The key trends redefining credit risk
in European banking
Credit risk management is undergoing a major transformation as banks adapt to a more complex and uncertain environment. Institutions are increasingly leveraging forward-looking capabilities, advanced analytics and expanded risk frameworks to improve decision-making and strengthen resilience. Banks that combine strong risk discipline with data-driven insights are better positioned to remain competitive in a rapidly evolving financial landscape.
Data Integration and Automation in Credit Risk
Banks are accelerating the adoption of data integration, automation and predictive early‑warning systems, enabling faster, more consistent and forward‑looking decision-making.
Credit Risk Role in Capital Steering
66% of respondents already support senior management with forward‑looking RWA and scenario insights, highlighting a clear shift toward a more strategic role in capital planning.
Technology Investment in Banking
Investment in automation, real-time monitoring and advanced capabilities continues to increase, yet legacy systems, budget constraints and competing priorities remain key obstacles.
AI Adoption in Credit Risk
AI use cases are expanding across early warning, scoring and process automation; however, scaling remains constrained by data quality, explainability and integration challenges.
ESG and Structural Risk Drivers
ESG, climate risk and alternative data are becoming increasingly embedded in credit decision-making, driving more integrated and forward‑looking risk strategies.
Sector-Focused Credit Risk Models
Institutions are evolving toward sector-focused models, enhanced client experience and more differentiated pricing approaches, positioning credit risk as a value‑driven function.
Strategic priorities in Credit Risk for European Banks
European banks are operating in a credit risk environment shaped by persistent macroeconomic pressures, evolving regulatory expectations and rapid technological change. High interest rates, inflation and sector-specific vulnerabilities are increasing the need for more forward-looking, data-driven credit risk processes.
At the same time, the integration of ESG, digital transformation and AI is reshaping core credit risk activities, from origination to portfolio management. These dynamics are raising the bar for credit risk functions, which must balance regulatory compliance, resilience and strategic decision support. This context sets the foundation for the key trends identified in the survey.
What are the top 3 strategic priorities for your bank’s credit risk function (either 1.5 or 2 LoD) over the next 12–24 months?
The survey results highlight a clear set of top strategic priorities for European banks.
Improving data integration and automation emerges as the most frequently selected priority (26%), closely followed by enhancing credit monitoring and early warning capabilities (21%), strengthening origination and underwriting standards (13%).
These top priorities are followed by integrating ESG and climate risks, as well as adapting to geopolitical risks (each 11%), adapting to CRR III and new regulatory requirements (9%), expanding structured credit and risk transfer capabilities (7%) and additionally, 2% of respondents selected others.
Idea in motion
Banks are primarily focused on building stronger data and analytical foundations and evolving towards earlier, more forward‑looking risk detection.
The findings
The evolving role of the credit risk function continues to stand at the forefront of regulatory expectations and strategic decision‑making, reflecting growing demands for forward‑looking risk management and enhanced support to senior leadership.
The results
The results show that most European banks are moving beyond a purely regulatory view of RWA, increasingly positioning the credit risk function as a strategic partner to senior management in shaping forward-looking RWA expectations and scenario-based insights.
Investment in technology as a top priority in Credit Risk for European Banks
Technology is playing an increasingly central role in credit risk transformation, with banks focusing on areas that enhance efficiency, predictive capabilities and decision-making.
Which areas of your credit risk function would benefit most from technological enhancement?
The study reveals that European banks are prioritising automation, predictive capabilities and real-time insights as the key drivers of technological progress within credit risk functions.
Credit decisioning automation is the top priority (29%), reflecting the need for faster, more consistent and data-driven credit decisions, followed by Early Warning Systems with predictive triggers (23%), showing strong interest in strengthening early-stage risk detection. Real-time credit risk monitoring and dashboarding (14%) completes the top three areas identified for enhancement.
These are followed by on-demand stress testing and scenario simulation (12%), watchlist and monitoring tools (9%), AI-infused business plan projection for SME/mid cap clients (7%), and ESG/climate risk integration into credit assessment (6%).
