Markus Halvorsen
Markus brings over 15 years of iGaming industry experience, specialising in regulatory compliance, licensing frameworks, and risk assessment. He personally ensures that every casino review on the platform meets rigorous transparency and player protection standards.
My Story
I began working in iGaming compliance and licensing in 2010, concentrating on operator risk assessment and regulatory frameworks across European markets. Over the following five years, I specialised in multi-jurisdictional licensing structures - MGA, UKGC, KGC - and started reviewing bonus terms against player-protection standards. The work gave me direct visibility into how operators draft their T&Cs, where the legal grey areas sit, and which clauses systematically disadvantage players.
By 2020, I had a recurring frustration: most affiliate review sites operated as paid listing directories. Rankings were sold, criteria were vague, and editorial independence was theatre. The problem was structural - review teams needed scale, scale required money, and money came from operators who expected favourable placement. No accountability, no public formula, no audit trail.
In 2024, I started building CasinoScraper as a solo-founder project. I designed the six-pillar rating formula, built the FastAPI and Next.js stack, wrote the scraping pipelines, and integrated Anthropic Claude for TOS analysis. The platform spent two years in engineering-only mode - no public traffic, just pipeline development and data accumulation. In August 2026, CasinoScraper launched publicly across 38 markets with the full audit infrastructure already running: public formula, monthly re-scoring, daily catalogue expansion, automated TOS analysis, and full version history from day one.
The backend that replaces the team
Six always-on pipelines handle scraping, scoring, TOS analysis, and daily publication - the workflow that would require an editorial staff runs on Celery and Claude instead.
One founder. Six pipelines. Zero manual score adjustments.
Monthly scraping of casino terms, bonus details, payment methods, and licensing data via ScrapingBee and Playwright. Extracts structured data from operator sites and feeds it into the scoring engine.
monthlyCollects user reviews from Trustpilot, AskGamblers, and other third-party platforms. Aggregates sentiment and rating distributions to feed the User reviews pillar.
monthlyAnthropic Claude analyses every casino's terms and conditions against a fixed predatory-clause checklist - max cashout traps, dormancy fees, one-sided change rights, unrealistic wagering requirements. Findings feed the Bonus fairness pillar and are surfaced in reviews.
on TOS changeComputes Trust & licensing, Bonus fairness, Payout speed, Payment convenience, UX & mobile, and User reviews scores using the public formula. Recomputes automatically whenever any input data changes - no manual overrides.
on changeDaily Celery job publishes updated scores and rankings at 08:00 UTC. Triggers Next.js ISR revalidation for affected pages and clears Redis cache entries.
daily 08:00 UTCRedis stores computed scores, serialised brand data, and aggregated review stats. Next.js ISR caches pages with stale-while-revalidate - users always see fast responses, background jobs refresh data on change.
always-onWhy CasinoScraper
CasinoScraper exists because the affiliate review industry has an accountability problem. Most sites present rankings as editorial judgement while selling the order behind the scenes. Criteria are described in vague language - "trusted", "reputable", "best" - with no definition of how those labels are earned or lost. When a casino drops five positions overnight, readers have no way to know whether the operator changed or the affiliate's revenue deal did.
I built this platform to solve that problem for one person at a time. Every score on CasinoScraper comes from a public formula. The six pillars - Trust & licensing, Bonus fairness, Payout speed, Payment convenience, UX & mobile, User reviews - are weighted and computed the same way for every brand. If a rating changes, the input data changed. If a clause in the terms gets flagged, the flagging logic is documented. Affiliate links fund the operation, but they do not move rankings.
What makes it WOW
What makes CasinoScraper different is the engineering discipline behind it. This is not a content site with a scoring system bolted on - it is an audit platform that happens to publish content. Every casino is re-scored monthly against fresh data. Every terms-and-conditions document is analysed by Claude against a fixed predatory-clause checklist. Every brand change is versioned. The workflow that would require an editorial team runs on Celery jobs and caching layers instead.
