##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:
Account owner demographics include gender distribution and average age. Transaction volumes include total income and expenses. Loan performance includes success rate calculated as successful loans divided by total loans. Statistics should be grouped by the year the account was opened.

##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: For accounts opened in Beroun after 1996, what are the yearly statistics including account owner demographics, transaction volumes, loan performance, and credit card distribution?
Evidence: Account owner demographics include gender distribution and average age. Transaction volumes include total income and expenses. Loan performance includes success rate calculated as successful loans divided by total loans. Statistics should be grouped by the year the account was opened.
Answer: Sorry, I cannot answer.
Permission: denied (Missing column permissions: account: account_id; loan: amount, duration)
Gold SQL: WITH AccountsInBeroun AS (
    SELECT 
        a.account_id,
        a.date,
        d.A2 AS district_name,
        STRFTIME('%Y', a.date) AS opening_year,
        a.frequency
    FROM 
        account AS a
    INNER JOIN 
        district AS d ON a.district_id = d.district_id
    WHERE 
        d.A2 = 'Beroun' AND STRFTIME('%Y', a.date) > '1996'
),
ClientsWithAccounts AS (
    SELECT 
        c.client_id,
        c.gender,
        c.birth_date,
        STRFTIME('%Y', 'now') - STRFTIME('%Y', c.birth_date) AS client_age,
        aib.account_id,
        aib.opening_year
    FROM 
        client AS c
    INNER JOIN 
        disp AS dp ON c.client_id = dp.client_id
    INNER JOIN 
        AccountsInBeroun AS aib ON dp.account_id = aib.account_id
    WHERE 
        dp.type = 'OWNER'
),
TransactionStats AS (
    SELECT 
        aib.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 
        AccountsInBeroun AS aib
    LEFT JOIN 
        trans AS t ON aib.account_id = t.account_id
    GROUP BY 
        aib.account_id
),
LoanInfo AS (
    SELECT 
        aib.account_id,
        COUNT(l.loan_id) AS loan_count,
        SUM(l.amount) AS total_loan_amount,
        AVG(l.duration) AS avg_loan_duration,
        SUM(CASE WHEN l.status = 'A' THEN 1 ELSE 0 END) AS successful_loans,
        SUM(CASE WHEN l.status = 'B' THEN 1 ELSE 0 END) AS running_loans,
        SUM(CASE WHEN l.status = 'C' THEN 1 ELSE 0 END) AS defaulted_loans
    FROM 
        AccountsInBeroun AS aib
    LEFT JOIN 
        loan AS l ON aib.account_id = l.account_id
    GROUP BY 
        aib.account_id
)
SELECT 
    COUNT(DISTINCT aib.account_id) AS total_accounts,
    aib.opening_year,
    AVG(CASE WHEN cwa.gender = 'M' THEN 1 ELSE 0 END) * 100 AS male_percentage,
    AVG(CASE WHEN cwa.gender = 'F' THEN 1 ELSE 0 END) * 100 AS female_percentage,
    AVG(cwa.client_age) AS avg_client_age,
    SUM(ts.transaction_count) AS total_transactions,
    SUM(ts.total_income) AS total_income,
    SUM(ts.total_expense) AS total_expense,
    SUM(ts.total_income) - SUM(ts.total_expense) AS net_balance,
    SUM(li.loan_count) AS total_loans,
    SUM(li.total_loan_amount) AS total_loan_amount,
    SUM(li.successful_loans) AS successful_loans,
    SUM(li.defaulted_loans) AS defaulted_loans,
    CASE 
        WHEN SUM(li.loan_count) > 0 THEN ROUND((SUM(li.successful_loans) * 100.0 / SUM(li.loan_count)), 2)
        ELSE 0 
    END AS loan_success_rate,
    COUNT(DISTINCT CASE WHEN c.type = 'gold' THEN c.card_id END) AS gold_cards,
    COUNT(DISTINCT CASE WHEN c.type = 'classic' THEN c.card_id END) AS classic_cards
FROM 
    AccountsInBeroun AS aib
LEFT JOIN 
    ClientsWithAccounts AS cwa ON aib.account_id = cwa.account_id
LEFT JOIN 
    TransactionStats AS ts ON aib.account_id = ts.account_id
LEFT JOIN 
    LoanInfo AS li ON aib.account_id = li.account_id
LEFT JOIN 
    disp AS d ON aib.account_id = d.account_id
LEFT JOIN 
    card AS c ON d.disp_id = c.disp_id
GROUP BY 
    aib.opening_year
ORDER BY 
    aib.opening_year;