Category: Risk Assessment & Analysis

Risk Register

Also known as: Risk Log, Risk Repository

Simply put

A risk register is a central document that records the known risks facing a project, organization, or other defined scope, along with related information about each one. It is used to help teams identify, track, and manage risks before they cause problems. It typically serves as a single reference point that supports both day-to-day risk management and, in some contexts, regulatory compliance.

Formal definition

As commonly defined, a risk register is a structured record of current identified risks for a given scope or organization, capturing associated information used to identify, assess, prioritize, monitor, and manage those risks throughout the risk management process. In many frameworks it encompasses both accepted risks and risks slated for further treatment, and functions as a repository that can also support regulatory compliance obligations. The specific fields, taxonomy, and governance around a risk register vary by organization, sector, and framework; the evidence provided does not prescribe a single authoritative schema, and its application to AI-specific or model risk contexts is not detailed here.

Why it matters

A risk register provides a single, structured reference point for the risks an organization or project is tracking, which matters because risks that are not recorded are difficult to assign, monitor, or treat consistently. As commonly defined, it captures both accepted risks and risks slated for further treatment, giving governance functions visibility into what is known, who owns each item, and what action is planned. Without such a central record, risk information tends to fragment across teams and documents, making it harder to demonstrate that risks have been identified and are being managed.

Beyond day-to-day risk management, a risk register is often used as an artifact supporting regulatory compliance, acting as a documented repository of identified risks that can be referenced during oversight or audit. This dual role, operational tool and compliance evidence, is part of why registers are widely adopted across risk management processes. It is worth noting, however, that a register records and organizes risk information; it does not itself reduce or eliminate risk, which depends on the treatment actions the register tracks.

Professionals should be cautious about assuming a single authoritative schema. The specific fields, taxonomy, and governance around a risk register vary by organization, sector, and framework, and the evidence here does not prescribe one standard structure. Its application to AI-specific or model risk contexts is not detailed in the sources provided, so any use in those settings should be defined explicitly rather than assumed from general risk register practice.

Who it's relevant to

Risk and Compliance Officers

For those responsible for oversight, the risk register serves as both an operational tracking tool and, in many contexts, an artifact supporting regulatory compliance, providing a documented repository of identified risks. It is important to remember that the register evidences and organizes risk information but does not by itself reduce risk.

Project and Program Managers

The register is widely used as a project management tool to list every known risk that could affect a project and to identify, track, and treat those risks before they become problems. The specific fields and structure will depend on the organization's chosen framework rather than a single standard.

Auditors and Assurance Functions

Because a register acts as a central record of current identified risks, including both accepted risks and those slated for further treatment, it can be referenced to assess whether risks have been documented and whether treatment is being tracked. Auditors should confirm the register's scope, taxonomy, and governance rather than assume a consistent schema across organizations.

AI Governance and Model Risk Teams

Teams may adopt a risk register to record risks within an AI or model context, but the evidence here does not detail how general risk register practice maps to AI-specific or model risk settings. Any such application should define fields, ownership, and taxonomy explicitly rather than inheriting them from general practice.

Inside Risk Register

Risk identification and description

A structured record of identified risks, each typically captured with a unique identifier and a plain-language description of the risk event or condition. In an AI context this may include risks arising from specific models, data pipelines, or deployment settings, though the level of granularity varies by organization and framework.

Risk assessment (likelihood and impact)

An evaluation of each risk, commonly expressed in terms of likelihood and potential impact. Registers often distinguish inherent risk (before controls) from residual risk (after controls are applied); these are separate concepts and should not be collapsed into a single rating without clarity about which is being recorded.

Controls and mitigations

The measures in place or planned to address each risk. These are documented as means to reduce or manage risk rather than eliminate it. In model risk management contexts, controls may map to validation, monitoring, or oversight activities.

Risk ownership and accountability

The assignment of a responsible owner for each risk. This links the register to broader AI governance structures, and in some organizations to first, second, and third lines of defense, though the specific accountability model depends on the organization's design.

