Topic: Research and analysis

New research from the Global Institute of Credit Professionals identifies the core capabilities employers consistently seek across the world’s top banks, revealing that AI is reshaping credit roles but not replacing the foundations of successful careers.

Employers across the world’s leading banks are converging on a clear definition of what it means to be “credit capable,” according to new research from the Global Institute of Credit Professionals (GICP).

The report, ‘Building the Modern Credit Workforce’, analyzed more than 1,500 live credit-related job postings from the world’s top 50 banks across eight major financial markets to identify the skills employers consistently prioritize across modern credit roles. Rather than revealing a race towards AI-only expertise, the findings show that employers are building teams that combine technical, regulatory and behavioral capabilities to support increasingly complex credit decisions.

The research found that employers are converging around a universal credit skill set that combines data platforms and governance, model risk and governance, NLP and document analysis with adaptability, stakeholder management, risk mindset, judgment, communication and storytelling as the foundations of successful credit careers. While AI, data and programming skills are now present across credit functions, they are being sought alongside core capabilities rather than replacing them. The report concludes that today’s most successful credit professionals combine technical expertise with the ability to explain, challenge and defend decisions in increasingly data-driven environments.

The analysis also highlights how credit roles are evolving. Forty-four per cent of roles remain traditional in structure, while 45% have already evolved into blended roles where established credit responsibilities are augmented by AI-supported tasks. Hybrid roles are found in areas such as data and modelling, underwriting and credit research, reflecting how AI is increasingly supporting analysis while accountability for decisions remains firmly with people.

Python is the third most requested technology across credit roles, while Excel and PowerPoint remain the two most widely requested tools. Nearly 10% of job postings explicitly require proficiency in at least two of these three, showing that employers value professionals who can combine established financial expertise with technical and analytical capabilities. Rather than pointing to a wholesale shift in the tools used by credit professionals, the findings show that traditional and technical capabilities are already being sought together across modern credit roles.

Andreas Karaiskos, Executive Director of the Global Institute of Credit Professionals, said:

“There is a growing perception that AI is fundamentally changing the skills employers value. Our research tells a more nuanced story. The world’s leading banks are looking for professionals who can combine technical and digital capability with sound judgment, strong communication and effective risk management. AI is changing how credit work is performed, but it is being integrated alongside the capabilities that have always underpinned good credit decision-making. For professionals, the message is clear: the strongest careers will be built by combining enduring credit fundamentals with the ability to work confidently alongside new technologies.”

The report also found that employer expectations evolve as careers progress. Early-career roles focus on developing strong foundations in data quality, governance and communication, while senior roles place greater emphasis on leadership, commercial judgment and strategic decision-making. Across every level of seniority, however, employers consistently expect professionals to combine technical knowledge with the ability to communicate effectively, manage risk and exercise sound judgment.

According to GICP, the findings provide a practical blueprint for organizations seeking to build future-ready credit teams and for professionals looking to develop the capabilities employers consistently value in an evolving financial services landscape. As AI becomes embedded across the credit lifecycle, the report concludes that competitive advantage will come not from mastering a single technology or skill, but from developing the blend of technical, regulatory and behavioral capabilities that define today’s modern credit professional.

Download the full ‘Building the Modern Credit Workforce’ report.

New research from the Global Institute of Credit Professionals reveals why organizations with similar levels of AI adoption are achieving very different business outcomes.

Organizations are rapidly embedding artificial intelligence into credit processes, but new research suggests that simply using more AI does not automatically translate into better business outcomes.

Our latest report, ‘Credit in the Age of AI’, finds that organizations with similar levels of AI adoption can achieve markedly different results, with success determined less by the technology itself and more by the organizational capability needed to embed AI effectively across its people, processes and operating models.

The findings show that AI adoption remains relatively shallow across much of the industry. 56% of organizations currently use AI in less than 25% of their credit processes, including 14% that are not using AI at all. Adoption is currently concentrated in lower-risk activities such as document drafting, financial analysis and market research, while AI is delivering its greatest reported impact in activities closest to credit decision-making, including risk assessment and credit scoring.

Despite relatively modest levels of adoption, organizations are already seeing measurable benefits. Nearly half (47%) of organizations using AI across just 25–49% of their workflows report high organizational impact, rising to 66% among those using AI across 50–75% of workflows. The findings suggest that how organizations implement AI is just as important as how much AI they use.

The report identifies governance as one of the clearest differentiators between organizations achieving high AI-enabled impact and those struggling to realize value. Sixty-seven per cent of organizations with eight or nine AI governance measures in place reported high AI-enabled impact, compared with just 23% of organizations with zero or only one governance measure in place. Similarly, 50% of organizations reporting high AI-enabled impact have formal governance frameworks in place, compared with only 18% of those where AI-enabled impact remains minimal or mixed.

Organizations reporting high AI-enabled impact also introduced more than twice as many workforce and workflow changes, averaging 2.58 organizational changes compared with 1.22 among organizations reporting lower AI impact, reinforcing that successful AI implementation requires organizational transformation as well as technology.

However, the research also reveals a significant disconnect between where organizations recognize challenges and where they are investing. Sixty-five per cent of respondents identified leadership and governance factors as the biggest barrier to successful AI adoption, yet only 38% plan to prioritize investment in this area.

The report also highlights what it describes as the “Two Waves of AI Value.” The first wave has focused on productivity gains from lower-risk applications such as drafting, summarization and research. The second wave is now emerging as organizations begin applying AI to underwriting, credit assessment and risk scoring. Overall, across organizations expecting disruptions from generative AI, autonomous decision-making or real-time monitoring, 79% are not yet deploying AI in the corresponding workflows, suggesting ambition continues to outpace organizational readiness.

Andreas Karaiskos, Executive Director of the Global Institute of Credit Professionals, said: “The conversation around AI has largely focused on adoption, but our research shows that adoption alone is not creating competitive advantage. Organizations with similar levels of AI activity are achieving very different outcomes because success depends on much more than technology. The organizations seeing the greatest impact are investing in governance, workforce capability and operating models that enable AI to be embedded effectively into day-to-day credit decision-making. As AI becomes an established part of the credit lifecycle, competitive advantage will increasingly depend on how well organizations combine technology with skilled professionals, sound judgment and effective execution.”

The report concludes that as AI becomes embedded across the credit lifecycle, competitive advantage will increasingly depend on an organization’s ability to embed AI across its people, processes and decision-making. Organizations that invest in governance, leadership, workforce capability and operational change alongside technology will be best placed to translate AI adoption into meaningful long-term business value.

Download the full ‘Credit in the Age of AI’ report.