #315%

Technical Feasibility

Viability of the technical approach, choice of technologies, data availability, complexity, and team capabilities.

CRITERION #415%

Team Capability

Technical skills, quantitative background, domain knowledge, complementary abilities, and previous project execution.

CRITERION #510%

Innovation

Meaningful new idea, creative approach, novel combination of tools, not another generic chatbot with a new logo.

CRITERION #610%

Potential Impact

Target user adoption, business or social value, practical applicability, scalability, and future development scope.

CRITERION #710%

Previous Work & Evidence

Past projects, GitHub repos, hackathons, or research demonstrating genuine development capabilities.

GitHub & Project Verification

Ensuring Fairness & Genuine Technical Capability

Application Review

Applicants may be asked to provide links to their previous projects, GitHub repositories, or portfolios. The organising team may review repository history, commit activity, structure, and original contributions to verify genuine previous development.

💡 Note: You do not need an extensive GitHub profile to participate. A repository created specifically for an application is not automatically disqualifying—what matters is whether your work demonstrates genuine capability.

PARTICIPATION & GUIDELINES

Eligibility, AI Policy & Rules

Everything you need to know about team eligibility, AI tool permissions, and project submission guidelines.

WHO CAN PARTICIPATE

1 to 4 Members / Team

Global Open Participation

QuantHacks welcomes anyone interested in technology, data science, and quantitative problem-solving. Participants from outside India are welcome.

College & University Students

Undergraduate and postgraduate students in CS, math, stats, finance, engineering, or actuarial tracks.

School Students

Ambitious high-school coders and data enthusiasts with an aptitude for quantitative reasoning.

Working Professionals

Engineers, data scientists, quantitative analysts, and developers in industry.

Actuarial & Math Aspirants

Students pursuing IFoA, SOA, CAS, or IAI actuarial examinations and risk research.

You may participate as an individual, pair, or team of 3 to 4.

AI TOOL USAGE POLICY

AI Permitted & Embraced

Empowered by AI, Grounded in Understanding

AI coding assistants, LLMs, and AI APIs are expected tools in modern engineering. QuantHacks does not artificially restrict them.

The Fundamental AI Rule:

“AI may assist your work. It cannot replace your understanding of it.”

Teams must be able to explain:

What was built and why the architecture was chosen
How the system works and mathematical models function
Why the quantitative approach makes sense & model limitations

⚠️ Submitting an AI-generated project that you cannot defend will negatively affect evaluation.

Final Submission Deliverables Checklist

Teams will demonstrate a working solution or meaningful prototype on Devfolio

Public or Evaluator-accessible Project Repository

Project Description & Comprehensive README

Working Prototype or Interactive Demonstration

Quantitative Methodology & Mathematical Formulation

Data Sources & Model Training / Simulation Explanation

Empirical Results, Model Limitations & Future Scope

PRIZES & RECOGNITION

Awards, Categories & Recognition

The prize pool and rewards structure is currently being finalized by the London Institute of Actuarial Studies (LIAS).

Final Prize Details Will Be Announced Prior to Hackathon Kickoff

Specialty Award

Best Quantitative Solution

Awarded to the team with the most rigorous, sound, and insightful quantitative / actuarial mathematical model.