I have some questions... - Where do you see the biggest “fake automation” in NAV ops—something branded as automated but still heavily manual behind the scenes? - What’s the one process you’ve “optimised” three times already… and it still keeps coming back? - In your experience, what creates more operational risk: non-standard client promises, or poor upstream data quality? - If you could change one thing tomorrow—system design, data governance, or operating model—which would actually move the needle fastest? - What’s the most common “Alex problem” you’ve seen—one key person holding a critical process together—and why does it keep happening? - Do you think the industry is genuinely reducing exceptions, or just getting faster at managing them? - What would a truly modern NAV production model look like to you—human-led with AI support, or AI-led with human exception handling?

Before you sign off the NAV, take 3 minutes to validate that reconciliations are genuinely clean (not just “cleared”): ✅ Custody vs accounting positions truly match– Any breaks hidden by mapping rules or tolerances?– Any unmatched lots/ISINs sitting in “other” buckets?– Any corporate action-driven breaks (splits/mergers) not resolved? ✅ Cash reconciliations tell a clean story– Cash breaks explained by timing (trade vs settle) and documented?– Any aged breaks or recurring small differences?– Any FX translation differences incorrectly treated as breaks? ✅ Income & expenses recon are not “forced”– Dividends/interest accruals match expectations and schedules?– Any breaks cleared via plugs/suspense without evidence?– Any items repeatedly carried forward with no owner? Why this matters: Reconciliations are not a tick-box exercise — they are your early warning system. If a recon is “clean” only because it was forced, the risk didn’t disappear; it simply moved forward. Pro move: If you can’t explain a break in one sentence with evidence, it’s not resolved — it’s deferred.

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Before you finalise the NAV, take 3 minutes to scan for stale data and manual overrides: ✅ Any stale or missing inputs?– Prices, FX, benchmarks, or rates still showing prior NAV date?– Any “default” values used (0 price, 1.00 FX, fallback sources)?– Any missing files or partial loads from vendors? ✅ Any manual overrides applied today?– Manual prices, FX, accrual adjustments, or trade edits?– Were they reviewed/approved per your control process?– Are they documented clearly (who/why/when)? ✅ Any breaks “fixed” by force?– Reconciliations cleared via plugs or temporary accounts?– Unmatched items moved to suspense without a resolution plan?– Anything that balances but doesn’t make sense? Why this matters: Many NAV issues start as “small” manual fixes and stale inputs. Overrides are not bad — undocumented overrides are. A clean audit trail and a quick sanity check prevents invisible errors from rolling forward. Pro move: If you had to override it, you must be able to explain it in one sentence and point to evidence.

Before you sign off the NAV, take 3 minutes to sanity-check expenses and fee accruals: ✅ Do management fees and admin fees look reasonable?– Fee rate matches the latest agreement / share class?– AUM basis correct (gross vs net assets, exclusions applied)?– No sudden jumps or drops vs prior NAV days? ✅ Are expense accruals behaving normally?– Known monthly/quarterly accruals trending as expected?– Any “stuck” accruals rolling forward and never reversing?– Any unusually large true-ups posted without explanation? ✅ Are payables and invoices clearing on time?– Old payables still sitting open with no settlement?– Any expenses posted twice (invoice + accrual)?– Any suspense/temporary accounts used to park expenses? Why this matters: Fees and expenses rarely cause dramatic breaks day-to-day — which is exactly why errors here survive. Accrual drift compounds quietly and eventually becomes a client escalation, audit finding, or a painful true-up. Pro move: Treat fee accruals like a trend control: if the pattern changes, investigate before it becomes “normal.” Building better NAV production habits, one day at a time.