Compliance has rarely cost investment banks more or felt less under control than in 2026. The World Corporate and Investment Banking Report 2026¹ from Capgemini reveals an industry at an inflection point, with growth slowing, heightened competition and mounting pressure to transform. Compound annual growth is set to plummet from 6.5 percent to 5.4 percent over the next 5 years, meaning every increase in the cost of staying compliant bites harder. And that cost is mounting: 61 percent of banking executives now cite high compliance expenses as a major pain point for business performance.

The cause is not a shortage of effort or spend, but operating models that still lean heavily on manual review. However, compliance no longer has to rely on manual effort to keep pace. Agentic AI, multi-agent systems that gather data, weigh context and document their reasoning across an end-to-end workflow, now makes it possible to move compliance monitoring from periodic, rules-based checks toward continuous, context-aware assurance: Detection that weighs intent, triage that prioritizes genuine risk and decisions a bank can evidence to a regulator on demand.

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The Compliance Cost Burden

 

61% of banking executives now cite high compliance expenses as a major pain point for business performance.

The shift is urgent for the same reason it is possible: AI agents are taking on more of the bank's work. The volume and velocity of activity to be monitored will only grow, and manual review cannot scale to meet it. Handled well, this is how a bank can turn regulatory overload into an advantage rather than a cost.

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The Process Bottleneck

 

48% of banking executives say regulatory and compliance monitoring processes are highly manual and fragmented.

The current picture is very different, however. Despite years of investment in screening and monitoring tools, much of the work — clearing alerts, investigating exceptions, documenting decisions and filing reports — remains a labor-intensive human process, running ever faster to keep up with rising volumes and tightening rules.

This is why regulatory and compliance monitoring completes the investment banking value chain's list of most inefficient workflows. 48 percent of banking executives say it is highly manual and fragmented. This is a workflow with years of dedicated technology spend already behind it. The tools have improved, but the model beneath them has not, until now.

In this article, we explore what re-inventing regulatory and compliance monitoring looks like in practice, and why the banks that get it right will come to see compliance as a source of trust rather than a burden to bear.

This article concludes our Intelligent Operations in Investment Banking series by examining regulatory and compliance monitoring, the final workflow in the investment banking value chain. Combined with the four other articles on KYC and due diligence, client onboarding and CX, transaction and trade reconciliation, and data management and reporting, these demonstrate how intelligent operations can transform the critical processes that underpin growth, resilience and trust.

Why Traditional Compliance Monitoring is No Longer Sustainable

For decades, enterprises built compliance monitoring around fixed rules and periodic checks: Screen against a list, raise an alert when a threshold trips, review it and record the outcome. The design made sense for the era that produced it, when obligations were fewer, volumes were lower and a finding could wait for the next review cycle. However, what regulators, clients and transaction volumes now demand of monitoring has outpaced the way it is built, and that model is straining under three specific pressures.

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Banks that keep meeting rising volumes with more people and more rules are accumulating audit risk faster than they are clearing alerts, paying more every year for a model that was never built to keep pace. Escaping that trap means changing what compliance monitoring is for, evolving from periodic, threshold-based checks toward continuous, risk-based assurance: A model that detects in context, triages intelligently and evidences every decision as it is made. So how can banks build the operating model that delivers it?

Four Pillars of Intelligent Compliance Monitoring

Re-inventing compliance monitoring is not about buying another screening tool; it is about re-designing how detection, investigation and evidence fit together. What makes that re-design possible now is that the technology has caught up with the ambition. Agentic AI has matured from flagging exceptions to running multi-step investigations. Generative AI (Gen AI) can draft and document decisions as they are made, and screening engines can weigh context rather than match keywords. Together, these tools enable detection that understands intent, triage that finds the signal and evidence that builds itself.

By harnessing their potential, banks can realize a fundamentally different operating reality. In this future, alerts arrive pre-triaged, with context and supporting data attached; analysts spend their time on genuine risk rather than clearing noise; and every decision carries an audit-ready rationale from the moment it is made, in whichever jurisdiction it lands. Embracing four shifts can turn that prospect into practice:

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Detection that understands context:

Rules-based screening flags anything that resembles a match, producing volume rather than insight. AI-driven screening engines now manage sanctions checks, negative news monitoring and transaction surveillance with far more contextual understanding, weighing relationships, behavior and intent rather than surface patterns. Detection becomes risk-based and continuous rather than threshold-based and periodic.

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Triage that cuts the false-positive burden:

The defining problem in monitoring is not too few alerts but too many, the vast majority of them false. At today’s volumes, every false positive cleared by hand is time not spent on the alert that matters. Manual triage does not just cost more; it lets genuine risk wait in the queue. Intelligent triage automates the first-pass review – comparing data across systems, running open-source checks and clearing the noise – so analysts concentrate on genuine risk and only true exceptions are escalated for human judgment.

