Banking on AI: 8 essentials for unshakable operational resilience

Between 2018 and 2023, major global banks lost more than $170 billion in total due to operational failures, according to an EY report. This alarming figure proves that resilience gaps can destroy decades of growth overnight. The culprit? Most banks are running their operational resilience programs on thousands of disconnected, legacy systems across teams and departments.

This creates a dangerous paradox: Every department has green-light dashboards, but no one can confidently answer critical questions such as “What happens if our electronic funds transfer (EFT) processor fails during month-end?” or “Which services depend on that mainframe we're decommissioning?” These unanswered questions expose the fragility of banks' operational resilience programs, leaving them vulnerable to catastrophic losses and regulatory scrutiny.

Siloed systems make it impossible to see cascading failures before they happen. When one system goes down, teams scramble to manually trace dependencies through spreadsheets and tribal knowledge, turning what should be a one-minute fix into a five-hour outage.

Without real-time visibility across interconnected services, banks can't proactively isolate problems, redirect traffic, or accurately communicate impact to customers and regulators. Although AI is ready to help banks predict failure patterns and automatically map hidden dependencies across systems, most banks still rely on outdated manual processes, meaning their AI maturity remains low.

The AI-driven operational resilience advantage

The difference between banks that thrive and those that merely survive goes beyond capital reserves—it lies in a strong, AI-driven operational resilience program. Future-proof banks can instantly map critical dependencies, predict cascade failures, and recover services in minutes while their competitors are still assembling crisis teams.

To drive differentiation for your bank, you must excel across eight AI-driven, interconnected operational resilience competencies. At ServiceNow, we've worked with hundreds of banks and have identified common challenges. Let's examine some critical questions to ask yourself across these eight competencies.

1. Continuous service & enterprise asset mapping

When regulators ask to review the mapped dependencies for your EFT processing within 72 hours, can you actually deliver? Advanced banks use AI-driven configuration management with a common taxonomy to instantly map and trace every connection—tech infrastructure, third parties, people dependencies, critical data flows, required skills, and essential facilities.

However, most financial institutions still discover phantom dependencies during outages, when a forgotten legacy interface blocks wire transfers and regulators start asking uncomfortable questions about operational control. This reactive approach exposes banks to regulatory scrutiny, financial losses, and reputational damage.

To meet regulatory demands and maintain operational resilience, banks must proactively map and manage their complex web of dependencies. AI-driven tools can automate this process, providing real-time visibility and enabling rapid response to regulatory inquiries.

2. Autonomous IT operations

Picture this: Your core banking platform experiences a critical error at 2 a.m. on a Sunday. Will your team be able to fix it before Monday's opening bell? Best-in-class banks see their autonomous AI agents diagnose root causes, orchestrate remediation, and restore services without customers knowing about the issues.

Meanwhile, many operations teams are paging through business continuity playbooks on conference calls, watching helplessly as batch processing failures start affecting customers.

3. Risk and compliance

How quickly can you translate new regulatory guidance into tested controls? Future-proof institutions deploy AI that automatically maps new regulatory requirements and framework updates directly into their control libraries, complete with testing protocols and attestation workflows.

Without this approach, compliance teams may find themselves drowning in spreadsheets, racing against implementation deadlines, and hoping nothing falls through the cracks before the next exam.

4. Vulnerabilities

When a critical vulnerability affecting your digital channels is discovered, can you quickly identify all the potentially impacted components across your IT systems? Banks with resilient operations have real-time vulnerability correlation and automated patching based on business importance, and they can provide comprehensive impact assessments to the board within hours. Banks that are not as well equipped may still be searching for vulnerabilities when the first attack hits their firewall.

Similarly, in operations, are you identifying control failures before they escalate into significant issues? Continuous monitoring is crucial for wire transfer limits, dual control overrides, and privileged access to production systems. Forward-thinking banks integrate AI automation into these workflows to catch limit breaches and segregation failures automatically.

Banks that are less prepared uncover control gaps only when auditors or examiners discover them first—or worse, when they appear in a suspicious activity report.

5. Business continuity

When cloud providers experience issues during critical processing periods, can you quickly assess the impact on your essential business services and functions? AI-enabled banks automatically simulate disruptions, invoke alternate routes, and maintain operations within approved impact tolerances while continuously testing vendor patches against established thresholds.

In less advanced business continuity management programs, stakeholders gather in war rooms. There, they discover that their quarterly exercises missed critical changes, their applications' dependencies remain unmapped, and their recovery time objectives for payment processing and securities settlement are unrealistic under actual stress.

6. Incident response and service recovery

Critical incidents instantly reveal operational maturity. During your next critical incident, can you confidently inform clients, the board, and regulators when service will resume?

Sophisticated banks use AI orchestration that prioritizes recovery by actual business impact, dynamically allocates resources based on real-time recovery time objective analysis, and provides executives with minute-by-minute recovery projections they can share with regulators.

Banks that lag behind are left fielding status requests every 10 minutes while profit and loss impact climbs each hour and no one can definitively say when service will resume.

7. Third-party management

Does AI monitor your vendors' ISO compliance and test their patches?

Forward-thinking banks use AI agents to track certification validity, simulate patch impacts on critical services, predict downstream failures across geographies, and generate executive-ready dashboards with human approval. Banks that are not as well prepared often discover expired certifications during incidents, lacking the automated vendor monitoring that regulators increasingly expect as proof of extended enterprise oversight.

8. Governance, AI, and reporting

Is your AI governance framework supported by an integrated, end-to-end view of AI development and use? This includes real-time model key performance indicators, complete algorithmic audit trails, and embedded approval workflows. With such a framework, board conversations can shift from incident postmortems to strategic discussions about automation investments at the strategy, execution, and portfolio levels.

Alternatively, are directors still questioning why fragmented AI risk dashboards showed all green until models failed miserably, while regulators demand evidence of your controls? Banks that lack a comprehensive AI governance framework may struggle to provide satisfactory answers and, consequently, face increased scrutiny.

How does your operational resilience measure up?

These hard-hitting questions expose the challenges within the eight key competencies of operational resilience. How does your program stack up? Mastering these competencies can create a best-in-class, interconnected operational resilience ecosystem. Investing in these areas can help shield your bank from threats, position it for long-term success, deliver unrivaled customer value, and cement your firm as an industry leader.

The ServiceNow^® AI Platform provides a centralized data foundation, agentic AI workflows, and single-platform approach to help break down silos, foster collaboration, and connect people, processes, and data. This powerful combination can drive business growth, increase regulator and customer confidence, lower capital requirements, and ultimately create a resilient organization ready to withstand any disruption.

Find out more about how ServiceNow can help you improve operational resilience and drive growth.