A Quarterly Fraud-Rules Review Process

Fraud rules are not "set and forget." The fraud landscape shifts, your traffic mix changes, and rules that made sense in Q1 can quietly generate false positives or stop catching anything by Q3. Without a scheduled review, most stores accumulate a pile of rules nobody remembers writing and never dares to touch.

A quarterly fraud-rules review fixes that. It is a short, structured meeting that happens on a predictable cadence, produces clear decisions, and leaves a paper trail. Below is a process you can adopt this quarter.

Why quarterly is the right cadence

• Monthly is too noisy. A single bad week can trick you into over-reacting to a trend that reverses itself.
• Yearly is too slow. Fraud rings adapt in weeks, not months, and stale rules cost real revenue.
• Quarterly gives you enough data to see genuine patterns while staying responsive.

If you run seasonal spikes (BFCM, product drops), add a lightweight mid-quarter check two weeks before the event.

Who should be in the room

Keep it small and decisive:

• The owner of fraud/risk (final decision-maker)
• One person from customer support (they feel the false positives)
• One person from fulfillment or finance (they feel the chargebacks)

Three to four people maximum. More than that and it becomes a status meeting instead of a decision meeting.

Prep: the data pack

The review only works if someone assembles the numbers before the meeting. Pull the last 90 days:

• Total orders vs. orders blocked or held
• Chargebacks received (count and dollar value)
• Support tickets tagged "order blocked" or "can't check out"
• Top blocking rules by volume (which rules fired most)
• Rules that fired zero times all quarter
• Any new fraud patterns support or fulfillment flagged anecdotally

If you use Shieldy — Fraud Filter, its blocking logs and rule-level activity make this pack fast to assemble because each rule shows how often it triggered and what it caught.

The quarterly agenda (60 minutes)

Print this and run it top to bottom.

1. Review the headline metrics (10 min)

Look at the trend, not the single number. Are chargebacks up or down vs. last quarter? Is the block rate creeping higher without a matching drop in chargebacks? That combination is the classic false-positive warning sign.

2. Retire dead rules (10 min)

Every rule that fired zero times this quarter goes on the chopping block. For each, ask: "Is this protecting against something real, or is it a fossil?" Retire aggressively. A rule that never fires adds risk (someone eventually trusts it) without adding protection.

3. Review high-volume rules (15 min)

Take your top 5 firing rules. For each:

• How many blocks were confirmed fraud vs. confirmed good customers who complained?
• Should the rule be tightened, loosened, or converted from "block" to "flag for review"?

A rule blocking 200 orders where 30 were legit customers is not a good rule — it is a liability.

4. Add new rules (15 min)

Based on the anecdotal patterns and any new chargebacks, propose new rules. Good candidates:

• Geography you never ship to but keep getting orders from
• VPN/proxy/Tor traffic on high-value carts
• Velocity patterns (same card, many attempts)
• Mismatch between billing country and IP country

Add each new rule in flag mode first if your tool supports it, so you can watch it for a quarter before it starts blocking.

5. Assign owners and log decisions (10 min)

Every change gets a name and a one-line reason. No orphan rules.

The decision log template

Keep a simple running document. Each row:

This log is the single most valuable artifact the process produces. In six months, when someone asks "why do we block X?", you have the answer.

Common mistakes to avoid

• Only adding, never retiring. Rule sets bloat and start conflicting. Every review should retire at least one rule.
• Judging rules by block count. A rule that blocks a lot is not automatically good. Judge by *precision* — how many blocks were genuinely fraud.
• Skipping the support voice. Support hears the false positives you never see in the data. Their anecdotes are early signals.
• No flag-mode buffer. Rolling a new blocking rule straight to production is how you accidentally block a country's worth of good customers on launch day.

A lightweight scoring habit

Between reviews, resist the urge to add rules reactively after every single chargeback. Instead, keep a "candidate rules" list and let the quarterly review evaluate them together. This prevents knee-jerk rules that overlap or contradict each other. Layering an AI fraud score on top of your hard rules also helps — it catches the fuzzy cases your explicit rules miss, so your rule set can stay lean.

Make it stick

The hardest part is not the first review — it is the fourth. Put the meeting on a recurring calendar invite for the year, assign the data-pack owner permanently, and keep the decision log in a shared place everyone can find.

A tuned rule set quietly saves money every day. If you want the logs and rule-level activity that make this review painless, Shieldy — Fraud Filter gives you the visibility to run it in an hour a quarter. Start free and tighten from there.