Key risk indicators examples — what KRIs are you actually tracking?
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I'm building out our KRI dashboard and looking for practical key risk indicators examples from other organizations. We have the basics — overdue audit findings, policy exceptions, customer complaints — but I want to go deeper.
Specifically interested in:
- Operational risk metric examples (we're in financial services)
- Leading indicators rather than lagging ones
- Metrics that actually predict problems before they happen rather than just confirming something went wrong
What's on your dashboard and which ones have actually proven useful in triggering early action?
Here are the key risk indicators examples that we track and have found genuinely predictive:
Operational:
- Staff turnover in control functions (leading — high turnover predicts control failures 3-6 months later)
- Overtime hours in operations (leading — correlates with increased error rates)
- System downtime hours (concurrent — but early warning of tech debt issues)
- Number of manual workarounds in production processes
Compliance:
- Regulatory finding closure rate (are we fixing things faster or slower than they arrive?)
- Training completion rates by business unit (low completion = future compliance gaps)
- Whistleblower report volume (both too many and too few are concerning)
Financial crime:
- Alert-to-SAR conversion ratio (if it drops suddenly, either risk decreased or your analysts are getting sloppy)
- Average investigation time (creeping upward = capacity problem)
Credit/counterparty:
- Watchlist additions as % of total portfolio
- Covenant breach rate trending
The ones that saved us: staff turnover in our ops team was a leading indicator that predicted a spike in processing errors about 4 months later. We caught it early and brought in temporary support before it became a real problem.
Examples of metrics that looked useful but weren't: number of risk events reported. It went up and down for random reasons and never correlated with actual risk outcomes.
2 réponses
Great list from Amit. One framework tip: organize your KRIs using a leading → concurrent → lagging classification. Most organizations are heavy on lagging indicators (things that already went wrong) and light on leading ones (early warnings).
For operational risk metrics in banking specifically, regulators like the OCC and EBA have published guidance on what they expect to see in risk appetite frameworks. These can be useful templates even if you're not directly supervised by them.
Also: fewer is better. A dashboard with 50 risk metrics is a dashboard nobody looks at. We recommend 12-15 at the board level, with the ability to drill into more granular data for management reporting.
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