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Evidence built-in, across jurisdictions:

Detecting risk is only half the task. A bank must also prove it acted correctly. Gen AI now drafts escalation rationales and produces consistent, audit-ready documentation, capturing the reasoning behind each decision as the work happens rather than re-constructing it under audit.

This matters most across borders, where obligations diverge. Suspicious activity reporting alone spans regimes from FinCEN in the US to the National Crime Agency in the UK and TRACFIN in France, each with its own forms and timelines, yet all manageable from a single, structured operating model. The payoff is fewer regulatory incidents and improved audit readiness, building greater trust with supervisors and clients alike.

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Governing AI that does the governing:

As AI takes over more of the monitoring itself, it creates a control problem inside the control function. Compliance exists to enforce standards, so the models now enforcing them must be held to the same bar: Explainable, validated, version-controlled and auditable, with model approvals and oversight embedded in the workflow rather than bolted on.

In practice, that means treating every model the way the function already treats a control. Each screening or triage model is documented and validated before it goes live and re-validated on a schedule; versions are tracked so any decision can be re-produced months later; new models are tested against the incumbent before promotion; and every automated decision can be inspected.

Leading financial crime operations build this discipline into delivery rather than bolting it on afterward, pairing model development and testing with standing quality control and governance frameworks and independent monitorship, so AI-assisted screening and investigation run inside a controlled, auditable environment.

The cost of skipping this is climbing. Where a compliance model is undocumented or cannot explain itself, a bank cannot show a supervisor why an alert was cleared or a client exited — and an efficiency tool becomes a regulatory exposure. Regulators are converging on the same expectation, with frameworks such as the EU AI Act raising the bar on transparency and human oversight for AI in high-stakes financial decisions. The irony is that compliance teams can be the biggest brake on AI adoption where governance is missing, and its strongest enablers where it is built-in. Governing AI is what lets a bank scale it with confidence.

Building an Intelligent Compliance Operating Model

Together, these four shifts replace a patchwork of manual controls with a single, intelligent assurance layer. Achieving this is no easy feat, and the difficulties are as much operational as technical. Transformation depends on deep financial crime compliance expertise, regulatory knowledge that spans jurisdictions and the capacity to run monitoring around the clock. At the same time, live obligations carry on without pause.

Building such a capability in-house is a significant undertaking, and the odds are not encouraging. Banks broadly struggle to turn technology investment into results. According to the Capgemini study, 94 percent of clients cite compliance risks as their primary concern when adopting emerging technologies in banking services. The reason lies in how these programs are run: New tools are bolted onto the existing process, while the process itself — the alerting logic, the manual review steps, the fragmented case data — stays put. The result is a faster version of the same over-alerting and backlog, at higher cost. Breaking the cycle means re-designing the operating model, and few banks get there alone.

A specialist partner can make the difference here, enabling mature financial crime compliance operations, ready-built accelerators and governed AI as a running capability rather than a build-it-yourself program. Organizations are already benefiting where such partnerships are in place.

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The Compliance Priority

 

94% of clients cite compliance risks as their primary concern when adopting emerging technologies in banking services.

The Way Ahead: From Reactive Compliance to Continuous Assurance

For most banks, compliance monitoring is still a reactive obligation: Catch what you can, document it and brace for the next examination. Re-framed as an intelligent capability, it becomes continuous assurance — evidence, in real-time, that the bank is operating within the rules and can prove it to the regulators and clients who rely on it. Where trust is itself a competitive asset, that is no small advantage.

This is where the arc of intelligent banking operations closes. KYC establishes who a client is; onboarding and reconciliation move and verify their business; a governed data foundation makes all of it reliable; and compliance monitoring stands over the whole, proving the institution can be trusted with what it has built. For the banks that pull ahead, compliance will no longer be the price of doing business, but proof they can be trusted to do it well.

If your operations still run on manual controls across any of these five workflows, from onboarding through compliance monitoring, the same logic applies: The advantage now lies in connecting them into one intelligent operating core.

WNS works with investment banks to re-invent compliance monitoring, combining deep financial crime expertise, AI-led accelerators and governed operations that scale across jurisdictions.

About the Author

Garry Harrison

Senior Vice President,
Banking and Financial Services

Garry is a business leader and board advisor at WNS, with 25+ years of experience across technology, AI, FinTech and financial services. He advises organizations and investors on AI-led transformation, financial crime innovation, commercial strategy and business growth.

FAQs

References

1. World Corporate and Investment Banking Report | Capgemini

2. Anti-Money Laundering and Countering the Financing of Terrorism Overview | European Commission