##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:
Before 1997 does not include year 1997. PRIJEM means income transactions and VYDAJ means expense transactions.

##Role Access Policy (Column-Level):
Role: DataOperator_3
Accessible Columns: account: account_id, date, district_id; card: disp_id, issued, type; client: ALL COLUMNS; disp: account_id, type; district: A10, A11, A14, A16, A2, A3, A4, A5, A6, A7, A8, A9, district_id; loan: account_id, amount, date, duration, loan_id, payments; order: amount, k_symbol; trans: ALL COLUMNS

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 accounts with loans exceeding 24 months duration that were opened before 1997, provide comprehensive details about the account(s) with the smallest loan amount, including transaction history, card information, client demographics, and order activity.
Evidence: Before 1997 does not include year 1997. PRIJEM means income transactions and VYDAJ means expense transactions.
Answer: Sorry, I cannot answer.
Permission: denied (Missing column permissions: order: account_id; disp: A2, A3, client_id, disp_id, district_id; account: frequency)
Gold SQL: WITH AccountsWithLongLoans AS (
    SELECT 
        l.account_id,
        l.amount,
        l.duration,
        a.date AS account_opening_date,
        STRFTIME('%Y', a.date) AS opening_year,
        d.district_id,
        d.A2 AS district_name,
        d.A3 AS region
    FROM 
        loan AS l
    INNER JOIN 
        account AS a ON l.account_id = a.account_id
    INNER JOIN 
        district AS d ON a.district_id = d.district_id
    WHERE 
        l.duration > 24 
        AND STRFTIME('%Y', a.date) < '1997'
),
AccountTransactionStats AS (
    SELECT 
        a.account_id,
        COUNT(t.trans_id) AS transaction_count,
        SUM(CASE WHEN t.type = 'PRIJEM' THEN t.amount ELSE 0 END) AS total_income,
        SUM(CASE WHEN t.type = 'VYDAJ' THEN t.amount ELSE 0 END) AS total_expense,
        MAX(t.balance) AS max_balance
    FROM 
        AccountsWithLongLoans AS a
    LEFT JOIN 
        trans AS t ON a.account_id = t.account_id
    GROUP BY 
        a.account_id
),
AccountWithCards AS (
    SELECT 
        a.account_id,
        COUNT(c.card_id) AS card_count,
        GROUP_CONCAT(DISTINCT c.type) AS card_types
    FROM 
        AccountsWithLongLoans AS a
    INNER JOIN 
        disp AS d ON a.account_id = d.account_id
    LEFT JOIN 
        card AS c ON d.disp_id = c.disp_id
    GROUP BY 
        a.account_id
),
ClientInfo AS (
    SELECT 
        a.account_id,
        COUNT(DISTINCT c.client_id) AS client_count,
        SUM(CASE WHEN c.gender = 'M' THEN 1 ELSE 0 END) AS male_count,
        SUM(CASE WHEN c.gender = 'F' THEN 1 ELSE 0 END) AS female_count,
        AVG(CAST(STRFTIME('%Y', 'now') AS INTEGER) - CAST(STRFTIME('%Y', c.birth_date) AS INTEGER)) AS avg_age
    FROM 
        AccountsWithLongLoans AS a
    INNER JOIN 
        disp AS d ON a.account_id = d.account_id
    INNER JOIN 
        client AS c ON d.client_id = c.client_id
    GROUP BY 
        a.account_id
),
MinimumLoanAmount AS (
    SELECT 
        MIN(amount) AS min_amount
    FROM 
        AccountsWithLongLoans
),
RankedAccounts AS (
    SELECT 
        a.*,
        ts.transaction_count,
        ts.total_income,
        ts.total_expense,
        ts.max_balance,
        c.card_count,
        c.card_types,
        ci.client_count,
        ci.male_count,
        ci.female_count,
        ci.avg_age,
        RANK() OVER (ORDER BY a.amount ASC) AS amount_rank
    FROM 
        AccountsWithLongLoans AS a
    LEFT JOIN 
        AccountTransactionStats AS ts ON a.account_id = ts.account_id
    LEFT JOIN 
        AccountWithCards AS c ON a.account_id = c.account_id
    LEFT JOIN 
        ClientInfo AS ci ON a.account_id = ci.account_id
    WHERE 
        a.amount = (SELECT min_amount FROM MinimumLoanAmount)
)

SELECT 
    r.account_id,
    r.amount AS loan_amount,
    r.duration AS loan_duration_months,
    r.account_opening_date,
    r.district_name,
    r.region,
    CASE 
        WHEN r.transaction_count IS NULL THEN 0 
        ELSE r.transaction_count 
    END AS num_transactions,
    COALESCE(r.total_income, 0) AS total_income,
    COALESCE(r.total_expense, 0) AS total_expense,
    COALESCE(r.total_income, 0) - COALESCE(r.total_expense, 0) AS net_cash_flow,
    COALESCE(r.max_balance, 0) AS max_balance,
    COALESCE(r.card_count, 0) AS num_cards,
    COALESCE(r.card_types, 'None') AS card_types,
    COALESCE(r.client_count, 0) AS num_clients,
    COALESCE(r.male_count, 0) AS male_clients,
    COALESCE(r.female_count, 0) AS female_clients,
    COALESCE(r.avg_age, 0) AS average_client_age,
    (SELECT COUNT(*) FROM `order` o WHERE o.account_id = r.account_id) AS order_count
FROM 
    RankedAccounts r
WHERE 
    r.amount_rank = 1
ORDER BY 
    r.account_id ASC;