Challenging Conventional Wisdom: Why Traditional Employ‎ment and Payment Behavioral Indicators Fail to Predict Financial Risk - Balcıoğlu, Yavuz Selim; Altındağ, Erkut; Karakaya, Turhan (International Journal of Accounting and Economics Studies, 2025)
This study examined behavioral patterns in financial risk assessment using a comprehensive dataset of 15,000 individual records to challenge conventional assumptions about employment stability and payment history as primary risk predictors. The analysis employed descriptive statistics, cross-tabulation methods, and comparative analysis across employment tenure categories, payment history classifications, and ‎employment status groups. Results revealed counterintuitive findings that fundamentally contradict established risk assessment theory. ‎Senior employees with 16 or more years of tenure demonstrated the highest risk rate at 10.7 percent, while veteran employees with 8-15 ‎years showed the lowest risk rate at 9.7 percent, directly challenging the linear relationship typically assumed between employment stability ‎and financial reliability. Payment history analysis revealed minimal risk differentiation across categories, with high risk rates ranging from ‎only 9.3 percent for excellent payment history to 10.4 percent for good payment history. Employment status comparisons showed nearly ‎identical risk profiles across unemployed, employed, and self-employed individuals, with high risk rates varying by less than one percentage ‎point. The most frequent high-risk behavioral combination was self-employed individuals with good payment history, representing a pattern ‎that contradicts conventional risk assessment logic. These findings suggest that traditional behavioral indicators may systematically misallocate risk across demographic segments and point toward the need for alternative risk assessment frameworks that incorporate behavioral ‎finance principles, real-time transactional data, and advanced analytical methodologies to improve accuracy and fairness in financial risk ‎evaluation‎.