For decades, credit risk has been the backbone of lending and banking decision-making, balancing opportunity and caution to support customers, safeguard portfolios, and fuel economic growth. But as the financial landscape shifts, some in the industry are asking the provocative question “Is traditional credit risk losing its relevance?”

While “traditional credit risk is dead” might be an overstatement, it is hard to ignore the way emerging and competing risks are reshaping priorities. Regulation now influences not just what we do, but how and when we do it. Reputational risk has grown in importance in a world where a single misstep can spread across social media in minutes. Cyber threats target the systems and data our models rely on, making security a core part of risk management.

For much of the past 15 years, credit risk conditions have been remarkably stable, with historically low arrears across most lending sectors. While this has been good news for balance sheets, it has also led to a quiet side effect, a lack of investment in both training for credit risk teams and the tools needed to support more sophisticated decision-making. Many teams have been operating with legacy systems and processes that were “good enough” in benign conditions but may struggle to meet the demands of a more volatile environment.

At the same time, the role of collections is shifting. The rising cost of living and a tougher economy means more customers will need support. This creates a dual challenge: protecting portfolio performance while also meeting the growing expectations around how lenders treat vulnerable customers. Collections can no longer be a back-office function; it must evolve into a frontline capability using data to identify early signs of stress, embedding hardship frameworks that are flexible and transparent, and equipping staff to respond with empathy. 

Those who get this right will not only manage arrears more effectively but will also build deeper trust and loyalty by showing customers that support is genuine when it matters most.

The future of credit risk also requires a cradle-to-grave approach, one that views credit and collections as a single continuum rather than separate functions. Supporting customers through the entire lending lifecycle means aligning risk appetite, decisioning, monitoring, and collections into a cohesive strategy. From the moment a loan is approved, lenders need to think about how they will help customers succeed, what early warning signs of stress to watch for, and how to step in with meaningful support if hardship arises. This isn’t about softening risk discipline; it’s about building a lifecycle strategy that protects portfolios while also guiding customers responsibly through good times and bad.

The sector is also navigating deeper, more structural changes. Climate change is affecting asset values, insurance cover, and long-term business viability. The credit cycle is shifting, requiring institutions to reset risk appetite in the face of slower growth, changing interest rates, and evolving borrower behaviour. A slowing housing market is testing traditional lending models, while softer economic conditions demand that lenders find ways to support businesses without compromising prudence. Technology and data are opening the door to greater efficiency and deeper insight, but they also require a careful balance between automation and the human judgement that underpins sound credit decisions.

Artificial intelligence is adding another layer of change. AI is already being applied to improve credit scoring models, detect fraud in real time, and predict emerging risks before they appear on a balance sheet. For credit risk departments, this technology has the potential to transform processes replacing manual tasks, enabling faster and more accurate decision-making, and unlocking new data sources. But it also raises important questions: how do we ensure transparency and fairness in AI-driven decisions? What governance is required to manage model risk? And crucially, what skills will credit risk professionals need in this new environment?

Fraud is an equally critical part of this conversation. Periods of economic pressure tend to increase the temptation and opportunity for fraudulent behaviour. We’re already seeing signs of “liar loans,” where borrowers deliberately misstate income, expenses, or employment status to obtain credit. With more applications being processed digitally, identity fraud and synthetic identities are becoming harder to detect, particularly if lenders are relying on outdated verification systems. The intersection of fraud prevention and credit risk assessment has never been more important. Robust detection tools, cross-department collaboration, and the integration of fraud analytics into lending decision frameworks will be essential for protecting both customers and balance sheets.

Demographics are also reshaping both sides of the equation, customers and credit risk teams alike. Lending preferences among younger generations are changing rapidly. Millennials and Gen A often view traditional lending products, such as long-term credit cards or mortgages, as restrictive or inaccessible. At the same time, their appetite for digital-first, flexible products like Buy Now, Pay Later continues to grow. This shift challenges lenders to rethink product design, affordability assessment, and risk appetite. It also raises important questions for credit risk leaders: how do we responsibly underwrite for customers who reject the very products that once defined retail banking? And how do we ensure these choices don’t translate into higher default risk down the line?

Meanwhile, the demographic profile of credit risk teams themselves is shifting. Many experienced professionals who built their careers in the stability of the last credit cycle are nearing retirement, while the next generation is stepping into leadership with different skills, expectations, and mindsets. This presents both a challenge and an opportunity: how do we transfer deep institutional knowledge while also embracing new capabilities that the future demands?

The future will demand teams that can not only interpret financial risk but also understand data science principles, challenge AI outputs, and bridge the gap between technical modelling and regulatory expectations. It will require professionals who can combine traditional credit expertise with fluency in technology, ethics, and change management.

It is important that we openly discuss these challenges and the opportunities they present. Credit risk is not disappearing, it is evolving. The challenge for today’s professionals is to integrate new considerations without losing sight of the fundamentals. That means building resilience into strategies, stress-testing portfolios for new threats, and rethinking how we measure, monitor, and manage credit exposures in a more complex and technology-driven world.

The 2026 Credit Risk & Fraud Summit will bring together industry leaders, regulators, and innovators to share insights, debate approaches, and map out what best practice will look like in the next decade. It is a learning and development opportunity for the entire sector. Across the programme, we will explore how to reset risk appetite in a tougher environment, how to utilise AI responsibly, how to align fraud prevention with credit strategy, and how to build resilient teams ready for demographic and technological change.