##Instruction:
Database: financial
Total Tables: 8
Total Columns: 55

Table Schemas:

Database: financial
Total Tables: 8
Total Columns: 55

Table Schemas:

Table: account (4 columns)
--------------------------
• account_id (integer): the id of the account
• district_id (integer): location of branch
• frequency (text): frequency of the acount
• date (date): the creation date of the account
  Values: in the form YYMMDD

Table: card (4 columns)
-----------------------
• card_id (integer): id number of credit card
• disp_id (integer): disposition id
• type (text): type of credit card
  Values: "junior": junior class of credit card; 
"classic": standard class of credit card; 
"gold": high-leve...
• issued (date): the date when the credit card issued
  Values: in the form YYMMDD

Table: client (4 columns)
-------------------------
• client_id (integer): the unique number
• gender (text)
  Values: F：female 
M：male
• birth_date (date): birth date
• district_id (integer): location of branch

Table: disp (4 columns)
-----------------------
• disp_id (integer): unique number of identifying this row of record
• client_id (integer): id number of client
• account_id (integer): id number of account
• type (text): type of disposition
  Values: "OWNER" : "USER" : "DISPONENT"
commonsense evidence:
the account can only have the right to issue pe...

Table: district (16 columns)
----------------------------
• district_id (integer): location of branch
• A2 (text): district_name
• A3 (text): region
• A4 (text)
• A5 (text): municipality < district < region
• A6 (text): municipality < district < region
• A7 (text): municipality < district < region
• A8 (integer): municipality < district < region
• A9 (integer)
  Values: not useful
• A10 (real): ratio of urban inhabitants
• A11 (integer): average salary
• A12 (real): unemployment rate 1995
• A13 (real): unemployment rate 1996
• A14 (integer): no. of entrepreneurs per 1000 inhabitants
• A15 (integer): no. of committed crimes 1995
• A16 (integer): no. of committed crimes 1996

Table: loan (7 columns)
-----------------------
• loan_id (integer): the id number identifying the loan data
• account_id (integer): the id number identifying the account
• date (date): the date when the loan is approved
• amount (integer): approved amount
  Values: unit：US dollar
• duration (integer): loan duration
  Values: unit：month
• payments (real): monthly payments
  Values: unit：month
• status (text): repayment status
  Values: 'A' stands for contract finished, no problems;
'B' stands for contract finished, loan not paid;
'C' ...

Table: order (6 columns)
------------------------
• order_id (integer): identifying the unique order
• account_id (integer): id number of account
• bank_to (text): bank of the recipient
• account_to (integer): account of the recipient
  Values: each bank has unique two-letter code
• amount (real): debited amount
• k_symbol (text): purpose of the payment
  Values: "POJISTNE" stands for insurance payment
"SIPO" stands for household payment
"LEASING" stands for lea...

Table: trans (10 columns)
-------------------------
• trans_id (integer): transaction id
• account_id (integer)
• date (date): date of transaction
• type (text): +/- transaction
  Values: "PRIJEM" stands for credit
"VYDAJ" stands for withdrawal
• operation (text): mode of transaction
  Values: "VYBER KARTOU": credit card withdrawal
"VKLAD": credit in cash
"PREVOD Z UCTU" :collection from anot...
• amount (integer): amount of money
  Values: Unit：USD
• balance (integer): balance after transaction
  Values: Unit：USD
• k_symbol (text)
  Values: "POJISTNE": stands for insurrance payment
"SLUZBY": stands for payment for statement
"UROK": stands ...
• bank (text)
  Values: each bank has unique two-letter code
• account (integer)

##Evidence:
Card issued date refers to issued = '1996-10-21'; largest transaction refers to MAX(amount)

##Role Access Policy (Column-Level):
Role: RiskAnalyst
Accessible Columns: account: account_id, district_id, frequency; client: client_id, birth_date, district_id; district: ALL COLUMNS; loan: loan_id, account_id, date, amount, duration, payments, status; trans: account_id, date, type, operation, amount, balance, k_symbol

Based on the above schema and your role's column-level access policy, generate a SQL query to answer the question. If your role does not have access to the required columns, respond with: "Sorry, I cannot answer."


Question: For the client who received a credit card on October 21, 1996, what are the complete details of their largest transaction, including their personal information, district details, and any associated loans or orders?
Evidence: Card issued date refers to issued = '1996-10-21'; largest transaction refers to MAX(amount)
Answer: Sorry, I cannot answer.
Permission: denied (Missing column permissions: trans: trans_id; disp: account_id, client_id, disp_id; client: gender; card: card_id, disp_id, issued, type; order: account_id, bank_to, order_id)
Gold SQL: WITH TransactionStats AS (
    SELECT 
        T4.account_id,
        T4.trans_id,
        T4.amount,
        T4.type,
        T4.date,
        T4.balance,
        RANK() OVER (PARTITION BY T4.account_id ORDER BY T4.amount DESC) as amount_rank
    FROM trans AS T4
),
ClientCards AS (
    SELECT 
        T2.client_id,
        T3.account_id,
        T1.card_id,
        T1.issued,
        T1.type as card_type,
        T5.gender,
        T5.birth_date,
        (strftime('%Y', 'now') - strftime('%Y', T5.birth_date)) - 
            (strftime('%m-%d', 'now') < strftime('%m-%d', T5.birth_date)) as client_age
    FROM card AS T1
    JOIN disp AS T2 ON T1.disp_id = T2.disp_id
    JOIN account AS T3 ON T2.account_id = T3.account_id
    JOIN client AS T5 ON T2.client_id = T5.client_id
    WHERE T1.issued = '1996-10-21'
),
DistrictInfo AS (
    SELECT 
        d.district_id,
        d.A2 as district_name,
        d.A3 as region,
        d.A11 as avg_salary,
        d.A12 as unemployment_rate_95
    FROM district d
)

SELECT 
    cc.client_id,
    cc.card_id,
    cc.card_type,
    cc.gender,
    cc.client_age,
    di.district_name,
    di.region,
    ts.trans_id,
    ts.amount as largest_transaction_amount,
    ts.type as transaction_type,
    ts.date as transaction_date,
    ts.balance as balance_after_transaction,
    CASE 
        WHEN ts.amount > 10000 THEN 'High Value'
        WHEN ts.amount > 5000 THEN 'Medium Value'
        ELSE 'Low Value'
    END as transaction_category,
    CASE 
        WHEN l.loan_id IS NOT NULL THEN 'Has Loan'
        ELSE 'No Loan'
    END as loan_status,
    l.amount as loan_amount,
    o.order_id,
    o.bank_to
FROM ClientCards cc
JOIN TransactionStats ts ON cc.account_id = ts.account_id AND ts.amount_rank = 1
JOIN client c ON cc.client_id = c.client_id
JOIN DistrictInfo di ON c.district_id = di.district_id
LEFT JOIN loan l ON cc.account_id = l.account_id
LEFT JOIN "order" o ON cc.account_id = o.account_id
ORDER BY ts.amount DESC
LIMIT 1