Branden Beardsley
Branden Beardsley
Payments Performance Manager, Adyen
Chicago, IL
MS Data Science · 4.0 GPA
Product Manager · Payments Intelligence · Stripe

Hi, I'm Branden.

Almost 8 years in payments. Currently at Adyen, where I pitch and configure the same products Stripe's Payments Intelligence team owns — authorization optimization, ML fraud prevention, smart authentication routing, and payment cost reduction. Before that: built a risk engine from scratch at Paze, pitched fraud tools at PayPal/Braintree, and scaled a fraud team at Chime.

I've never held the title of Product Manager — but I know how payments work, full funnel. I spend my weekends building Cellix.ai because I can't stop thinking about these problems. I'd love the opportunity to start my PM career at Stripe.

See my journey ↓ My weekend project → Resume
What I bring

I work on Adyen's versions of
the products this team owns.

Stripe's Payments Intelligence team owns Radar and Authorization Boost. At Adyen, I pitch, configure, and optimize the direct equivalents every day — across the full payment funnel.

Adyen Uplift Optimize → Stripe Authorization Boost

Authorization optimization & payment routing

I advise 50+ enterprise merchants on auth rate optimization at Adyen — designing A/B tests against competing processors, configuring intelligent payment routing, and translating basis-point auth improvements into dollar-denominated merchant revenue. This is the same work Authorization Boost does: smart retry logic, network token optimization, least-cost routing, and issuer-level auth strategy to maximize every transaction.

Adyen Uplift Protect → Stripe Radar

ML-powered fraud prevention & risk scoring

I help merchants configure Adyen's ML fraud scoring engine — setting risk thresholds, customizing action-based rules, backtesting rule performance, and tuning the balance between false positives and fraud catch rate. At Paze, I built an entire risk engine from scratch: 90+ signal-layered rules, vendor selection, and precision/recall tuning. This is Radar's core problem space.

Adyen Uplift Authenticate → Stripe 3DS/SCA

Smart authentication & exemption routing

I work with merchants on Adyen's authentication optimization — smart 3DS routing that applies authentication where required while leveraging exemptions where permitted. The ML models select the optimal auth route per transaction, balancing SCA compliance with conversion. This same challenge exists at Stripe across every regulated market.

Full-funnel payment optimization

How payments actually work, end to end

Most people specialize in one slice. I work across the entire payment funnel at Adyen — from pre-checkout fraud scoring (Protect), through authentication routing (Authenticate), to authorization optimization and cost reduction (Optimize). Understanding how these systems interact is what makes the difference between good and great payment intelligence.

Built from zero at Paze

0→1 risk engine architecture

Paze launched as a digital wallet with zero fraud infrastructure. I owned the entire buildout: evaluated vendors, wrote technical specs, defined API integration requirements, authored 90+ fraud rules, and ran tuning cycles against board-mandated auth rate targets. Shipped a complete risk engine to production in under 12 months — the kind of 0→1 work that teaches you how these systems really work.

Weekends & curiosity

I built Cellix.ai because I can't stop thinking about this

An AI-powered dispute automation platform across 27+ processor integrations — built on nights and weekends. Not to launch a startup. Because after years of watching merchants lose disputes they should win, I wanted to see if I could build something better. Stripe's API was my first integration because the DX was that good.

Career

Almost 8 years. Four companies.
One domain I can't get enough of.

Each role brought me deeper into payments — from operations to strategy to optimization. Here's the thread that connects them.

Adyen Feb 2025 – Present Payments Performance Manager

Consulting top accounts on the Adyen equivalents of Radar and Authorization Boost

Currently advising 50+ enterprise merchants on the full Uplift suite — Protect (ML fraud scoring, same as Radar), Authenticate (smart 3DS routing), and Optimize (auth rate optimization, same as Authorization Boost). I design A/B tests against competing processors, configure intelligent payment routing, and translate basis-point improvements into merchant revenue. Generated $15M+ in ARR through Protect portfolio expansion. This is the same work Stripe's Payments Intelligence team does — different logo.

