Artificial intelligence is changing how banks assess borrowers and manage lending risks. Indonesia’s Superbank is using AI and customer behaviour data to identify people who may be overlooked by traditional credit scoring systems. The approach aims to expand access to financial services while helping the bank develop better lending products and maintain credit quality.
AI reshapes lending decisions
PT Super Bank Indonesia, the country’s third-largest digital bank by assets, uses AI to analyse customer behaviour and identify patterns that conventional credit assessments might miss. These findings help the bank classify borrowers by risk, establish lending conditions and develop products for underserved customers. Speaking to Asian Banking & Finance, Chief Financial Officer Melisa Hendrawati explained that AI lets Superbank test lending assumptions and refine products faster.
However, human judgement remains essential when making credit decisions. Superbank continuously monitors its AI models for bias, performance and compliance with regulatory requirements. Every proposed AI project must also have clear business objectives and measurable targets before receiving approval. Initial pilot programmes determine whether the technology improves risk assessment, operational efficiency, and customer engagement.
Profitability remains a priority
Oki Stefanus, a partner at PT Ernst & Young Indonesia, warned that banks must demonstrate AI’s financial value rather than focus solely on reducing costs. Successful implementation requires stronger risk-adjusted returns, sustainable credit growth and consistent loan quality. Stefanus explained that alternative credit data alone offers little competitive advantage because many financial institutions can access similar information. What matters is how effectively banks turn that information into profitable lending decisions.
Digital banks may experiment faster, while traditional lenders benefit from established funding sources, risk management experience and customer relationships. Both experts emphasised the importance of controlled trials, regulatory compliance and long-term investment assessments. Ultimately, Hendrawati stressed that AI should support meaningful business goals rather than become a strategy in itself.
