-- RISK002
DROP TABLE team_kingkong.tpap_risk002_breaches;

-- CREATE TABLE team_kingkong.tpap_risk002_breaches AS
INSERT INTO team_kingkong.tpap_risk002_breaches
with tpap_base as
(SELECT DISTINCT B.*, C.category, C.txn_type
, IF(D.upi_subtype IS NOT NULL, D.upi_subtype, IF(C.category = 'LITE_MANDATE', 'UPI_LITE_MANDATE', '')) AS upi_subtype
, D.payer_ifsc, D.payer_account_num
FROM
    (SELECT txn_id,
    MAX(CASE WHEN participant_type = 'PAYER' THEN vpa END) AS payer_vpa,
    MAX(CASE WHEN participant_type = 'PAYEE' THEN vpa END) AS payee_vpa,
    -- MAX(CASE WHEN participant_type = 'PAYER' THEN masked_account_number END) AS sender_masked_account_number,
    MAX(DATE(created_on)) as txn_date,
    MAX(amount) AS txn_amount,
    MAX(created_on) AS txn_time
    FROM switch.txn_participants_snapshot_v3
    WHERE DATE(dl_last_updated) BETWEEN DATE(DATE'2025-06-01' - INTERVAL '1' DAY) AND DATE'2025-06-30'
    AND DATE(created_on) BETWEEN DATE(DATE'2025-06-01' - INTERVAL '1' DAY) AND DATE'2025-06-30'
    GROUP BY 1)B
inner join
    (select txn_id, category, "type" AS txn_type
    from switch.txn_info_snapshot_v3
    where DATE(dl_last_updated) BETWEEN DATE(DATE'2025-06-01' - INTERVAL '1' DAY) AND DATE'2025-06-30'
    and DATE(created_on) BETWEEN DATE(DATE'2025-06-01' - INTERVAL '1' DAY) AND DATE'2025-06-30'
    and upper(status) = 'SUCCESS' AND "type" <> 'CREDIT') C
on B.txn_id = C.txn_id
INNER JOIN
    (SELECT txnid
    , regexp_replace(cast(json_extract(request, '$.evaluationType') as varchar), '"', '') AS upi_subtype
    , json_extract_scalar(request, '$.requestPayload.payerIfsc') AS payer_ifsc
    , json_extract_scalar(request, '$.requestPayload.payerAccountNum') AS payer_account_num
    FROM tpap_hss.upi_switchv2_dwh_risk_data_snapshot_v3
    WHERE DATE(dl_last_updated) BETWEEN DATE(DATE'2025-06-01' - INTERVAL '1' DAY) AND DATE'2025-06-30'
    AND (lower(regexp_replace(cast(json_extract(request, '$.requestPayload.payerVpa') as varchar), '"', '')) LIKE '%@paytm%'
    or lower(regexp_replace(cast(json_extract(request, '$.requestPayload.payerVpa') as varchar), '"', '')) like '%@pt%')
    AND json_extract_scalar(response, '$.action_recommended') <> 'BLOCK'
    AND regexp_replace(cast(json_extract(request, '$.requestPayload.payerType') AS varchar),'"','') = 'PERSON'
    AND regexp_replace(cast(json_extract(request, '$.requestPayload.payeeType') AS varchar),'"','') = 'PERSON'
    AND  regexp_replace(cast(json_extract(request, '$.evaluationType') as varchar), '"', '') = 'UPI_TRANSACTION')D
ON B.txn_id = D.txnid
WHERE (payer_vpa LIKE '%@paytm%') OR (payer_vpa LIKE '%@pt%')
AND payee_vpa LIKE '%@%')
 
SELECT * FROM
    (SELECT t1.payer_vpa,
      t1.payee_vpa,
      t1.txn_id,
      t1.txn_amount,
      t1.category,
      t1.upi_subtype,
      t1.payer_account_num,
      t1.payer_ifsc,
      t1.txn_time,
      t1.txn_date,
      SUM(t2.txn_amount) AS amt_24hr,
      100000 AS threshold_24hr
    FROM tpap_base t1
    INNER JOIN tpap_base t2
    ON t1.payer_account_num = t2.payer_account_num AND t1.payer_ifsc = t2.payer_ifsc
    AND t2.txn_time BETWEEN (t1.txn_time - INTERVAL '86400' SECOND) AND t1.txn_time -- 24 hr
    AND t1.txn_id <> t2.txn_id AND t1.txn_date BETWEEN DATE'2025-06-01' AND DATE'2025-06-30'
    GROUP BY t1.payer_vpa, t1.payee_vpa, t1.txn_id, t1.txn_amount, t1.category, t1.upi_subtype, t1.payer_account_num, t1.payer_ifsc, t1.txn_time, t1.txn_date
    )
WHERE (txn_amount + amt_24hr) > threshold_24hr;