$15M+ ARR 50+ merchants advised Current role
Paze (Early Warning) Feb 2024 – Feb 2025 Sr. Fraud Risk Strategist

Built a risk engine from scratch for a digital wallet

Paze launched competing with Apple Pay and PayPal with zero fraud infrastructure. I owned the entire risk engine architecture: evaluated and onboarded signal vendors, wrote technical specs, defined API integration requirements with engineering, authored 90+ signal-layered fraud rules, and ran precision/recall tuning against board-mandated auth rate targets. Reported directly to the board weekly. This was 0→1 product ownership — the kind of build that teaches you how these systems really work under the hood.

90+ fraud rules shipped 3–5pp auth rate lift 0→1 from scratch
PayPal Oct 2021 – Feb 2024 Enterprise Risk Strategist

Pitched fraud tools and managed card program risk at scale

Pitched fraud tools and risk solutions to enterprise merchants at Braintree/PayPal — covering dispute analytics, fraud recommendations, and compliance dashboards across 500+ accounts. Managed card program risk with Visa and Mastercard, preventing $2M+ in annual fines. Designed the merchant-facing product bundle that drove $500K+ in new ARR. This is where I learned how payment risk works at the enterprise level.

$2M+ fines prevented $500K+ new ARR 500+ merchants
Chime 2019 – 2021 Fraud Operations & Strategy

Scaled a fraud team from pilot to 150+ people

Built and directly managed a team of 10, while scaling the broader fraud ops site from a small pilot to 150+ investigators. Defined case routing logic, SLA frameworks, and accuracy thresholds. Built dispute forecasting models that predicted volume 30 days out and cleared 30% of backlog. This is where I learned how fraud operations actually work — before the ML layer.

Managed team of 10 150+ investigators scaled 95%+ case accuracy
The weekend project

I built this for fun.
That's kind of the point.

Cellix.ai is an AI-powered dispute automation and payment intelligence platform. I built it on nights and weekends because the problem was too interesting not to. It's live in production with 27+ processor integrations.

Why I built it

After years of managing disputes manually across PayPal, seeing merchants struggle with card network compliance, and building fraud systems from scratch at Paze — I kept thinking: this should be automated, and nobody's doing it well. So I started building.

Cellix automates dispute investigations end-to-end — compiling evidence to Visa CE3.0 and Mastercard specs, submitting via processor APIs, and running fraud prevention across the stack. It solves a real industry pain point, and building it taught me more about payment infrastructure than any job could.

What it does

  • Automates dispute evidence compilation to card network specifications
  • Integrates with 27+ processors — including Stripe, Adyen, PayPal, Checkout.com, Braintree
  • 50ms dispute decision latency
  • Full lifecycle dispute automation from intake to submission
  • ML-powered fraud signal analysis and prevention
The full Cellix story → www.cellix.ai ↗
Why Stripe

I work at Adyen.
I want to be at Stripe.

The view from the other side

I work at one of Stripe's biggest competitors, and every day I see why Stripe is the company everyone is chasing. Stripe doesn't just process payments — it sets the standard. Radar changed what merchants expect from fraud prevention. Authorization optimization became a core product category because Stripe made it one. The developer experience is the benchmark every other processor measures against.

I've seen the gap firsthand

At Adyen, I watch us try to close the gap Stripe created. At PayPal, I saw enterprise merchants compare everything to Stripe's tooling. When building Cellix.ai, Stripe's API was my first integration — not for market share, but because the docs were so clean it took a fraction of the time. That's what happens when a company truly treats developers as the user.

Why Payments Intelligence specifically

This team sits at the intersection of everything I care about: ML-driven authorization optimization, fraud signal architecture, and turning model improvements into real merchant revenue. I've spent almost 8 years on these exact problems — and I've never seen a team that approaches them with the rigor and ambition that Stripe does.

What I'd bring

I don't have a PM title on my resume. What I have is domain fluency in the exact problem space this team owns, hands-on experience shipping payment systems, the analytical foundation (MS Data Science) to work with data science and engineering, and merchant-facing instincts from advising hundreds of enterprise accounts.

Stripe's posting welcomes "extraordinary career paths." Mine — from fraud ops at Chime to building an AI payment platform on weekends — is exactly that.

I'd love the chance to start my PM career at the company that defines how the world thinks about payments.