Investment firms are moving quickly to adopt AI agents, APIs, bots, and automated workflows across trading, research, operations, and reporting. Each of these systems depends on non-human identity (NHI) to access data and perform work. Non-human identities can include service accounts, tokens, API keys, certificates, and other machine credentials.
However, governance for those identities has not kept pace with adoption. As a result, many firms now face a growing security blind spot: powerful machine identities operating across critical systems with less visibility, less ownership, and less control than human users.
In financial environments, non-human identities can touch revenue systems, sensitive data, external vendors, and automated decision flows, which means poor governance can quickly become a business continuity, compliance, and resilience problem. In many cases, investment firm leaders need to discover them, assign accountability, limit their access, and remove them before they become a breach path or an audit problem.
Why the risk is growing
The number of non-human identities in enterprise environments has expanded rapidly as firms modernize technology stacks and increase automation. The Non-Human Identity Management Group (NHIMG) notes that non-human identities now outnumber human identities by 25 times to 50 times in modern enterprises, illustrating how quickly the machine-access surface can scale beyond traditional human-centered controls. A recent white paper from the Cloud Security Alliance (CSA) goes even further, stating that non-human identities outnumber human users by an average of 45 to 1, and in cloud-native environments the ratio can reach 144 to 1.
That growth changes the nature of identity risk. Human access is usually tied to known users, standard review processes, and clear lifecycle events such as hiring, role changes, or departures. Non-human identities behave differently: they are created by applications, integrations, and automated processes, often across cloud, on-premises, and hybrid environments. They can persist long after the original business need has changed. In practice, this means risk can accumulate quietly through over-privileged service accounts, orphaned credentials, and other identities that few people realize still exist.
For investment firms, the timing also matters. As AI initiatives expand, machine identities are becoming more deeply embedded in workflows that support research, analytics, and execution. CSA argues that agentic AI sharpens the NHI problem because these identities increasingly support autonomous actions across multiple systems. That raises the stakes: identity failures can affect decision speed, data integrity, vendor exposure, and operational resilience.
What this looks like in an investment firm
In many firms, non-human identity sprawl develops gradually. Steps may include:
- A new automation project gets launched
- An external data source is connected
- A service account is created for a platform integration
- An AI workflow is given standing access to internal systems.
Each step may appear reasonable on its own, but over time the environment fills with machine credentials that are hard to inventory, review, and retire.
The core risk is that they often operate with broad access and limited accountability. NHIMG’s financial-services guidance emphasizes that the controls determining whether NHIs remain governable are visibility, secret rotation, and least privilege. When those controls are weak, access becomes persistent, difficult to attribute, and easy to extend beyond its original purpose. In a regulated investment environment, that can undermine both cybersecurity posture and confidence in the firm’s control framework.
This is one reason non-human identity governance deserves broader leadership attention. A compromised employee account is familiar to most organizations, but a compromised service account connected to trading data, reporting pipelines, or portfolio systems can be harder to detect and explain.
Why traditional IAM is not enough
Most identity and access management (IAM) programs were designed around people. They are effective at handling employees, onboarding, approvals, authentication, and periodic access reviews. They are less effective when the identity in question is a workload, script, service account, or AI-driven process operating continuously across multiple systems.
CSA’s non-human identity management guidance makes this gap clear. It recommends that organizations start with the following steps:
- Define the scope.
- Map stakeholders and environments.
- Discover and inventory NHIs across cloud and on-premises systems.
- Assign ownership.
- Build a policy framework.
- Automate lifecycle management.
That sequence matters because it highlights what many firms are missing: non-human identities require a formal management program, not an ad hoc collection of technical fixes.
This is where the issue becomes strategic. If a firm cannot say how many non-human identities it has, who owns them, what they can access, and how they are decommissioned, then identity governance is incomplete. In investment firms, incomplete governance can directly affect resilience, vendor oversight, and the ability to demonstrate control to clients, auditors, and regulators.
Four priorities for non-human identity security
A strong response begins with acknowledging that non-human identity is part of the firm’s identity surface and should be governed accordingly. For leadership teams, four priorities stand out.
1. Establish visibility across people and machines
Firms need a reliable inventory of non-human identities across cloud, on-premises, and hybrid environments, along with a basic understanding of which systems and workflows those identities support. CSA identifies discovery and inventory as an essential step in defining the NHI perimeter, while NHIMG argues that leadership needs a single view of identity risk across both people and machine identities.
