As artificial intelligence adoption accelerates across financial services, banks are beginning to impose a new requirement on technology vendors: explainability. Procurement teams, compliance departments, and risk executives are increasingly demanding contractual clauses that force AI providers to disclose how models make decisions, how outputs are generated, and how institutions can audit automated recommendations.
The shift reflects growing concern inside banking over the operational and regulatory risks of deploying opaque AI systems into critical financial processes. While banks initially focused heavily on AI performance and automation gains, attention is now moving toward governance, accountability, and transparency as AI tools become embedded across lending, fraud detection, onboarding, compliance monitoring, and customer servicing.
Procurement Teams Are Becoming AI Risk Gatekeepers
In many financial institutions, AI procurement reviews are evolving into specialised risk assessment exercises. Vendors are no longer evaluated solely on functionality, pricing, or implementation timelines. Banks increasingly want evidence that AI systems can provide traceable reasoning behind outputs and recommendations.
This is particularly important in high-stakes banking functions where decisions can affect customer eligibility, fraud investigations, transaction monitoring, or regulatory reporting. Institutions are becoming wary of deploying black-box AI systems that cannot clearly justify why specific actions or recommendations were generated.
Procurement contracts are now starting to include provisions related to model transparency, data lineage, auditability, human override capabilities, and bias monitoring. Some banks are also requiring vendors to disclose when generative AI models rely on third-party foundation models or external datasets.
Regulators Are Quietly Influencing AI Procurement Behaviour
The push toward explainable AI is also being driven by regulatory pressure. Financial authorities globally are increasingly signalling that banks remain accountable for AI-generated decisions, even when external vendors supply the underlying systems.
This creates a major operational challenge for financial institutions. Banks may outsource technology infrastructure, but they cannot outsource regulatory responsibility. As a result, procurement departments are becoming frontline control functions for AI governance.
Several banking executives now view explainability clauses as a form of future-proofing against evolving AI regulations. Instead of waiting for mandatory compliance frameworks, institutions are proactively embedding governance requirements directly into vendor agreements.
AI Vendors Face A Growing Commercial Divide
The procurement shift could create a widening gap between enterprise-grade AI providers and smaller vendors unable to support rigorous governance requirements. Large banks increasingly expect detailed documentation, testing frameworks, explainability dashboards, and model risk controls as part of procurement evaluations.
Some AI vendors built primarily for speed and automation may struggle to satisfy banking-grade audit and compliance expectations. Others are now redesigning products specifically around explainability and governance as competitive differentiators.
This trend may reshape the broader fintech AI landscape. Banks appear increasingly willing to sacrifice some automation capability in exchange for greater transparency and operational control.
Explainability Is Becoming A Strategic Banking Requirement
The banking sector’s AI strategy is evolving beyond experimentation. Institutions are now preparing for a future where AI systems operate across core operational and decision-making infrastructure. In that environment, explainability becomes more than a technical feature. It becomes a strategic requirement tied directly to operational resilience, regulatory defence, and reputational protection.
Over time, explainability clauses may become as standard in banking technology contracts as cybersecurity obligations or data privacy requirements. Vendors unable to provide sufficient transparency may increasingly find themselves excluded from major financial institution procurement processes altogether.
The result is a subtle but important industry shift: banks are no longer simply asking whether AI works. They are increasingly asking whether AI can explain itself.
What this means for the industry
- Banks are increasingly embedding explainable AI requirements into vendor procurement contracts.
- AI procurement reviews are evolving into broader governance and risk assessment exercises.
- Financial institutions want greater visibility into how AI systems generate decisions and recommendations.
- AI vendors may face growing pressure to prioritise transparency and auditability over pure automation speed.
- Explainability could become a standard commercial requirement for banking AI deployments.
