Banks change criteria for loan applications! Credit score alone will no longer be enough
The number of people receiving rejections for loan and credit card applications despite having a high credit score is increasing. In this new era, banks are using not only credit scores but also customers' account activity, cash flow patterns, and financial behavior as decisive criteria in their lending decisions.
12punto
Across Turkey, the number of consumers whose loan or credit card requests are being turned down despite having a high credit score is increasing significantly.
With the new risk assessment model being implemented in the banking sector, credit evaluations are no longer based solely on a scoring system; the patterns of customers' account activity and cash flow over recent months have also become a decisive factor.
REJECTIONS ARE INCREASING
Recently, many people have been receiving rejections from banks despite having a good credit score. Financial institutions have begun to move beyond the classic scoring system to analyze account usage habits in greater depth.
In this context, regular income, the balance of expenditures, and the consistency of financial behavior are among the prominent criteria in the loan approval process.
"BEHAVIORAL RISK ANALYSIS" IS IN EFFECT
In the new system, a method called "behavioral risk analysis" is used to examine the nature of money entering and leaving the account in detail.
While salary payments, regular bills, and ordinary expenses are considered normal, frequent, unexplained transfers and sudden money movements are evaluated as risk factors.
VIRTUAL BETTING EXPENDITURES ARE A CRITICAL INDICATOR
In particular, regular payments made to virtual betting and gaming platforms are seen by banks as a strong risk signal. It is stated that loan and credit card applications can be rejected on the grounds that such transactions may weaken repayment capacity.
SUSPICIOUS MONEY MOVEMENTS ARE CAUGHT INSTANTLY
Banks carry out these audits largely through automated systems. AML software used in the fight against money laundering and financial crimes, along with artificial intelligence-supported analysis tools, can detect unusual transactions in a short time.
Customers identified with risky transactions are marked as "high risk" in the system, and this situation is directly reflected in credit processes.
In addition to data from the Central Bank Risk Center and the Credit Bureau (KKB), banks' own internal analyses are also effective in credit evaluations.
Artificial intelligence-based models shape the final decision on loan and credit card applications by scoring factors such as expenditures that do not align with income, irregular money traffic, and contact with high-risk sectors.