ACT 491 · Year 4 · Semester 2 · 3 credits · Integration & Practice

Capstone II: InsurTech Product Studio

From theoretical model to production deployment: engineer, price, govern, and pitch market-ready InsurTech systems.

Season 1 · 8 episodes

The Full Stack Actuary

A brilliant student founder and her team have twelve weeks to build, price, capitalise, and pitch a live embedded parametric casualty engine for gig-economy fleets to ruthless venture capitalists and skeptical chief actuaries.

Protagonist · Maya Chen, a final-year Actuarial Science and Computer Science double major and technical lead of ShiftGuard, a real-time parametric insurance engine for urban delivery couriers.

Setting · The Actuarium Product Foundry and the high-stakes boardroom of Apex Re Ventures.

Stakes · Winning the two-hundred-and-fifty-thousand-dollar seed funding commitment and securing capacity from global reinsurers, or watching ShiftGuard join the graveyard of under-capitalised InsurTech failures.

Pick an episode

Episodes

Season finale: A live, zero-latency pilot deployment on a real gig delivery platform, verified by an automated ASOP 56 governance audit and funded by a lead syndicate at Demo Day.

From the lecturer: Welcome to Capstone II, the ultimate convergence point of your actuarial, computer science, and machine learning training. In this studio course, you will not simply write another paper or derive a closed-form formula in isolation; you will architect, deploy, price, and defend a complete, production-grade InsurTech application. Keep your terminal open, your Git branches clean, and your actuarial workpapers fully documented. Every pricing API endpoint you expose must satisfy rigorous actuarial principles (such as ASOP No. 12 on risk classification and ASOP No. 56 on modeling), withstand heavy latency and load constraints, and reflect strict capital reserving realities under Solvency II or NAIC Risk-Based Capital. Treat every sprint review as a dual audit: your codebase must pass automated integration tests, while your business case must survive scrutiny from chief actuaries, risk officers, and venture investors. Approach each weekly build as an opportunity to prove that modern data science and deep mathematical rigor can seamlessly coexist in live financial infrastructure. Let us build the future of insurance.

Cold open

At 2:14 AM in the Foundry lab, Maya stares at a competitor's pitch deck whose user acquisition graph climbs like a rocket while its loss ratio quietly bleeds at one hundred and forty-two percent. Her co-founder wants to build an all-you-can-eat subscription app for bicycle couriers, but the numbers scream immediate adverse selection.

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Transcript

Differentiate viable insurance problem spaces from uninsurable or adverse selection traps.
Size an InsurTech target market rigorously using top-down and bottom-up TAM, SAM, and SOM frameworks.
Formulate and calculate insurance Customer Lifetime Value (LTV), Customer Acquisition Cost (CAC), and unit economics.
Scope a Minimum Viable Actuarial Product (MVAP) integrating pricing, underwriting rules, and API interfaces.