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Cash management in DualEntry gives you a single workspace for monitoring bank activity, matching it to your ledger, and closing out reconciliations. You connect bank accounts to pull in transaction feeds, reconcile those feeds against GL entries, and let Bank Match AI handle the routine matching so you focus on exceptions.

Bank connections

DualEntry connects to your bank through certified aggregator feeds or through manual CSV and BAI imports. To confirm a specific bank is supported, search for it in Company → Bank Connections → Add Bank Connection; see Provider coverage and checking whether a bank is supported. Once linked, transactions flow into a staging area where they wait to be matched against ledger activity. You can connect checking accounts, savings accounts, credit cards, and lines of credit, each tied to a GL cash or liability account. Aggregator-connected accounts refresh automatically on a rolling schedule, typically every four to six hours. You can also trigger a manual refresh at any time. Manual connections use CSV or BAI file uploads and don’t refresh on their own: you upload a new file each time you want to bring in recent activity. Each connection maps to exactly one GL account, which determines where transactions appear in your ledger and which account is reconciled. DualEntry supports multiple connections per organization, and each operates independently with its own feed schedule, GL mapping, and reconciliation history. For setup steps and troubleshooting, see How to Connect Bank Accounts. For the underlying feed architecture and security model, see Banking Connections: Paths, Sync, and Security.

Bank reconciliation

Reconciliation confirms that every bank statement line has a corresponding GL transaction and that the ending balance agrees. DualEntry supports auto-matching (via rules and AI), manual matching, and adjustment entries for items like bank fees and interest that may not yet exist in your ledger. You typically reconcile monthly, but nothing prevents you from running a reconciliation at any cadence. When you open a reconciliation, DualEntry loads unreconciled bank feed transactions and GL entries into a side-by-side workspace. Auto-matching runs first: rule-based matching evaluates your custom rules, then Bank Match AI scores the remaining pairs. Both stages produce suggestions you accept rather than finished matches, and items neither process catches stay unmatched for you to handle manually. Once the difference between matched bank items and matched GL items reaches zero, you complete and optionally certify the reconciliation. Certification stamps the reconciliation with your user ID and a timestamp, visible in the audit trail. See How to Reconcile Bank Accounts for the full workflow.

Bank Match AI

Bank Match AI is DualEntry’s ML-based matching engine. It scores each bank feed transaction against candidate GL entries, auto-matches high-confidence pairs, and leaves everything else on the Bank Match page for you to work through. Over time it learns from your corrections, so manual work decreases as the model adapts to your patterns. The model weighs multiple signals: amount proximity, date proximity, description similarity, and historical patterns from your prior reconciliations. A two-tier threshold system controls what gets auto-matched versus what waits for you on the To Match and For Approval tabs. Those thresholds are fixed in the product; there is no settings page for tuning them. What you control is the rule set, which you manage on the Bank Match page under Close Management → Close Workflows → Bank Match. New organizations start with a general-purpose model. After three to four completed reconciliation cycles, the model has enough organization-specific data to meaningfully improve. Most organizations see auto-match rates climb from roughly 60% to 85-90% within six months. For details on confidence scoring, override behavior, and accuracy metrics, see Bank Match AI.

How the pieces fit together

Bank connections supply the raw data. Bank Match AI and your custom rules propose matches. Reconciliation is where you confirm those matches, handle exceptions, and certify the period. Together, they replace the spreadsheet-based reconciliation workflows that most firms still maintain outside their GL. The typical flow moves in one direction: connect a bank account, wait for transactions to sync, open a reconciliation, let auto-matching handle the routine pairs, review and resolve exceptions, then complete and certify. Each step feeds into the next: connections populate the staging area, the staging area feeds the reconciliation workspace, and completed reconciliations generate the audit trail and history you need at period end. Because bank connections, matching, and reconciliation share the same data model, everything stays in sync. A transaction matched during reconciliation is immediately reflected in the bank connection’s sync status, and adjustment entries created during reconciliation flow directly into your journal entry log. For related topics, see:
Last modified on August 18, 2026