Artificial Intelligence Adoption and the Financial Performance of Commercial Banks in Kenya (Journal of finance and accounting.)

Summary

• Average return on assets (ROA) of commercial banks in Kenya declined from 3.3 percent in 2021 to 2.6 percent in 2024.p.1
• The study evaluated a census of all 38 commercial banks licensed by the Central Bank of Kenya across 190 bank-year observations from 2020 to 2024.p.5
• AI-enabled customer service had a positive and statistically significant effect on bank return on assets (β = 0.927, p = 0.003).p.1
• Machine learning credit scoring (β = −0.046, p = 0.841) and AI-driven fraud detection (β = 0.137, p = 0.459) had no significant direct impact on bank profitability.p.1
• Robotic process automation displayed a negative coefficient (β = −0.450, p = 0.098) that was not statistically significant at the 5 percent level.p.1
• AI-enabled customer service significantly lowered the cost-to-income ratio (β = −0.194, p < 0.001), but operational efficiency did not mediate its effect on ROA (Sobel z = 1.287, p = 0.198).p.1

Key insights

1. Only customer-facing AI applications had a statistically significant positive impact on bank profitability in Kenya.p.1
2. Machine learning credit scoring did not significantly alter return on assets despite widespread deployment across digital lending products.p.1
3. Operational efficiency measured by the cost-to-income ratio did not significantly mediate the relationship between AI adoption and financial performance.p.1
4. Bank size exerted a strong direct positive effect on return on assets but did not moderate the returns gained from AI adoption.p.1
5. AI-driven fraud detection was the most widely adopted application, present in 82.6 percent of bank-year observations.p.12