Match Every Trade Against Custodian and Broker Records Automatically
Trade reconciliation isn't just checking two numbers against each other. Kosh AI checks the full chain, from execution to settlement.
Your internal record of a trade and the custodian's record of it should agree. When they don't, you need to know why fast.
Not every trade reconciles the same way. Kosh AI supports the matching styles that fit different trade types.
A break that just says 'unmatched' doesn't help anyone. Kosh AI tells you what's probably wrong.
A trade passes through multiple internal systems before it settles. Kosh AI checks that it stays consistent at every step.
Regulators and auditors don't just want to know a trade settled. They want to see the record of how it got there.
Four stages that run continuously from trade execution through settlement.
Trade reconciliation needs differ by asset class, desk structure, and settlement timeline.
High trade volume with tight settlement windows that leave little room for a break to sit unresolved.
Settlement conventions and accrued interest calculations that need matching logic built for the asset class.
Multi-leg trades and collateral movements that need reconciliation across more than one counterparty record.
Trade confirmations checked quickly enough to catch an error before it affects same-day settlement.
The team responsible for resolving breaks between front-office trades and back-office settlement records.
Oversight teams that need a complete, auditable record of every trade's reconciliation history.
Compressed settlement windows that leave almost no time for a manual break investigation.
Different settlement conventions across markets that need to reconcile against a single internal record.
Trade volumes too high for manual reconciliation to keep pace with, regardless of settlement timeline.
Catching a break days earlier means it's resolved long before settlement is at risk.
A break flagged with its likely cause gets resolved faster than one that just says 'unmatched.'
T+1 environments leave no time for manual reconciliation delays.
Equities, fixed income, and derivatives each get matching logic suited to how they actually trade.
Every match and resolution is logged automatically, not reconstructed after the fact.
A busier trading day doesn't mean a manual reconciliation backlog the next morning.
Kosh AI connects directly with all major banks and ERPs, enabling real-time data sync for faster, more accurate reconciliations—no manual uploads, no delays.
Matching a trade correctly means understanding why it might not match, not just flagging that it doesn't.
Learns the typical signature of a timing break versus a genuine pricing error, speeding up triage.
Surfaces the breaks most likely to affect settlement first, instead of a flat, chronological queue.
Adjusts matching tolerances over time based on which thresholds actually reduce false breaks without hiding real ones.
Identifies more trade types that can safely skip manual review as confidence in the matching pattern grows.
Automated trade reconciliation software checks that a trade, as your firm's own systems recorded it, matches what the custodian, broker, or counterparty reports for that same trade. It covers everything from the moment a trade executes through to final settlement, catching mismatches in price, quantity, timing, or counterparty detail along the way.
The stakes here aren't abstract. A break that isn't caught and resolved before settlement can delay the trade, trigger a failed settlement, or create regulatory reporting problems, especially in markets that have moved to compressed settlement cycles like T+1. Manual reconciliation, built around spreadsheets and end-of-day checks, often doesn't leave enough time to catch and fix a break before it becomes a settlement problem.
Kosh AI's automated trade reconciliation software matches trades against custodian and broker records continuously, not just at end of day, and categorizes every break by its likely cause, so operations and compliance teams can resolve what's actually wrong instead of starting an investigation from a blank comparison.
Reconcile a day's trades by hand, then compare that to continuous, automated matching. In a T+1 settlement environment, the gap matters more than ever.
| Feature | Automated Trade Reconciliation | Manual Trade Reconciliation |
|---|---|---|
| Matching Frequency | Continuous, as trade and custodian data arrives. | Usually a single end-of-day batch check. |
| Break Categorization | Each break labeled by likely cause automatically. | An analyst has to manually investigate each unmatched item. |
| Settlement Risk | Aging models flag breaks closest to settlement first. | Breaks are typically worked in the order they're found, not by urgency. |
| Multiple Asset Classes | Matching logic configured per instrument type. | Different asset classes often need separate manual processes. |
| T+1 Readiness | Fast enough to resolve breaks within compressed settlement windows. | Manual investigation often can't keep pace with same-day resolution needs. |
| Audit Trail | Built automatically as part of the matching process. | Assembled after the fact from trade blotters and email threads. |
The move to T+1 settlement in major markets changed the math on trade reconciliation. A process built around end-of-day batch checks used to leave a comfortable window to catch and fix a break before settlement. That window has shrunk, and in some cases disappeared entirely, which means a break caught a day late isn't just inconvenient anymore, it's a real settlement risk.
Manual reconciliation also struggles with scale in a way that becomes obvious during a busy trading period. An operations analyst who can comfortably work through a normal day's breaks gets overwhelmed the moment volume spikes, and that's exactly when the risk of a missed break is highest.
Kosh AI's automated trade reconciliation software matches trades against custodian and broker data continuously rather than in a single daily batch, which means breaks surface with hours to resolve them instead of minutes. Combined with automatic break categorization, operations teams spend their time fixing problems instead of finding them.
Trade reconciliation gets harder in a few specific, predictable ways as a trading operation grows.
Past a certain volume, manually checking every trade against custodian records stops being realistic within a single trading day.
A T+1 environment leaves little room for a break discovered at end-of-day batch processing to be resolved in time.
Equities, fixed income, and derivatives each need matching logic suited to how they settle, not one generic process.
Different custodians and brokers format their statements differently, and matching logic needs to handle that variation.
A few habits keep trade reconciliation fast enough to matter in a compressed settlement environment.
Waiting for a single daily batch check means every break gets discovered with less time to fix than it needs.
A break close to settlement deserves attention before one with days of runway left, regardless of which was found first.
A tolerance set once and never revisited either lets real errors through or buries the team in false breaks.
An audit trail built during resolution is far more reliable than one reconstructed from memory weeks later.
Bring a recent batch of trade breaks to the call. We'll show you how Kosh AI would have caught and categorized them automatically.
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