Fund Controller
Reconcile positions and investigate breaks
What You Do Today
Perform daily reconciliation of positions, cash, and transactions between the accounting system, prime broker, administrator, and custodian. Investigate and resolve breaks, aging items, and systemic reconciliation issues.
AI That Applies
AI automates matching across systems, classifies break types, and suggests resolution paths based on historical patterns. ML reduces false breaks by learning legitimate timing differences.
Technologies
How It Works
The system ingests historical patterns as its primary data source. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context.
What Changes
Reconciliation matching becomes more intelligent, with AI resolving routine breaks automatically and prioritizing genuine issues.
What Stays
Investigating complex breaks that span multiple systems and counterparties, and identifying whether a break indicates a control failure versus a timing difference, require experienced operational judgment.
What To Do Next
This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.
Establish Your Baseline
Know where you are before you move
Before adopting AI tools for reconcile positions and investigate breaks, understand your current state.
Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.
Define Your Measures
What to track and how to calculate it
Time per cycle
How to calculate
Measure how long reconcile positions and investigate breaks takes end-to-end today, then after AI adoption.
Why it matters
The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.
Quality of output
How to calculate
Track error rates, rework frequency, or stakeholder satisfaction scores before and after.
Why it matters
Speed without quality is just faster mistakes. Measure both.
Start These Conversations
Who to talk to and what to ask
your CFO or VP Finance
“What data do we already have that could improve how we handle reconcile positions and investigate breaks?”
They're prioritizing which finance processes to automate first
your ERP or finance systems admin
“Who on our team has the deepest experience with reconcile positions and investigate breaks, and what tools are they already using?”
They know what automation capabilities exist in your current stack
your FP&A counterpart at a peer company
“If we brought in AI tools for reconcile positions and investigate breaks, what would we measure before and after to know it actually helped?”
They can share what worked and what didn't in their AI rollout
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.