A French platform that aggregates and verifies referral codes across various sectors including banking, crypto, mobile, energy, shopping, and cashback, allowing users to earn bonuses.
Each model independently rates Parrain Code on a 1–5 star scale.
Parrain Code is a French referral code aggregation platform. It serves as a directory for promo/referral codes across sectors. Not a financial service itself, but a marketing intermediary. Limited international reputation data available.
Parrain Code is a French platform for referral codes with a focus on bonuses across multiple sectors. Limited public information affects scoring.
Parrain Code is a French platform aggregating referral codes for bonuses across sectors like banking, crypto, and shopping. Lacks specific regulatory oversight or trading features, hence moderate scores. Reputation is based on user experience with deals.
Parrain Code is a French referral-code aggregator with community verification across sectors. Useful for bonuses but limited third‑party coverage. Likely basic compliance (e.g., GDPR) but not sector‑regulated. Mixed user sentiment typical for referral platforms.
Limited public information available on Parrain Code, a niche French referral aggregator. No major red flags or strong track record found, so neutral scores assigned across all categories.
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Parrain Code is rated 2.5 out of 5 (“Poor”) on TrustRating, based on 5 independent AI model assessments. The TrustScore combines real customer reviews with AI models that independently assess trust, regulation, support and reputation signals. Always do your own research before making a purchase or investment.
TrustRating doesn't issue scam verdicts — we publish the data instead: Parrain Code scores 2.5 out of 5 (“Poor”) based on 5 independent AI model assessments. Every review passes TrustGuard, our fraud-screening system that blocks fake and paid reviews, so the score reflects genuine customer experience. Read the most recent reviews below before you decide.
Parrain Code currently has a TrustScore of 2.5 out of 5 (“Poor”). The score blends verified customer reviews with assessments from multiple independent AI models, and it updates automatically as new reviews and scans come in. You can read exactly how scores are computed on our methodology page.
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