People, risk and sustainability. Chief Risk Officer
AI for the Risk Office
Risk is reported every quarter.It changes every day.
The register is updated in workshops, indicators are checked by hand and a new scenario takes weeks of spreadsheets. By the time a risk reaches the board, it has often already happened. We map the Risk Office the way your team actually works, then put agents where they let you see risk in time to act on it.
The short answer
It turns a quarterly view of risk into a live one. Agents sense emerging risks in news, data and operations, keep the register current, watch indicators against appetite, run stress scenarios in days and draft the board risk report from live data.
Your team keeps the judgement, the appetite and every call on what to do. The agents do the watching, the gathering and the modelling, so risk reaches the right owner while there’s still time to act.
The mandate
Keep the company within its risk appetite. And see what could hurt it in time to act.
What the board measures you on
Risk within appetite
Top risks against agreed limits
Losses and incidents
Number, size and repeat events
Control effectiveness
Key controls working as designed
Time to detect
From first signal to risk owner
Scenario readiness
Stress tests run and acted on
Time to report
Board and regulator risk reports
The canvas of the Risk Office
Most risk tools store the register. The real work sits in keeping it true, in gathering the signals that should change it and in turning it into decisions.
Canvas 1
What you run
The risk engine.
Enterprise risk management
Risk register, assessments and appetite.
Operational risk
Incidents, losses, key risk indicators and controls.
Credit and market risk
Exposures, limits and counterparties.
Scenarios and stress tests
What happens to the business if things go wrong.
Risk reporting
Board, committee and regulator reports.
Canvas 2
What you answer for
The things the board and regulators hold you to.
Risk appetite
Limits the board sets and you police.
Resilience and continuity
Critical services that keep running when something breaks.
Third party and concentration risk
Suppliers and partners the business can’t do without.
AI and model risk
Models and agents that make or shape decisions.
Where value leaks
Most of them come from timing. The signals exist every day, but the process looks at them every quarter.
01
Risks spotted late
Early signals in news, data and operations go unread.
Risk sensing agents. Read signals every day, link them to your risks and alert the owner with evidence.
Time to detect
Risks caught early
02
Register out of date
Ratings refreshed in quarterly workshops.
Register agents. Propose rating and control updates from incidents, findings and indicators for owners to approve.
Register freshness
Workshop hours
03
Indicators checked by hand
KRIs pulled into spreadsheets each month.
KRI agents. Watch indicators live against appetite and flag breaches the day they happen.
Breaches flagged same day
Appetite use
04
Scenarios built by hand
Each new stress test takes weeks of spreadsheet work.
Scenario agents. Gather the data, run the scenario and explain the drivers in days.
Time per scenario
Scenarios run
05
Incidents that teach nothing
The same failure shows up again next year.
Incident agents. Capture, classify and find the root cause, then link it to the control and the risk.
Repeat incidents
Losses
06
Board report assembled by hand
Days spent building a pack that’s out of date on arrival.
Reporting agents. Draft the risk report from live data for your team to review.
Days to report
Board questions answered
Process lifecycles
We start from the tools you already run. The orange steps are where an agent takes on the work. Appetite, ratings and responses stay with your team.
Risk identification to report
Continuous, reported quarterly
Identify
Signals linked to risks
Agent
Assess
Treat
Monitor
Indicators watched live
Agent
Report
Drafted from live data
Agent
Typical systems. Archer, MetricStream, ServiceNow IRM, data platforms
Appetite monitoring
Every day
Set limits
Measure
From source systems
Agent
Alert
Breaches flagged
Agent
Decide
Act
Typical systems. ERP, risk engines, BI tools
Incident to lesson
Every incident
Capture
From every channel
Agent
Classify
Type, size and cause
Agent
Respond
Link
To control and risk
Agent
Fix
Typical systems. Incident tools, loss databases, GRC tools
Scenarios and stress tests
On demand
Define
Gather
Data pulled and checked
Agent
Run
Across the business
Agent
Explain
Drivers written up
Agent
Decide
Typical systems. Risk models, finance systems, spreadsheets
Agent intervention point
The Risk control tower
Not a heatmap from last quarter. A live view of where risk sits against appetite, what’s moving and what the business should do about it.
Illustrative
Risk control tower
Sample data to show the view. Not client results.
Top risks
12
2 over appetite
KRI breaches
5
This month
Tested in full
78%
▲ from 12%
Repeat incidents
4
▼ from 17
Scenario time
3 days
▼ from 5 weeks
Board report
2 days
▼ from 12
This week’s risk brief
Supplier
A key packaging supplier shows signs of financial distress
Linked to the Procurement Office. Second source reviewed
Cyber
Phishing incidents up for the third week running
Cyber risk now over appetite. CISO briefed
Scenario
Board asked for a 20% energy price shock
Run overnight. Margin impact drafted
Lessons
Last quarter’s payment error fixed at the control
No repeat since the change
Appetite used by risk
Cyber
112%
Supply
105%
Credit
71%
Conduct
48%
Cyber and supply are over appetite. Both sit with other offices, which is why the view has to be shared.