Status, monitoring, and review dates

Fields tracking the current state of each risk, actions taken, and dates for review. This supports ongoing monitoring, since risk profiles can change over time—for example due to model performance degradation, which is distinct from model risk itself.

Prioritization or rating

An aggregated or relative ranking used to focus attention, often derived from the likelihood and impact assessment. Rating scales and thresholds are typically organization-specific rather than dictated by a single authoritative standard.

Common questions

Answers to the questions practitioners most commonly ask about Risk Register.

Is a risk register the same thing as a risk assessment?

No. A risk register is typically a living record or inventory that captures identified risks along with attributes such as descriptions, owners, ratings, and mitigation status. A risk assessment is the analytical activity of identifying and evaluating risks. The register is often an output that records assessment results and is updated over time, whereas the assessment is the process that generates the entries. Treating the two as interchangeable can obscure the distinction between the documentation artifact and the ongoing analytical work that populates it.

Does maintaining a risk register mean the listed risks have been eliminated?

No. A risk register records and tracks risks so they can be monitored, prioritized, and managed; it does not by itself remove or resolve them. Even risks marked as mitigated typically retain some residual risk. The register is a management and oversight tool that supports risk reduction, not evidence that a risk no longer exists. Reading a populated register as proof of elimination is a common error.

What information is commonly captured for each entry in a risk register?

Practices vary by organization and framework, but entries typically include a risk description, the source or category of the risk, an assigned owner, an assessment of likelihood and impact, an inherent and/or residual rating, planned or implemented controls or mitigations, status, and review dates. The specific fields depend on organizational policy and the register's intended audience.

Who is typically responsible for maintaining a risk register?

Ownership arrangements vary. In many organizations, individual risk entries are assigned to a designated risk owner, while overall upkeep may sit with a risk or compliance function. In lines-of-defense models, first-line units often identify and manage risks while a second-line function may oversee the register's consistency and completeness. Roles should be defined by organizational policy rather than assumed.

How often should a risk register be reviewed or updated?

There is no single universal cadence. Registers are commonly reviewed on a periodic schedule and also updated when triggering events occur, such as new risks being identified, changes in a risk's status, or material changes to the systems or processes in scope. Update frequency is typically set by organizational policy and may be more frequent for higher-rated or fast-changing risks.

How does a risk register relate to broader governance and oversight processes?

A risk register often serves as an input to governance activities such as reporting to committees, prioritizing mitigation efforts, and supporting decisions about risk acceptance or escalation. Its usefulness depends on being kept current and connected to accountability structures, so that entries have owners and are acted upon rather than recorded and left static.

Common misconceptions

A risk register eliminates the risks it documents.

A register is a documentation and tracking tool; the controls it records are measures that reduce or manage risk, not remove it. Residual risk typically remains after mitigations are applied, and documenting a risk does not by itself change its likelihood or impact.

Maintaining a risk register is the same as having AI governance or model risk management in place.

A register is one instrument that can support both AI governance and model risk management, but it is not equivalent to either. AI governance concerns organizational structures, policies, and oversight, while model risk management concerns identifying, measuring, monitoring, and controlling risks from model use. A register on its own does not supply these functions.

The contents and format of a risk register are standardized across frameworks and jurisdictions.

As commonly defined, core elements such as risk description, assessment, controls, and ownership recur, but specific fields, rating scales, and terminology vary by organization, sector, and framework. There is no single universally authoritative template that applies across all contexts.

Best practices

Clearly distinguish inherent risk from residual risk in the register, and label which rating each field represents to avoid conflating the two.

Assign a named owner to each risk and link entries to your organization's accountability structure so the register connects to broader governance rather than sitting in isolation.

Record review dates and update entries as conditions change, recognizing that a risk profile can shift over time—for example when monitoring reveals model performance degradation.

Document controls as measures that reduce or manage risk, and avoid language implying they eliminate risk entirely.

Use consistent, organization-defined rating scales and state the assumptions behind them, since no single scale is authoritative across all frameworks.

Treat the register as one component supporting AI governance and model risk management, and ensure it feeds into decision-making rather than serving as a standalone compliance artifact.