The survey results clearly highlight the areas where banks expect the greatest impact from technological improvements.
Benefits of Investing in Advanced Credit Risk Technology
Banks are primarily targeting operational efficiency, improved decision quality and stronger predictive capabilities through investment in advanced credit risk technology.
The survey results confirm this focus. Reducing manual workload and operational risk ranks as the top expected benefit (22%), followed by faster and more consistent credit decisions (21%) and improved predictive accuracy and early detection of distress (19%).
Additional benefits include improved client experience (14%), more accurate pricing (7%) and better alignment with strategic planning and capital allocation (7%). Institutions also highlight gains in transparency and auditability (6%) and cross-selling opportunities (4%).
This highlights a clear focus on efficiency, consistency and predictive performance as the core value drivers of technology investment.
What benefits do you expect from investing in advanced credit risk technology?
Investment Appetite, Budget Constraints and Barriers in Credit Risk
European banks are demonstrating a growing commitment to investing in credit risk innovation, particularly across AI, data infrastructure and decisioning platforms. However, this investment appetite is not uniform and is increasingly shaped by internal budget constraints, competing priorities and structural challenges.
Understanding how banks allocate funding—and what prevents them from investing more—provides critical insight into the pace and direction of credit risk transformation across the sector.
Does your bank have a dedicated budget for credit risk innovation?
Budget allocation patterns reveal important differences in how banks are approaching credit risk innovation.
From the responses gathered, 28% of banks prioritise AI and analytics tooling, focus on data infrastructure and prioritise credit decisioning platforms (each 22%). Finally, 20% of respondents report not having a dedicated budget and 8% allocate their budget to staff training, risk culture and capability building.
The results reveal a sector that is clearly investing, yet doing so with diverse speeds and priorities ranging from banks that are rapidly accelerating their digital transformation to those still consolidating foundational elements before scaling innovation.
Idea in motion
Despite the growing commitment to strengthening credit‑risk capabilities across Europe, institutions continue to face structural and organisational constraints that influence the pace and scale of their investment decisions.
The findings
Competing internal priorities (30%) and budget constrains (28%) stand out as the most significant barriers, followed by legacy systems coupled with data fragmentation. Regulatory uncertainty and limited internal expertise appears each with 7% of responses.
The results
The findings reveal a sector that is clearly committed to modernizing its credit risk capabilities yet progressing at different speeds. Some institutions are rapidly advancing digital transformation initiatives, while others are still addressing foundational or resource related hurdles before scaling innovation.
Alternative Lending, Risk Transfer and Structuring in Credit Risk
European banks are increasingly exploring alternative lending instruments and structuring approaches to optimise balance sheets, enhance capital efficiency and diversify risk exposure. However, adoption remains uneven, reflecting different levels of maturity, strategic focus and risk appetite across institutions.
Is your bank actively exploring or using alternative lending models/ instruments?
The survey reveals a clear division between institutions experimenting with alternative lending models and those taking a more conservative stance. With 32% of respondents engaging in synthetic risk transfer, while another 32% are not exploring such models. Meanwhile, 13% of institutions are adopting originate‑to‑securitise approaches and another 11% are using originate‑to‑distribute frameworks. Fund‑based lending structures account for a smaller share of activity and other alternatives (each 6%).
As European banks reassess their balance‑sheet strategies amid evolving market dynamics and regulatory expectations, the exploration of alternative lending models has increasingly emerged as a potential lever for risk transfer, capital efficiency and portfolio diversification.
Overall, the findings show that although the sector is clearly investing in innovative lending structures, progress remains uneven. Some banks are moving decisively toward more sophisticated balance‑sheet optimisation tools, while others continue to consolidate foundational processes before embracing alternative models at scale.
Regulatory and Supervisory Challenges in Credit Risk for European Banks
European banks are operating under an increasingly demanding regulatory and supervisory environment, where heightened scrutiny, complex requirements and evolving expectations are placing significant pressure on credit risk functions. These challenges are not only absorbing internal resources but also influencing how banks prioritise data, governance and risk management practices.
