##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:
Running loan contracts include status 'C' (running contract, OK so far) and status 'D' (running contract, client in debt). Remaining debt is calculated as loan amount minus total payments made (payments * duration).

##Role Access Policy (Column-Level):
Role: DataOperator_1
Accessible Columns: account: date, district_id, frequency; card: ALL COLUMNS; disp: ALL COLUMNS; district: A10, A13, A14, A16, A2, A5, A6, A7, A9, district_id; loan: account_id, date, loan_id, status; order: account_id, account_to, amount, bank_to, 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: What are the demographics and financial statistics of account owners with running loan contracts in district 1, including their average remaining debt, gender distribution, age, card ownership, transaction activity, and account balances?
Evidence: Running loan contracts include status 'C' (running contract, OK so far) and status 'D' (running contract, client in debt). Remaining debt is calculated as loan amount minus total payments made (payments * duration).
Answer: Sorry, I cannot answer.
Permission: denied (Missing column permissions: district: A11, A3, account_id, client_id, disp_id, type; account: account_id; client: birth_date, client_id, gender; loan: amount, duration, payments)
Gold SQL: WITH AccountsWithRunningLoans AS (
    SELECT 
        a.account_id,
        a.district_id,
        l.status,
        l.amount,
        l.duration,
        l.payments,
        (l.amount - (l.payments * l.duration)) AS remaining_debt
    FROM account AS a
    INNER JOIN loan AS l ON a.account_id = l.account_id
    WHERE a.district_id = 1 AND (l.status = 'C' OR l.status = 'D')
),
ClientDetails AS (
    SELECT 
        d.account_id,
        c.client_id,
        c.gender,
        strftime('%Y', 'now') - strftime('%Y', c.birth_date) AS client_age,
        COUNT(card.card_id) AS num_cards
    FROM disp AS d
    INNER JOIN client AS c ON d.client_id = c.client_id
    LEFT JOIN card ON d.disp_id = card.disp_id
    WHERE d.type = 'OWNER'
    GROUP BY d.account_id, c.client_id, c.gender, c.birth_date
),
TransactionStats AS (
    SELECT 
        account_id,
        COUNT(*) AS transaction_count,
        SUM(CASE WHEN type = 'PRIJEM' THEN amount ELSE 0 END) AS total_income,
        SUM(CASE WHEN type = 'VYDAJ' THEN amount ELSE 0 END) AS total_expense,
        MAX(balance) AS max_balance
    FROM trans
    GROUP BY account_id
)
SELECT 
    COUNT(DISTINCT arl.account_id) AS total_accounts_with_running_contracts,
    ROUND(AVG(arl.remaining_debt), 2) AS avg_remaining_debt,
    SUM(CASE WHEN cd.gender = 'M' THEN 1 ELSE 0 END) AS male_account_owners,
    SUM(CASE WHEN cd.gender = 'F' THEN 1 ELSE 0 END) AS female_account_owners,
    ROUND(AVG(cd.client_age), 0) AS avg_client_age,
    ROUND(AVG(cd.num_cards), 1) AS avg_cards_per_account,
    ROUND(AVG(CASE WHEN ts.transaction_count IS NOT NULL THEN ts.transaction_count ELSE 0 END), 0) AS avg_transactions_per_account,
    ROUND(AVG(CASE WHEN ts.max_balance IS NOT NULL THEN ts.max_balance ELSE 0 END), 2) AS avg_max_balance,
    d.A2 AS district_name,
    d.A3 AS region,
    d.A11 AS avg_salary_in_district
FROM AccountsWithRunningLoans AS arl
LEFT JOIN ClientDetails AS cd ON arl.account_id = cd.account_id
LEFT JOIN TransactionStats AS ts ON arl.account_id = ts.account_id
JOIN district AS d ON arl.district_id = d.district_id