Call for Papers – Special Issue: AI-Driven Credit Risk and the Future of Financial Decision-Making

Journal of Risk Management in Financial Institutions

Subramanian (Subbu) Narayanaswamy, Executive Director, Wells Fargo Bank, US

Submission deadline: 15th January 2027

Credit risk management is undergoing its most consequential transformation in decades. Foundation models, alternative data, real-time decisioning engines, and, increasingly, agentic AI systems are changing how institutions assess creditworthiness, price risk, and allocate capital, while fintech lenders and embedded finance platforms blur the lines between origination, servicing, and risk oversight. The opportunity and the fragility are happening simultaneously: AI can widen credit access and improve risk differentiation, but it can also encode bias at scale, obscure accountability, and create model dependencies that are poorly understood until they fail.

A second transformation has received far less attention. AI is becoming a driver of credit risk in its own right. The capital expenditure cycle financing AI infrastructure is creating increasingly concentrated exposures across banks, private credit providers and capital markets, some of which are difficult to see through conventional measures of direct lending. AI-driven changes in employment and income stability could affect consumer and small business portfolios in ways that models calibrated on an earlier labour market may not capture. The industry has spent several years asking how AI changes credit decisions; the question for the next cycle is how AI changes credit.

Regulation is moving unevenly. In the European Union, obligations governing high-risk AI systems, including those used to assess the creditworthiness of natural persons, became applicable in August 2026. In the United States, revised interagency model risk management guidance placed generative and agentic AI outside its scope, leaving institutions to work out how existing expectations apply. Institutions are deploying some of their least understood technology in an area where the formal governance framework remains unsettled.

This special issue seeks contributions that assess where this is all heading, not only with where it stands today. We are particularly interested in work grounded in production experience, supervisory practice or original data. Practice articles, case studies and applied research are all welcome, from both academic and practitioner authors.

Submissions covering any of the following topics for this special issue will be considered, but additional suggestions for papers are also welcomed.

The Future of Credit Risk and Trust in Banking

  • What happens to many lenders at once when a shared foundation model, cloud provider or data vendor fails?
  • Model monoculture: what are the systemic consequences of correlated decisions, shared blind spots and procyclicality when lenders underwrite on similar models and data?
  • As credit decisioning becomes autonomous, what changes for trust, stability and the relationship between lender and borrower?
  • Are banks evolving into identity and trust platforms rather than traditional financial intermediaries?
  • Expanding financial access while preserving system stability: Can AI deliver on both?
  • What can be learned from AI adoption failures and model governance breakdowns?
  • What does the credit risk function look like in an AI-native bank, in talent, organizational design and culture?

AI as a New Source of Credit Risk

  • How concentrated and correlated is lending to AI infrastructure across data centres, compute, power and the hyperscaler supply chain?
  • How can indirect and obscured credit exposures through non-bank lenders and private credit be identified and measured
  • How should collateral valuation and recovery assumptions be set for fast-depreciating compute assets?
  • What could AI-driven labour displacement mean for consumer and small business credit quality, and for models calibrated on an earlier labour market?
  • How should lenders underwrite and monitor borrowers whose own business models are being disrupted by AI?

AI Models, Governance and Regulation

  • Foundation models and LLMs in credit underwriting: capability, risk and governance
  • What architectural patterns support real-time and dynamic credit decisioning, and what risks do they introduce?
  • Can AI-powered early warning systems detect portfolio deterioration and macro regime shifts earlier than existing approaches?
  • How should non-deterministic systems be validated when point-in-time validation no longer fits?
  • How should institutions govern what model risk guidance excludes, and what should supervisors expect of generative and agentic systems in credit?
  • Credit policy in the agentic era: how can risk appetite, authorities and exceptions be translated into machine-executable controls?
  • Who is accountable, and who is liable, when an autonomous system extends, prices or withdraws credit?
  • How are global institutions managing divergent regulatory paths across the EU, UK, US and Asia?

Fintech, Embedded Finance and Ecosystem Risk

  • Who owns risk oversight when embedded credit sits inside a non-financial platform and the lender is invisible?
  • What do stablecoins, tokenized deposits and programmable money imply for credit creation, liquidity and the transmission of risk?
  • How does default contagion propagate through fintech and private credit portfolios during macro stress events?
  • How is synthetic identity fraud reshaping the convergence of fraud, identity and credit risk in digital lending?
  • Which identity verification strategies hold up in open banking and API-driven financial infrastructures?
  • AI agents as transacting parties: what identity, credit and KYC obligations apply when the counterparty is not human?

Submission guidelines:

The following types of articles will be considered for publication:

  • Practice articles: Thought pieces, briefings, case studies and other contributions written by practitioners. Articles should be 2,000 to 5,000 words in length.
  • Research papers: Contributions which explore new models, theories and research in risk management. The principal management implications of the submission should be included. Articles should be up to 6,000 words in length.

We are seeking an even balance between academic and practitioner contributions.

All submissions will be peer-reviewed to ensure that they are of direct, practical relevance to those working in the field.

Our current copy deadline for this special issue is 15th January 2027.

Further, more specific guidance for authors on format and style can be found at: Instructions for authors – Henry Stewart Publications

Expressions of interest, proposed titles, abstracts and manuscript submissions should be sent to the Publisher, Julie Kerry.

About Journal of Risk Management in Financial Institutions

The journal is a quarterly professional journal aimed directly at those responsible for managing risk in financial institutions. The journal publishes a mixture of technical papers as well as qualitative papers on five inter-related areas of risk: strategic, financial, operational, regulatory and systemic risk. The journal is aimed at senior management within the banking sector, companies providing a service to the financial sector, and governments, regulators and academics throughout the world with an interest in financial risk management. The journal publishes briefings, discussions, applied research, case studies, expert comment and analysis on the key issues. Further information on the journal is available here.