YITH WooCommerce Anti-Fraud scores every WooCommerce order against configurable rules: IP country mismatch, address mismatch, repeated email, high order value, prior chargeback. Each rule contributes to a numeric risk score, which lands in wp_postmeta on the shop_order post alongside the matched rule list and an overall fraud status.

The default WooCommerce orders screen shows the risk badge per row. There is no cross-order view of score distribution, no breakdown of which rules trigger most often, and no time-series view of fraud pressure over the month.

SleekView Charts reads the YITH meta keys directly. Risk score becomes a numeric column, fraud status becomes a groupBy dimension, and the rule list becomes a chartable distribution. The same dataset feeds the SleekView orders table, so the analyst can move from a Pie card to the underlying flagged rows without leaving the workspace.

YITH Anti-Fraud already does the hard work of scoring orders, attaching matched rules, and labelling a fraud status. The gap is in the admin: every signal lives per order, with no roll-up for the shop manager. SleekView Charts reads the YITH meta keys directly and aggregates them into Number, Pie, Bar, and Area cards.

Risk pressure becomes a trend instead of a stack of badges, rule frequency becomes a chart instead of a guess. The plugin keeps owning the scoring and the rule engine; the dashboard turns the output into something a team can run a shift around.