Lending in 2025 looks vastly different from just a few years ago, influenced by factors including the rise in online lending, stricter regulation, and more sustainable lending practices. While predicting its future remains uncertain, one thing is clear: technology is driving the greatest change.
AI and credit decisions
Most obviously, artificial intelligence (AI) is changing how credit decisions are made, moving beyond simple automation to deliver sophisticated, multi-layered credit analysis. The result? Greater speed, more accuracy and improved efficiency.
In syndicated lending, AI models are processing troves of unstructured data from multiple sources to evaluate complex multi-party transactions. These systems can simultaneously analyse financial statements, market conditions, industry trends, and even ESG factors to provide comprehensive risk assessments in hours rather than the weeks that a traditional loan officer would take.
Commercial lending has seen perhaps the most dramatic transformation. AI systems are now integrating supply chain metrics, and market indicators to create dynamic risk profiles. Banks report faster credit decisions and a reduction in risk assessment costs as a result.
For consumer lending, AI has enabled lenders to go beyond traditional credit scoring by integrating multiple data points while staying compliant with regulations like GDPR. Modern systems analyse thousands of data points - from traditional credit scores to transaction patterns and social media footprints - to create highly accurate risk profiles, all while taking care adhere to regulations around transparency and user data. This has opened up lending to previously underserved segments while maintaining robust risk management.
The no-code revolution in lending
It may not grab the headlines as much as AI, but perhaps the most transformative trend is the shift toward no-code and low-code lending platforms.
Modern no-code platforms enable business users to do everything from modifying credit scoring models quicker to bringing new lending products to market quickly.
This has proven particularly valuable in commercial lending, where relationship managers can now customise lending solutions for specific industries or client segments.
The risk management revolution
Risk management has shifted from reactive to proactive. AI and predictive analytics now anticipate defaults months in advance by detecting subtle borrower behaviour changes and external risk factors. Risk signals are detected in advance, which allows lenders to decide on preventive actions. Lenders can then act pre-emptively—offering restructuring or payment plans—reducing default rates and strengthening borrower relationships.
What’s next?
For many, the biggest challenge now is capitalising on the many technological innovations on the market, ensuring that they bring business value. For those interested in trends beyond AI, I am also excited about identifying new trends that will increase transparency and security in loan origination, distribution, and management. The latter promises to boost protection against identity theft and fraud while streamlining digital loan applications. But for now, it’s all eyes on AI.
