Creating a competitive advantage for financial institutions with smarter lending solutions

Shivani Landie talks digital and disruption, and how South African financial institutions can create fast and affordable solutions that make lending a competitive advantage

South African credit-active consumers grew by 4.7% year-on-year to R18.5 million people in 2024 with credit to the private sector increasing by 4.98% yoy in May 2025. In 2024, major banks reported a 5.4% annual growth in gross loans and advances, reflecting this increased demand and growth and an uptick in sector optimism. However, as fintech players continue to gain ground and momentum, traditional lenders face mounting cost pressures, a shrinking talent pipeline and growing consumer credit expectations. There’s an opportunity here for these institutions to retool their lending strategies with data, automation and digital trust, gaining market share while building customer stickiness in a highly competitive market.

The race to capture South Africa’s evolving credit market is on. The lean, mobile-first and data-savvy fintech is transforming how lending is delivered while traditional institutions are being pushed to reassess the foundations on which their credit strategies were built. Fintech players have shown just how quickly digital adoption can scale and continue to attract capital and policy attention. New entrants leverage tools like behavioural data, embedded payments and real-time scoring tools to underwrite risk with increasing precision, often with lower overheads than legacy institutions.

While this shift has driven innovation, it has also exposed structural tensions within the lending ecosystem. Chief among them is the assumption that digital equals better. For many banks, replicating fintech UX or launching instant loan offerings isn’t enough because credit products are only as strong as the systems, strategies and safeguards that support them.

The reality is that while the consumer appetite for credit is growing, so are the vulnerabilities. Alongside the uptick in demand for personal loans, home finance and credit cards, delinquencies have climbed just as fast. According to TransUnion, more than two in five South Africans holding a personal loan have been in arrears for three months or more. This duality – a booming demand curve set against rising repayment stress – puts lenders in a complex position. Extending access too liberally can threaten margins and compliance, but limiting credit too conservatively risks irrelevance.

Resolving this tension asks that financial institutions prioritise more precise and resilient credit architectures which rethink the mechanisms traditionally used to manage credit decisioning. Many banks still rely on static scoring models and dated assumptions about income, affordability and behavioural risk, and these are increasingly misaligned with the complexity of today’s borrowers.

South Africans are juggling multiple income sources, informal work and fluctuating debt loads, and legacy systems aren’t equipped to interpret these signals in real time.

Compounding this challenge is a growing shortage of skilled credit professionals. Only 15% of the population has basic ICT skills and 5% have advanced digital competencies, with companies reporting severe shortages in AI, data analytics and digital finance expertise. For institutions wanting to transform and build robust digital foundations, the talent gap is becoming a structural constraint.

One area where this tension is especially acute is in collections. Traditional approaches such as phone calls, letters and legal escalations are no longer sustainable at scale. Legal recovery costs often exceed the debt value and third-party agents charge steep commissions with variable results. Some institutions are now using segmentation, predictive analytics and self-service platforms to overhaul early-stage engagement. Some financial institutions have had impressive results by resolving payment issues through self-service, which has improved customer stickiness and improved recovery rates.

However, efficiency is only one part of the equation, the most important challenge to overcome (and the biggest opportunity) is trust. In an increasingly digital lending environment, the questions of fairness, transparency and explainability have moved to the fore. How does a borrower know why they were declined? What governance protects them from biased models or opaque risk categorisations?

Research from Cornel University has shown that when services from financial institutions are personalised, they enhance and build customer trust. And the more people trust, the more they are open to sharing data, exploring new offerings and becoming a deeper part of the financial ecosystem. And this is where the new edge lies, in building systems that are responsible and accountable and that leverage customer data to create continuous learning loops that adapt to market and customer shifts in real time.

This doesn’t mean compromising risk management. It’s more about focusing on how to define what risk looks like in a digital-first world and moving towards dynamic, outcome-led design and systems that can balance commercial growth with ethical responsibility.

Meeting these challenges asks that institutions access deep specialisation in credit decisioning, advanced data analytics and applied AI. The most effective support combines regulatory fluency, mathematical modelling expertise, and a proven ability to translate data into real-world lending and collections strategies. This includes designing predictive models that capture changing risk, optimising credit limit and pricing strategies, and orchestrating decision flows that remain explainable under scrutiny.

In a market where operational outcomes must be precise, measurable and ethical, these capabilities will define the next wave of sustainable lending, providing support and trust to borrowers and institutions alike.