What are the main challenges your bank faces in light of the current supervisory and regulatory environments?
Closely behind, 22% of institutions point to data and reporting burdens, underscoring persistent challenges with data quality, availability, and the operational effort needed to meet evolving regulatory expectations. 19% highlight the complexity and fragmentation of regulatory requirements.
A further 17% of respondents emphasize supervisory pressure related to provisioning, classification or underwriting standards, which remains a key area of focus under both existing and forthcoming frameworks and 14% cite uncertainty around new rules, including those linked to CRR III, ESG, and AI‑related expectations while a further 1% selected other.
Idea in motion
The survey highlights a set of supervisory and regulatory pressures that continue to shape banks’ credit risk agendas.
The findings
The most frequently cited challenge is the intensity of supervisory inspections and requests, selected by 27% of respondents, reflecting the significant internal resources required to meet ongoing supervisory scrutiny.
The results
These findings point to a landscape in which regulatory demands continue to grow in scope and sophistication, placing pressure on banks’ data, governance, and operational risk management capabilities, reinforcing the need for more integrated, streamlined regulatory processes.
Geopolitical and Macroeconomic Risks in Credit Risk Management
As European banks navigate an increasingly complex macroeconomic landscape, understanding the expected time horizons of key headwinds has become essential for anticipating credit risk pressures and shaping resilient risk management strategies.
Across the different scenarios assessed, banks report varying time horizons for the expected impact:
When considering the transition to and implementation of the ESG agenda, 45% of institutions see the effects as medium-term, 26% as short-term and 29% as long-term.
Under the cost-of-living scenario, driven by high inflation and interest rates, 59% of respondents expect medium-term impacts, 23% short-term effects, 15% see it as not applicable and 3% anticipate long-term implications.
Geopolitical uncertainty is predominantly viewed as a short-term risk, with 57% highlighting immediate effects, 31% assessing it as medium-term followed by 10% as long-term and 2% see it as not applicable.
In the scenario linked to the ongoing impacts of the pandemic, 88% of banks consider the effects no longer applicable, while 6% still perceive short-term repercussions and another 6% as long-term.
As of today, what are your perspectives on the impacts/implications of the following macroeconomic headwinds?
The results show that banks clearly distinguish between macroeconomic forces with structural implications (such as ESG transition and persistent cost of living pressures) and risks perceived as more immediate or cyclical, such as geopolitical tensions.
Pandemic related impacts have largely faded from the risk horizon, underscoring a shift in focus toward more enduring and forward-looking drivers of credit risk evolution.
As macroeconomic and geopolitical pressures intensify, banks are increasingly required to embed these external risk drivers directly into their credit risk frameworks to ensure timely monitoring, forward‑looking assessments and enhanced portfolio resilience.
AI Adoption in Credit Risk Management in Banking
Artificial Intelligence is rapidly reshaping credit risk functions, enabling banks to enhance predictive capabilities, automate data-intensive processes and improve decision-making across the credit lifecycle. While adoption is gaining momentum, its application remains uneven, reflecting differences in data maturity, technological readiness and regulatory considerations.
In which areas is your bank currently applying or exploring AI in credit risk?
AI is most commonly applied or explored in early warning signal detection (29%), highlighting a growing emphasis on anticipating credit deterioration before it materialises.
Document analysis and data extraction (28%) and credit scoring and underwriting (27%), while 8% of institutions report not yet applying AI within their credit risk processes.
Only 5% of respondents selected other while a further 3% report AI use in portfolio segmentation or behavioural modelling, indicating that adoption in these areas remains at an early stage.
Idea in motion
AI is increasingly becoming a strategic focus within credit risk functions, as institutions seek to enhance their analytical capabilities, automate processes, and strengthen early-stage risk identification.
The findings
As AI adoption expands, banks are exploring the use of AI across multiple stages of the credit risk lifecycle. The survey indicates that AI adoption in credit risk is steadily advancing, with banks broadening its application from early-stage risk detection towards more sophisticated analytical and underwriting activities.
