Kenyan banks are increasingly turning to artificial intelligence and machine learning to assess credit risk, with the technology emerging as the leading AI application in the country’s banking sector.
A Central Bank of Kenya (CBK) survey shows that 65 per cent of financial institutions using AI and machine learning apply the technology in credit risk assessment, putting loan evaluation ahead of cybersecurity and customer service.
The findings contained in the CBK Bank Supervision Annual Report 2025 examined how financial institutions were adopting artificial intelligence and the risks associated with the technology.
The survey was conducted in March 2025 and targeted commercial banks, mortgage finance institutions, Credit Reference Bureaus, microfinance banks and digital credit providers.
CBK said the survey aimed to assess AI adoption, identify its benefits and risks, and gather information to guide future policy.
“Artificial Intelligence (AI) technologies are increasingly being adopted across the Kenyan banking sector to improve operational efficiency, customer service, and risk management,” CBK said in the report.
AI Enters the Loan Assessment Process
Credit risk assessment emerged as the most common application of AI and machine learning among the institutions surveyed.
CBK reported that 65 per cent of the institutions used AI and machine learning for credit risk assessment.
Cybersecurity was the second-largest application at 54 per cent, while customer service accounted for 43 per cent.
The report also shows that the use of AI in lending is expected to grow further.
According to CBK, 83 per cent of institutions said they were likely to adopt AI for credit risk assessment in future.
A further 82 per cent indicated they were likely to adopt AI for cybersecurity, customer service and electronic Know Your Customer (e-KYC) solutions.
“The top three applications of AI and ML in the banking sector were credit risk assessment (65 percent), cybersecurity (54 percent), and customer service (43 percent),” the report said.
“Notably, 83 percent of institutions indicated that they were likely to adopt AI for credit risk assessment in future, and 82 percent for cybersecurity, customer service, and electronic Knowyour-Customer (e-KYC) solutions.”
The increasing use of technology comes as banks move towards more data-driven lending.
CBK’s risk-based credit pricing framework promotes the use of credit scoring models, high-quality data, and advanced analytics to assess borrowers.
“The framework promotes the use of robust credit scoring models, high-quality data, and advanced analytics to enhance risk assessment, improve pricing accuracy, and strengthen overall credit decision-making,” CBK said.
Under the framework, borrowers’ interest rates are expected to reflect their individual credit risk profiles rather than applying similar rates to all customers.
CBK said lower-risk customers could benefit from lower borrowing costs under the risk-based approach.
What AI looks at
The CBK report does not provide a single list of data points that every bank’s AI system uses to approve or reject a loan.
Instead, it identifies credit scoring, risk assessment, data and analytics as key components of the emerging data-driven lending model.
For mortgages, however, the CBK survey indicates the factors banks examine when assessing borrowers.
These include the borrower’s credit rating, ability to repay, income sustainability, repayment capability, employment details for salaried borrowers, credit history, and credit scores.
Banks also consider the ratio of monthly loan installments to disposable income, the loan-to-value ratio and the value and location of the property offered as security.
For businesses seeking mortgages, institutions examine factors including cash flows, financial performance, business turnover, past repayment records, projected income, business experience and industry performance.
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Half of Surveyed Institutions Have Adopted AI
The CBK survey found that 50 per cent of all institutions surveyed had adopted AI solutions.
Commercial banks recorded a higher adoption rate of 66 per cent, compared with 57 per cent among microfinance banks and 43 per cent among digital credit providers.
Credit Reference Bureaus were the exception, with all CRBs surveyed indicating that they had not adopted AI in their operations.
CBK said most institutions that had not adopted the technology were nevertheless exploring potential uses.
The report also found that AI adoption is outpacing formal governance structures in some institutions.
Only 30 per cent of institutions had formal AI strategies, although 62 per cent had data strategies and dedicated data or AI teams.
Institutions with formal AI strategies cited credit scoring, fraud detection and customer support chatbots among their applications.
Banks Face Risks as AI Use Expands
The growing use of AI also comes with risks.
CBK identified data quality, governance challenges, cybersecurity risks and dependence on third-party providers as common concerns.
Institutions also cited limited availability of AI-skilled staff, the high cost of AI, and data and regulatory compliance challenges.
The concerns are particularly relevant as banks increasingly depend on external technology providers.
A separate CBK survey found that all commercial banks and microfinance banks surveyed relied on third-party technology service providers in their operations.
The providers support areas including cloud services, mobile banking, internet banking and other technology functions.
Also Read: Why Kenyans Cannot Afford House Loans Despite Cheaper Mortgage Rates
CBK Plans AI Guidance for Banks
The increasing use of AI is also pushing the regulator towards new rules for the technology.
CBK said 93 per cent of respondents recommended that the regulator issue comprehensive guidance on AI.
The proposed guidance would cover governance and compliance, risk management, and incident management and reporting.
“The survey findings will enable CBK to develop a Guidance Note on AI for the banking sector,” the report said.
CBK said the guidance would cover “critical areas including data governance and AI governance strategies, AI risk mitigation measures, and interaction with third-party AI vendors.”
The regulator said AI was already benefiting financial institutions.
“AI has enhanced operational efficiency, improved decision-making, and enabled new financial products,” CBK said.
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