Illustrative example. Figures are invented to show how the view works. In discovery we build it on your own data and KPIs.
Your industry changes the agenda
The canvas stays the same. The risks that keep the board awake do not. Here’s the question we hear most from risk leaders in each industry, and where agents help first.
CPG
How do we see commodity and supplier shocks before they hit margin?
Risk sensing and scenario runs
FMCG
How do we spot product safety and recall risk early?
Incident signals across markets
Retail
How do we track risk across thousands of stores and suppliers?
Live indicators and incident linking
D2C
How do we manage fraud, platform and supplier risk with a small team?
Risk sensing and live indicators
Automotive
How do we see supplier failure and quality risk before it stops the line?
Supplier risk sensing
Healthcare
How do we keep critical services running through any disruption?
Resilience scenarios and incident lessons
Energy
How do we stress test price, asset and transition risk together?
Scenario agents across the portfolio
Manufacturing
How do we stop the same plant incidents from coming back?
Incident to lesson loop
Logistics
How do we see disruption on routes and hubs in time to reroute?
Risk sensing on routes and hubs
BFSI
How do we watch credit and operational risk daily, not quarterly?
Live indicators and stress tests
B2B technology
How do we manage concentration risk on cloud and key customers?
Concentration indicators and scenarios
How the Risk Office connects
Most risks are owned somewhere else. Cyber sits with the CISO, supplier risk with procurement and capital with the CFO. The agents that serve the Risk Office share the same platform and data as those offices, so one signal reaches every owner at once.
The obligation relay
People, risk and sustainability
See where obligations slip between your offices.
Policy and controls
Compliance Office
Where rules become policies and controls.
Cyber risk
CISO Office
Where cyber threats are found and fixed.
Appetite and capital
CFO Office
Where risk meets the balance sheet.
How we’d start
Pilot 1
Live view of your top ten risks
↳
Risk sensing and indicator agents on your top ten risks for one quarter
↳
Signals linked to each risk and sent to its owner with evidence
↳
What the agents flagged compared with what the normal process caught
Your decision
Whether to extend it to the full register.
Pilot 2
Incidents that change the register
↳
Incident agents on one business unit’s incidents and losses
↳
Each one classified, root caused and linked to its control and risk
↳
Repeat incidents and register updates tracked
Your decision
Whether to run it across the group.
Both run under our Validation First Framework. They’re tested on your own data before you commit a larger budget, and if the numbers don’t hold, we tell you.
Your intervention map
Bring your register, your appetite statement and last quarter’s board risk report. We bring the Risk Office canvas. In one session we map it to your systems and owners, and mark where agents would pay back first.
01
Your Risk Office canvas
What you run and answer for, checked against how your team and risk owners really work.
02
Your value chain
The canvas placed on your industry and company, showing where your biggest risks really sit.
03
Your intervention points
Each leak with an agent design, its controls and the KPI it moves. Delivered as a mind map, an architecture view or an interactive dashboard.
AI for the Risk Office, answered
What can AI do for the Risk Office?
Agentic AI gives the Risk Office a live view instead of a quarterly one. Agents scan news, data and operations for emerging risks, keep the risk register current from incidents and audit findings, watch key risk indicators against appetite, run stress scenarios in days and draft the board risk report from live data. Your team spends its time on judgement and action.
How can AI spot emerging risks earlier?
Risk sensing agents read news, supplier signals, market data, incidents and operational data every day and link what they find to the risks on your register. When a signal matters, the risk owner gets an alert with the evidence and a suggested next step, weeks before it would show up in a quarterly review.
Can AI keep the risk register up to date?
Yes. Register agents read incidents, losses, audit findings and indicator movements as they happen and propose updates to the ratings, controls and actions on each risk. Risk owners approve the changes. The register stops being a quarterly workshop output and starts reflecting the business.
Can AI run stress tests and scenarios?
Agents gather the data, apply the scenario across your portfolio, suppliers or balance sheet and draft the results with the key drivers explained. A scenario that took weeks of spreadsheet work runs in days, so you can test more of them and respond when the board asks a new question.
How does AI change risk reporting to the board?
Reporting agents pull indicators, incidents, control results and appetite use from live data and draft the risk report for your review. The board sees current numbers with the story behind them, and your team spends days less assembling the pack.
Where should a Chief Risk Officer start with agentic AI?
With your top ten risks. Put risk sensing and live indicator monitoring on them for one quarter and compare what the agents flagged with what the normal process caught. Turning incidents into lessons that update the register is a strong second pilot.