The results
AI adoption in credit risk continues to face several structural and operational challenges. Issues such as data quality, model transparency, system integration, and regulatory expectations remain central to determining how effectively institutions can scale AI-enabled practices.
Top Barriers to AI Adoption in Banking
PwC European Credit Risk Survey 2026 results highlight the key barriers constraining the effective and scalable adoption of AI in credit risk.
The findings suggest that banks perceive AI challenges as predominantly technical and regulatory at this stage of adoption, with ethical concerns emerging but not yet representing a primary barrier.
Data quality and legacy system integration
Data quality and availability stand out as the most pressing constraint (28%), followed by integration with legacy systems which accounts for 24% of responses.
Model Explainability and Regulatory Compliance
Model explainability and transparency concerns account for 21% of responses, followed by regulatory acceptance and compliance challenges (18%) and ethical and governance considerations (9%).
Credit Risk Pricing and Capital Allocation in Banking
Defining accurate credit pricing remains a complex challenge for banks, as it requires balancing forward‑looking risk assumptions with profitability targets, capital constraints and operational cost drivers.
Where do you see the greatest challenges in defining accurate credit pricing for new lending operations?
Accurate credit pricing remains challenging as banks must balance forward‑looking risk assumptions with financial and operational cost drivers. These factors shape where the main difficulties in pricing new lending operations emerge.
The results reveal two dominant pain points for European banks: the determination of the expected Return on Equity (ROE) cited by 31% and forward-looking definition of cost of risk with 29% of respondents.
These are followed by the allocation of operational costs directly associated with the credit granted (21%) and the precise ex-ante calculation of Risk-Weighted Assets (RWA) for new transactions (19%).
Overall, the results reinforce that pricing accuracy hinges increasingly on forward-looking insights rather than operational mechanics.
Future Outlook for Credit Risk Management in Banking 2026
Credit risk strategies are increasingly shaped by broader structural trends, particularly around sustainability, data innovation and advanced analytics. These developments are influencing how institutions assess risk, design lending models, and adapt their operating frameworks, making some themes more prominent than others.
ESG and climate risk integration emerge as the most influential driver (28%), reflecting the intensifying regulatory, investor and societal expectations around sustainable finance. The use of alternative data sources follows at 20%. AI-driven credit scoring and underwriting represent 17%.
Other trends play a more targeted but still relevant role: 11% point to shifts in business models aimed at embedding additional client services within lending activity, while 9% of respondents highlight the expansion of risk transfer and structuring capabilities and another 9% are attributed to IRB-related developments.
Other initiatives were mentioned by 3% of respondents, emerging themes such as embedded finance models with 2% and credit decisioning-as-a-service platforms represent 1%.
As credit risk functions evolve, banks are refining their strategic priorities to strengthen competitiveness and adapt to shifting market, client and regulatory expectations. Over the next 12–24 months, several themes are emerging as focal points, reflecting where institutions expect to direct their efforts and investment.
The results indicate three primary priorities:
- Enhancing client experience (33%), reflecting a stronger focus on service quality and speed
- Focusing on specific sectors and funding structures (30%), signalling increased specialisation
- Improving pricing models (19%), to better reflect risk, business models and client profiles
Overall, the PwC European Credit Risk Survey 2026 suggests that banks appear to be sharpening their strategic lens toward sector specialisation and client centricity, signalling a shift from broad risk management towards more tailored, relationship-driven credit strategies.
Unlock insights into Credit Risk Management Maturity
Download the PwC European Credit Risk Survey 2026 to access in-depth insights, benchmarks, and strategic recommendations shaping the future of banking.
About the Survey
PwC conducted a survey between December 2025 and February 2026 with 35 European banking institutions across 13 countries, providing a comprehensive view of credit risk management practices, maturity levels and key challenges. The study reflects how banks are adapting their frameworks to an evolving macroeconomic, technological and geopolitical environment, offering a comparative perspective across the European market. Discover the full results and key insights from the survey.
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Director, Financial Services Risk & Regulation and EBA SSM Office credit risk transformation ws. Co-Leader, PwC Portugal
