Explaining Return on Assets of Government-Owned Universal Banks in the Philippines Using Murtini-Purnama-Lumbantobing Hypotheses

This study analyzed the financial performance of three government-owned universal banks in thePhilippines, namely Land Bank of the Philippines (LBP), Development Bank of the Philippines (DBP) andAl-Amanah Islamic Investment Bank of the Philippines (AAIIBP), from 2012 to 2022. Anchored in theMurtini-Purnama-Lumbantobing hypotheses, the study described the Return on Assets (ROA), CapitalAdequacy Ratio (CAR), and Operating Expense and Operating Income (BOPO) Ratio, Non-PerformanceLoans (NPL), and Interest Rate of the three banks over the study period. Furthermore, it examined theimpact of CAR and BOPO Ratio on ROA, as well as the mediating role of NPL and the moderating role ofInterest Rates on this relationship. Based on the results, policy recommendations were proposed.The study employed an ex-post facto research design, analyzing secondary data from financialstatements, Banks’ annual reports, and BSP reports. While the researcher computed ROA and BOPORatio, the CAR and NPL Ratios were directly sourced from the financial statements and annual reports.Data on Interest rates were derived from BSP's report on Domestic Interest Rates. Data gathered wereanalyzed through line graphs to visually present the trend, Generalized Linear Model (GLM) MediationAnalysis to determine whether the relationship between independent variables (CAR and BOP) on adependent variable (ROA) is mediated by an intermediate variable (NPL), and Moderation Analysis toexamine how the relationship between an independent variable (CAR) and a dependent variable (ROA)changes depending on the level of third variable, known as the moderator variable (Interest Rate).Findings revealed that AIB consistently exhibited negative ROA, highlighting profitabilitychallenges, while LBP and DBP showed positive, though generally below-industry-average, returns. LBPand DBP maintained CAR above the 10% BSP requirement despite fluctuations, while AIB's CAR sharplydeclined from 203.89% in 2012 to 3.43% in 2020. All three banks had higher BOPO ratios than theindustry average. NPL trends varied, with LBP and DBP fluctuating due to market conditions, and AIB'sNPL surging to 18.89% in 2022 after a period of near-zero NPLs. Interest rates, stable from 2012-2017,rose in 2018 due to inflation. CAR had a statistically significant negative impact on ROA (Estimate: -0.013, SE: 0.005, β: -0.124, z: -2.560, p = 0.010), as did BOPO (Estimate: -0.035, SE: 0.002, β: -0.928, z:-19.170, p < 0.001). NPL's mediating effect on both relationships was insignificant (p > 0.35). However,interest rates significantly moderated the CAR-ROA relationship (CAR*IR interaction: Estimate: 19.1631,SE: 8.5281, z: 2.247, p = 0.025). Based on these findings, the researcher proposed policyrecommendations intended to reduce NPLs, including integration of enhanced NPL data analytics and AIbased risk management and promotion of financial education programs for borrowers.