SELECT '2022' AS year, Z.month, 'MIN + FULL' as kyc, Z.risk_catg, 'PerTxn' as Frequency, SUM(IF(Z.amt >= Z.limit, 1, 0)) AS breaches, 'egvRedeemTxnAmtPerTxn' as Rule FROM (SELECT A.user_id, A.txn_id, A.amt, month(A.txnTime) as month, IF(C.hml_category IS NOT NULL, C.hml_category, 'LOW RISK') AS risk_catg, CASE WHEN C.hml_category = 'HIGH RISK' THEN IF(10000 > (SUM(B.amt) * 0.7), 10000, (SUM(B.amt) * 0.7)) WHEN C.hml_category = 'MEDIUM RISK' THEN IF(15000 > (SUM(B.amt) * 0.8), 15000, (SUM(B.amt) * 0.8)) ELSE IF(20000 > SUM(B.amt), 20000, SUM(B.amt)) END AS limit FROM (SELECT DISTINCT user_id, transaction_id as txn_id, updated_at AS txnTime, execution_amount/100 as amt from egv.transaction_data where year = 2022 and operation like 'REDEEM%' AND response_code = 'SUCCESS' AND egv_transaction_state = 'SUCCESS')A INNER JOIN (SELECT DISTINCT user_id, card_number, original_balance/100 AS amt, created_at FROM egv.gift_cards WHERE year = 2022)B ON A.user_id = B.user_id AND ((UNIX_TIMESTAMP(A.txnTime) - UNIX_TIMESTAMP(B.created_at))/2592000) BETWEEN 0 AND 1 LEFT JOIN (SELECT DISTINCT senderuserid, hml_category FROM fraud.hml_classification)C ON A.user_id = C.senderuserid GROUP BY A.user_id, A.txn_id, A.amt, month(A.txnTime), C.hml_category)Z GROUP BY Z.month, Z.risk_catg