##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:
PRIJEM refers to incoming transactions (credits), VYDAJ refers to outgoing transactions (debits). Expense to income ratio is calculated as (total expenses / total income) * 100.

##Role Access Policy (Column-Level):
Role: LoanOfficer
Accessible Columns: account: account_id, district_id, frequency, date; client: client_id, district_id; disp: disp_id, client_id, account_id, type; loan: ALL COLUMNS; trans: account_id, date, type, amount, balance

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 applied for a 98832 USD loan on January 3rd, 1996, provide a comprehensive profile including their birthday, age at the time of loan application, location, transaction history before the loan, expense-to-income ratio, balance range, credit card information, and number of previous loans.
Evidence: PRIJEM refers to incoming transactions (credits), VYDAJ refers to outgoing transactions (debits). Expense to income ratio is calculated as (total expenses / total income) * 100.
Answer: Sorry, I cannot answer.
Permission: denied (Missing column permissions: trans: trans_id; disp: A2, A3, district_id; client: birth_date, gender; card: card_id, disp_id, type)
Gold SQL: WITH LoanClient AS (
    SELECT 
        T1.loan_id,
        T1.account_id,
        T1.date AS loan_date,
        T1.amount,
        T1.duration,
        T1.payments,
        T1.status,
        T4.client_id,
        T4.birth_date,
        T4.gender,
        T4.district_id AS client_district_id,
        T2.district_id AS account_district_id,
        CAST(strftime('%Y', T1.date) AS INTEGER) - CAST(strftime('%Y', T4.birth_date) AS INTEGER) - 
            CASE WHEN strftime('%m%d', T1.date) < strftime('%m%d', T4.birth_date) THEN 1 ELSE 0 END AS age_at_loan
    FROM loan AS T1 
    INNER JOIN account AS T2 ON T1.account_id = T2.account_id 
    INNER JOIN disp AS T3 ON T2.account_id = T3.account_id AND T3.type = 'OWNER'
    INNER JOIN client AS T4 ON T3.client_id = T4.client_id
    WHERE T1.date = '1996-01-03' AND T1.amount = 98832
),
ClientTransactions AS (
    SELECT 
        LC.client_id,
        LC.birth_date,
        LC.age_at_loan,
        COUNT(DISTINCT 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,
        MIN(t.balance) AS min_balance,
        d.A2 AS district_name,
        d.A3 AS region
    FROM LoanClient LC
    JOIN account a ON LC.account_id = a.account_id
    LEFT JOIN trans t ON a.account_id = t.account_id AND t.date < LC.loan_date
    LEFT JOIN district d ON LC.client_district_id = d.district_id
    GROUP BY LC.client_id, LC.birth_date, LC.age_at_loan, d.A2, d.A3
),
CardInfo AS (
    SELECT 
        LC.client_id,
        COUNT(DISTINCT c.card_id) AS card_count,
        GROUP_CONCAT(DISTINCT c.type) AS card_types
    FROM LoanClient LC
    JOIN disp d ON LC.client_id = d.client_id
    LEFT JOIN card c ON d.disp_id = c.disp_id
    GROUP BY LC.client_id
)
SELECT 
    CT.birth_date,
    CT.age_at_loan,
    CT.district_name,
    CT.region,
    CT.transaction_count,
    CT.total_income,
    CT.total_expense,
    CASE 
        WHEN CT.total_income > 0 THEN ROUND((CT.total_expense * 100.0) / CT.total_income, 2)
        ELSE 0 
    END AS expense_to_income_ratio,
    CT.max_balance,
    CT.min_balance,
    COALESCE(CI.card_count, 0) AS card_count,
    COALESCE(CI.card_types, 'None') AS card_types,
    (SELECT COUNT(*) FROM loan l 
     JOIN account a ON l.account_id = a.account_id
     JOIN disp d ON a.account_id = d.account_id
     WHERE d.client_id = CT.client_id AND l.date < '1996-01-03') AS previous_loans
FROM ClientTransactions CT
LEFT JOIN CardInfo CI ON CT.client_id = CI.client_id
ORDER BY CT.birth_date;