That combined view matters because human-centric reporting can create false confidence. An executive dashboard may show strong employee access governance while leaving machine credentials, service-to-service trust, and automation accounts largely unmeasured. NHIMG warns that this is precisely how real exposure can remain hidden from leadership until after an incident.
2. Make ownership a governance requirement
Every non-human identity should have clear accountability tied to a business owner, technical owner, or both. NHIMG’s guidance stresses that machine identities should be governed as part of one exposure picture, with ownership, logging, rotation, and revocation visible at the management level.
This is especially important in investment firms because access often spans multiple functions. A single integration may touch data vendors, internal analytics, reporting environments, and third-party platforms. Without explicit ownership, firms increase the odds that identities become orphaned, over-privileged, or exempt from regular review.
3. Treat policy as a control, not a guideline
Least privilege, rotation, attestation, and decommissioning should be treated as policy requirements. CSA recommends formal policies governing NHI access, rotation or federation, and decommissioning, aligned with broader frameworks such as zero trust and the NIST Cybersecurity Framework (CSF).
That framing is useful at the leadership level because it shifts the conversation away from isolated fixes. The goal is to create a durable operating model in which machine identities are created, governed, and retired under clear rules that can be evidenced over time.
4. Insist on automation where scale demands it
Manual handling does not scale when non-human identities proliferate. CSA recommends automating provisioning, secret rotation, attestation, compliance documentation, and decommissioning so organizations can reduce operational overhead while maintaining control.
When machine identities outnumber human users by dozens to one, manual reviews alone cannot keep pace with the speed of change in modern environments. Automation becomes necessary to maintain minimum standards of visibility, timeliness, and control.
Executive oversight of non-human identity security
Identity governance is increasingly becoming a leadership issue because risk now accumulates across both people and machines. NHIMG’s governance guidance says boards and senior leaders need a single view of identity exposure, and that reporting should separate human access metrics from machine identity metrics rather than blend everything into one vague KPI.
For investment firms, that means leadership should expect management reporting on several elements, such as:
- Machine identity inventory
- Secret age
- Rotation compliance
- Privilege concentration
- Ownership of critical NHIs
This is an important shift in perspective. The right management question is whether the firm can explain which machine identities exist in production, what they can access, who owns them, and how quickly they can be revoked. That framing aligns more closely with resilience, auditability, and third-party oversight than with a narrow IAM checklist.
CSA’s governance-vacuum research reinforces why this matters now. Its executive summary argues that most enterprise security investment has focused on the human identity perimeter even though non-human identities now represent the faster-growing unmanaged attack surface. CSA also reports that only 15% of organizations feel highly confident in their ability to prevent NHI-based attacks.
For senior leadership, that makes non-human identity governance less of a technical maturity topic and more of a control-confidence issue.
A practical path forward
For many investment firms, the most effective next step is to frame non-human identity governance as part of a broader modernization and resilience agenda. That means connecting the issue to cloud strategy, cybersecurity, operational risk, and AI readiness. When approached this way, NHI governance supports several business goals at once: tighter security, clearer accountability, stronger auditability, and safer automation.
A practical program can begin with a focused assessment of high-value systems and workflows. Firms do not need to solve every NHI issue at once. They can start by identifying where machine identities have the greatest business impact, such as:
- Trading platforms
- Data pipelines
- Vendor integrations
- Reporting systems
Applying governance disciplines in any of these areas creates a manageable entry point. It also produces visible improvements in risk posture and control maturity.
From there, the program can expand into standard lifecycle practices: clearer ownership, stronger policy enforcement, regular review, and automation for provisioning and decommissioning. Over time, these capabilities help transform machine identities into a governed operational asset.
Creating formal controls for non-human identity security
Non-human identities have become essential to how modern investment firms operate. However, their importance has outgrown the informal controls many organizations still rely on. In financial services, NHIMG’s guidance is direct: when service accounts, APIs, and machine-learning processes sit inside revenue systems, access sprawl becomes an operational resilience concern. That framing is useful because it places the issue where it belongs: with leadership teams responsible for protecting the firm’s continuity, reputation, and growth.
For investment firms pursuing AI, automation, and platform modernization, the right response is to govern machine access with the same seriousness applied to human access. Firms that do that will be in a stronger position to scale technology safely, satisfy growing scrutiny around controls, and protect the systems and data that matter most.
