##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:
A2 refers to district names. PRIJEM refers to incoming transactions (credits), VYDAJ refers to outgoing transactions (debits). Net balance is calculated as total income minus total expense. Customer category is determined by loan count and transaction activity: High Activity (has loans and >10 transactions), Loan Customer (has loans), Active Customer (>10 transactions), or Regular Customer (others).

##Role Access Policy (Column-Level):
Role: DataOperator_2
Accessible Columns: account: account_id; card: card_id, disp_id, type; disp: account_id, client_id, disp_id; district: A10, A11, A12, A14, A15, A16, A2, A3, A4, A5, A6, A7, A8, district_id; loan: account_id, amount, duration, status; order: account_id, account_to, amount, k_symbol, order_id; 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 opened in Prachatice district, provide a comprehensive financial profile including account details, owner demographics, transaction statistics, loan information, customer categorization, and rank them by net balance from highest to lowest.
Evidence: A2 refers to district names. PRIJEM refers to incoming transactions (credits), VYDAJ refers to outgoing transactions (debits). Net balance is calculated as total income minus total expense. Customer category is determined by loan count and transaction activity: High Activity (has loans and >10 transactions), Loan Customer (has loans), Active Customer (>10 transactions), or Regular Customer (others).
Answer: Sorry, I cannot answer.
Permission: denied (Missing column permissions: district: account_id, client_id, disp_id, type; account: date, district_id; client: account_id, birth_date, client_id, gender; loan: loan_count, loan_id, loan_status, total_loan_amount)
Gold SQL: WITH AccountsInPrachatice AS (
    SELECT a.account_id, a.date, a.district_id
    FROM account AS a
    INNER JOIN district AS d ON a.district_id = d.district_id
    WHERE d.A2 = 'Prachatice'
),
ClientsWithPrachaticeAccounts AS (
    SELECT c.client_id, c.gender, c.birth_date, d.disp_id, d.account_id
    FROM client AS c
    INNER JOIN disp AS d ON c.client_id = d.client_id
    INNER JOIN AccountsInPrachatice AS a ON d.account_id = a.account_id
    WHERE d.type = 'OWNER'
),
TransactionStats AS (
    SELECT 
        t.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 trans AS t
    INNER JOIN AccountsInPrachatice AS a ON t.account_id = a.account_id
    GROUP BY t.account_id
),
LoanInfo AS (
    SELECT 
        l.account_id,
        COUNT(l.loan_id) AS loan_count,
        SUM(l.amount) AS total_loan_amount,
        CASE 
            WHEN MAX(CASE WHEN l.status = 'B' THEN 1 ELSE 0 END) = 1 THEN 'Has Default'
            ELSE 'No Default'
        END AS loan_status
    FROM loan AS l
    INNER JOIN AccountsInPrachatice AS a ON l.account_id = a.account_id
    GROUP BY l.account_id
)

SELECT 
    a.account_id,
    a.date AS opening_date,
    d.A2 AS district_name,
    d.A3 AS region,
    c.gender,
    strftime('%Y', 'now') - strftime('%Y', c.birth_date) - 
        (strftime('%m-%d', 'now') < strftime('%m-%d', c.birth_date)) AS client_age,
    COALESCE(ts.transaction_count, 0) AS transaction_count,
    COALESCE(ts.total_income, 0) AS total_income,
    COALESCE(ts.total_expense, 0) AS total_expense,
    COALESCE(ts.total_income, 0) - COALESCE(ts.total_expense, 0) AS net_balance,
    COALESCE(ts.max_balance, 0) AS max_balance,
    COALESCE(l.loan_count, 0) AS loan_count,
    COALESCE(l.total_loan_amount, 0) AS total_loan_amount,
    COALESCE(l.loan_status, 'No Loans') AS loan_status,
    CASE 
        WHEN COALESCE(l.loan_count, 0) > 0 AND COALESCE(ts.transaction_count, 0) > 10 THEN 'High Activity'
        WHEN COALESCE(l.loan_count, 0) > 0 THEN 'Loan Customer'
        WHEN COALESCE(ts.transaction_count, 0) > 10 THEN 'Active Customer'
        ELSE 'Regular Customer'
    END AS customer_category,
    ROW_NUMBER() OVER (ORDER BY COALESCE(ts.total_income, 0) - COALESCE(ts.total_expense, 0) DESC) AS balance_rank
FROM AccountsInPrachatice AS a
INNER JOIN district AS d ON a.district_id = d.district_id
LEFT JOIN ClientsWithPrachaticeAccounts AS c ON a.account_id = c.account_id
LEFT JOIN TransactionStats AS ts ON a.account_id = ts.account_id
LEFT JOIN LoanInfo AS l ON a.account_id = l.account_id
ORDER BY balance_rank;