Built Risk Models → Cut Fraud £820k/Yr: Risk & Fraud Bullets
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Risk-and-fraud bullets must always quote BOTH detection lift AND false-positive impact — gains in one at the cost of the other are not real wins. The rewrite quotes both, names the fraud-type (CNP), and the transaction volume.
Shipped a rule-graph + GBM hybrid card-not-present fraud model — cut chargebacks £820k/year while holding false-positive rate flat at 0.7% across 1.4M monthly transactions.
What changed and why
- ALWAYS quote the trade-off (FP rate, friction added, decline rate) — risk models that ignore the trade-off are how regulators get involved.
- Name the fraud-type (CNP, ATO, friendly-fraud, mule, ACH) — recruiters know the patterns vary 10× across types.
- £ saved/year > % reduction — auditors and CFOs prefer absolute numbers in finance bullets.
- Transaction volume (1.4M/mo) prevents a recruiter assuming the model ran on toy data.
Recruiter perspective
“£820k saved with flat FP rate on 1.4M txns is a real risk-eng result. Hybrid stack is the 2026 standard.”
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