Interview: Sheikha Maryam Al Thani, CEO, Credit Bureau, on how advanced technologies are influencing regulations within the sector
How is the digitalisation of services influencing the way financial institutions assess creditworthiness?
SHEIKHA MARYAM AL THANI: Regulations issued by the Qatar Central Bank (QCB) have ensured user protection and identity verification, which are critical for the safe adoption of digital services. The QCB released guidelines on ethical artificial intelligence (AI) use in mid-2024, emphasising transparency, data privacy and model explainability. These standards have enabled banks to deploy AI models trained on expansive datasets from digital wallets and transaction logs, allowing for early identification of deteriorating credit profiles. The Regulatory Framework for Digital Banks mandates end-to-end digital processes, generating rich, real-time data that supports advanced credit scoring models. Traditional banks are also adopting cloud-based platforms and personal finance management tools to capture detailed spending behaviour for risk profiling. The QCB’s Data Handling and Protection Regulation further compels financial institutions to strengthen data governance and integrate alternative data sources, such as utility payments, into their credit assessments, expanding access to underserved segments.
What credit activity and borrower behaviour trends are emerging as the banking sector works towards Qatar National Vision (QNV) 2030 goals?
SHEIKHA MARYAM: Qatar is in pursuit of a 4.7% compound annual growth rate in financial services by 2030, and banks have seen shifts in credit activity and borrower behaviour. Lending is increasingly directed towards private firms, with a targeted 7% allocation for small and medium-sized enterprises (SMEs) to promote diversification and innovation. SME borrowers are typically younger and expect faster, digital-first credit processes. Consumers are also adopting digital borrowing habits, preferring mobile apps and automated credit scoring systems. The rise of buy now, pay later schemes and embedded finance models reflect this transition.
Credit growth is now concentrated in the services and trade sectors, while real estate lending, having contracted after the 2022 FIFA World Cup, began recovering in mid-2024. Private sector credit expansion, recorded at 5% annual growth, signals a transition toward a more diversified economy with reduced reliance on public-sector financing.
In what ways can lenders use advanced data analytics and AI in credit risk assessment?
SHEIKHA MARYAM: Enhanced credit scoring, real-time risk monitoring, automation, fraud detection and predictive analytics are key opportunities for the use of advanced data analytics and AI in credit risk assessment. AI allows banks to analyse alternative and behavioural data, providing more accurate risk profiles and enabling financial inclusion for thin-file customers. Real-time monitoring updates borrower profiles dynamically, supporting early interventions. Automation speeds up low-risk credit decisions, reduces operational costs and scales lending efficiently. Advanced fraud detection tools enhance transaction monitoring, while predictive analytics enable early identification of potential defaults, allowing proactive credit management.
How has economic adjustment affected borrower risk profiles following the 2022 FIFA World Cup?
SHEIKHA MARYAM: After the sporting event, economic adjustment has increased real estate and construction credit risks. Early signs of rising non-performing loans have emerged, prompting banks to restructure loans and tighten underwriting standards. There is a rebalancing of credit towards logistics, tourism, manufacturing and digital infrastructure to align with diversification strategies under QNV 2030. Banks are deploying AI-driven monitoring tools and stress-testing frameworks to track borrower vulnerabilities and anticipate defaults, bolstering the resilience of their portfolios amid a shifting economic landscape.
Read More from OBG