The platform launched across 38 markets on day one because the pipeline architecture was built first and content was generated second. I did not start with five markets and expand gradually - I built the tooling to handle 38 locales, ran it for two years, then made it public. The solo-founder model is not a limitation - it is the design constraint that made the automation necessary and the independence possible.
The editorial bar is also non-negotiable. Every text field on the site is written by me, in first person, with no ghostwriters and no swappable freelancers. When I describe a licensing framework or a withdrawal test, the voice is consistent because it is one voice. Where other platforms say "our team of experts", I say "I" or describe what the system does. That is not a stylistic choice - it is an accountability mechanism.
Public formula
Every score is computed from documented inputs and published weights. Anyone can reproduce a rating from the same data.
Monthly re-scoring
Every casino is re-evaluated once per month against fresh scraped data, external reviews, and terms changes.
Never paid rankings
Affiliate links fund the operation, but they do not change scores or order. Position comes from the formula.
One editorial voice
Every text field on the site is written by one person, in first person, with no ghostwriters or swappable freelancers.
Automation over teams
The workflow that would require an editorial staff runs on Celery jobs, scraping pipelines, and AI-assisted analysis instead.
Audit-trailed changes
Every brand edit is versioned. If a rating changes, the input data changed - and the history is preserved.
TOS analysis
Every casino's terms are analysed by Claude against a fixed predatory-clause checklist. Findings feed the Bonus fairness pillar.
38-market launch
The platform launched publicly with full coverage across 38 locales, not a gradual rollout. The tooling was built for scale first.
Tech & Tools
The stack that powers locale-aware data, audit trails, and AI-assisted content.
How I do things differently
Most casino affiliate sites operate on a team-driven editorial model. They hire writers to produce reviews, SEO specialists to optimise for keywords, and analysts to assign scores. The output is polished, the update cadence is high, and the rankings are influenced by commercial relationships even when the disclosure says otherwise. The tell is usually in the vague criteria - "overall quality", "player satisfaction", "industry reputation" - and the absence of any public formula that would allow a third party to verify a score.
CasinoScraper inverts that model. The scoring is automated and deterministic. The six-pillar formula is published with exact weights. The rankings update monthly when the data updates, not when a partnership deal changes. The editorial voice is singular and attributed - every review, every market guide, every explanatory paragraph is written by the same person. The platform does not pretend to be a team operation because independence at this scale requires automation, not hiring.
The technical infrastructure also separates this project from typical affiliate sites. Most platforms run on WordPress with a review plugin and manual score entry. CasinoScraper runs on a custom FastAPI backend with Celery pipelines, PostgreSQL storage, Redis caching, and Next.js 15 on the frontend. Scraping happens monthly via ScrapingBee and Playwright. TOS analysis runs on Anthropic Claude. Scores recompute automatically when any input changes. Publication happens daily at 08:00 UTC via a scheduled job. The stack is over-engineered for a review site because this is not a review site - it is an audit platform.
Journey so far
Started in iGaming compliance
Began working in regulatory compliance, licensing structures, and operator risk assessment at European iGaming operators.
Multi-jurisdictional licensing focus
Specialised in cross-border licensing frameworks (MGA, UKGC, KGC) and began reviewing bonus terms against player-protection standards.
Identified the affiliate problem
Recognised the structural issue in affiliate review sites: paid placements disguised as editorial rankings, vague criteria, zero accountability.
Started building CasinoScraper
Began engineering the platform as a solo-founder project - designed the six-pillar formula, built the FastAPI/Next.js stack, wrote scraping pipelines, integrated Claude for TOS analysis.
Public launch across 38 markets
Launched CasinoScraper.com publicly in August with full audit infrastructure: public formula, monthly re-scoring, daily catalogue expansion, automated TOS analysis, version history.
Recent casino reviews
The latest casinos analysed using my 6-pillar scoring formula.

Stake

22bet

Playamo

Hitnspin

Slotoro
