Uncategorized transactions across 40 locations compound into a close that never closes on time.
Someone is manually sorting problem entries across every entity every month. Bailey identifies the issues, suggests the right GL codes using existing patterns, and prioritizes cleanup by financial impact.
Your team is spending days every month sorting transactions that should already be clean.
Uncategorized entries pile up across entities. Inconsistent coding creates reconciliation headaches. By close time, the backlog is so large that speed wins over accuracy, and errors carry forward into the next period.
Uncategorized transactions flagged and categorized using your own coding history
Every month, hundreds of transactions sit in suspense accounts or default categories. Someone has to review each one, figure out the right GL code, and reclassify it manually. Bailey learns from your existing coding patterns and suggests the correct category automatically.
Inconsistencies and unusual postings caught before they compound
A vendor coded to supplies at one location and to services at another. A payroll entry posted to the wrong department. These inconsistencies go unnoticed until the consolidation fails or the audit flags them. Bailey catches them at the transaction level.
Close cycle time reduced without adding headcount
The bottleneck in most multi-entity closes is not the accounting itself. It is the cleanup work that has to happen before the accounting can start. Bailey eliminates the manual sorting so your team can focus on the review and analysis that actually requires judgment.
How Bailey works
Bailey connects to your accounting systems, learns your GL coding patterns, and continuously cleans up transactions so your team starts each close with data that is already organized.
Ingests transactions and learns your coding patterns
Bailey analyzes your historical transaction data across every entity to build a model of how your team categorizes entries. It learns vendor-specific codes, department mappings, and location-level variations.
Flags problem entries and suggests corrections
Uncategorized transactions, coding inconsistencies, and unusual postings are identified as they occur. Bailey suggests the correct GL code for each entry based on your own history, ranked by confidence level.
Prioritizes cleanup by financial impact
Not all transaction issues are equal. Bailey ranks cleanup tasks by their impact on your financial statements, so your team addresses the entries that matter most to close accuracy first.
What changes when Bailey is cleaning up transactions across your network
These are real scenarios multi-entity accounting teams deal with every close cycle. Here is how they play out with and without Bailey handling the cleanup.
1,200 uncategorized transactions pile up across 40 entities by month-end.
The accounting team spends the first three days of close sorting through suspense accounts. Each transaction requires opening the bank feed, identifying the vendor, determining the correct GL code, and reclassifying it. The work is tedious, error-prone, and delays everything downstream.
90% of uncategorized transactions pre-classified before close begins. Three days recovered.
Bailey categorized 1,080 of the 1,200 transactions automatically using the team’s own coding history. The remaining 120 were flagged with suggested codes and ranked by dollar impact. The team reviewed and approved the suggestions in a single session instead of spending three days on manual sorting.
The same vendor is coded to three different GL accounts across locations.
Location A codes the cleaning service to Facilities. Location B codes it to General & Administrative. Location C codes it to Outside Services. The inconsistency makes consolidated reporting unreliable and creates extra work during the audit when the auditor questions the variance.
Vendor coding inconsistency flagged across all three locations. Standardized in one batch.
Bailey detected that the same vendor was coded differently across locations and flagged the inconsistency with the recommended standard code based on the majority pattern. The team approved the correction and Bailey applied it across all three entities in a single action.
A $45,000 equipment purchase is coded as an expense instead of a capital asset.
The entry posts to Repairs & Maintenance because the vendor description matches a previous repair invoice. Nobody catches it during close because the team is focused on clearing the backlog. The misclassification understates assets and overstates expenses for the period.
Unusual expense amount flagged for review. Reclassified to capital assets before close.
Bailey flagged the $45,000 transaction as an outlier for the Repairs & Maintenance category based on historical posting patterns. The alert included the vendor, amount, and a suggested reclassification to capital assets. The controller reviewed and approved the correction before the books closed.
Bailey connects to 8,500+ systems your network already uses
Accounting platforms, ERP systems, banking feeds, and more. No data migration. Bailey reads directly from the financial systems your team works in every day.
Frequently asked questions
Bailey analyzes your historical transaction data to build a model of how your team categorizes entries. It learns vendor-specific codes, department mappings, amount thresholds, and location-level variations. The model improves continuously as your team approves or corrects suggestions.
Bailey suggests classifications and flags issues, but your team retains full control over approvals. High-confidence suggestions can be auto-applied if your team configures that preference, while lower-confidence items are queued for human review. Nothing posts without authorization from your accounting team.
The time savings depend on the number of entities and the volume of uncategorized transactions. Teams managing 20 or more entities typically recover two to four days per close cycle by eliminating manual transaction sorting. The reduction compounds as Bailey learns your patterns and its classification accuracy improves over time.
Bailey connects to major accounting platforms including QuickBooks, Xero, Sage, NetSuite, and most ERP systems. It ingests transaction data, chart of accounts structures, and historical coding patterns. The integration is read-write, so approved corrections can be posted back to the source system.
Bailey is built for any organization that manages accounting across multiple entities. Franchise networks are the primary use case because the transaction cleanup problem scales directly with the number of locations. Multi-entity businesses, portfolio companies, and property management firms with high transaction volumes benefit from the same capabilities.
Ready to stop spending the first week of every close sorting transactions?
See how Bailey categorizes transactions using your own coding history, flags inconsistencies, and prioritizes cleanup by financial impact.