If you work in retail finance or accounting, Q1 has a predictable rhythm: the holiday rush ends, and the cleanup begins. Because while Q4 is where revenue peaks, Q1 is where complexity hits the books – late settlements, gift card redemptions, returns, chargebacks, and variances that only appear when there’s no time left in the close.

This last holiday season was the biggest yet. The National Retail Federation (NRF) forecasted that U.S. holiday sales for November–December 2025 would surpass $1 trillion for the first time. But for finance, those numbers show up as a flood of micro transactions across more systems than ever.

And then come the returns.

NRF’s 2025 Retail Returns Landscape projects nearly $849.9 billion in returns across the industry for 2025 (about a 15.8% return rate). Online is the toughest channel, with an estimated 19.3% of online sales expected to be returned. Plus, return fraud remains an ongoing concern for the industry, with the report estimating 9% of all returns to be fraudulent.

So, if Q1 feels like a second closing rush all over again, it’s not your imagination.

This is also the moment when teams can start to implement changes and decide, “How do we never do that again?” With a few, AI-enabled, intelligent close practices, next year’s Q4 rush and Q1 cleanup can be much less stressful, and allow you to actually enjoy the season again.

Retail doesn’t just need a faster close, it needs a smarter one

In many industries, close pain is mostly about month-end. In retail, the close is more continuous—built on daily reconciliations that require ongoing attention. Did every sale (in-store and online) actually make it to the bank, and does it match what landed in the ERP/GL?

In a normal month, half of all finance teams still take 6+ business days to close the books, even outside of holiday volume spikes. When reconciliations happen in spreadsheets and email threads, the close remains reactive—investigating what went wrong after the fact.

An intelligent close puts you in proactive control. It treats reconciliation, matching, exception management, and documentation as a daily, continuous workflow, so month-end becomes streamlined signoffs, not discovery of last-minute issues.

Trintech provides retailers with a “daily system of control” that connects transactions from in-store and online from any tender to bank settlement and ERP/GL posting, so your sales audit stays clean throughout the period instead of exploding at month-end.

AI’s role in the intelligent close: 3 practical upgrades for retail

AI in finance doesn’t have to mean risky black-box decisions. With so much hype out there, the key is to apply AI in ways that are controlled, transparent, and measurable. In retail, AI can take manual burdens off in three very real ways.

1. Scale your matching, not your headcount.

With seasons that ebb and flow, it’s unrealistic to hire enough temporary workers to manually match millions of transactions across POS, processors, and banks, especially when your data formats don’t match up either.

As a Trintech customer with Abercrombie & Fitch joked, “Accounting gets no love when it comes to headcount.” However, with Trintech, the global clothing retailer processes roughly 150 million transactions a year and their core reconciliation team hasn’t grown over five years.

Trintech solutions are purpose-built for high-volume environments like retail, automating over 90% of daily, monthly, and periodic reconciliation processes. That automation is designed for complex, multi-source scenarios (POS → processor → bank → ERP/GL), allowing finance to monitor rules and approvals at a higher level.

2. Smarter exception handling, less chasing.

The problem with Q1 cleanup isn’t just routine exceptions, it’s the variety of exceptions that need to be addressed. Some breaks are urgent (missing deposits, duplicate refunds, fraud signals). Others can be normal, expected timing differences that will resolve quickly. In spreadsheet-based processes both remain open, waiting for someone to deal with them.

AI helps triage low-risk exceptions, so teams spend time where it matters most, prioritizing higher-risk issues, spotting recurring patterns, and providing context to the right owner so exceptions are resolved faster and more accurately.

This is the “never do that again” lever: solve issues while they’re still fixable—before the period closes and write-offs become the only path to resolution.

3. Make audit readiness automatic.

Even when reconciliations are done, audit prep can still eat up days, tracking down support, proving who approved what, understanding adjustments, and stitching together evidence from emails, shared drives, and spreadsheets.

With an intelligent close, the audit trail is created as work happens, not rebuilt later. Approvals, segregation of duties, timestamps, comments, and supporting documents are captured in a centralized workflow, so auditors can trace activity end-to-end without your team spending time searching for evidence. Trintech’s workflow-based approach automatically generates audit trails and governance controls within tasks and approvals. Supporting documentation and comments are kept in one centralized place tied to the transaction-level detail. Many Trintech customers, like Racetrac, give their auditors direct access to the system, so their accounting teams don’t have to do any extra audit prep.

Spend less time preparing for audits, with fewer back-and-forth requests because the evidence is already organized, controlled, and traceable.

Prevent the next holiday hangover before it’s too late

Once Q2 arrives, retail shifts back into planning and execution, which makes Spring the ideal time for close modernization. You still have fresh perspective (and data) from the season you just lived through, plus enough time to make meaningful changes before the next holiday peak.

Start with a holiday close postmortem: identify the biggest exception drivers, where volume spiked, what aged the longest, and where exposure or write-offs crept in. What cost you the most time, rework, and frustration – and why? Then, use those insights to pilot AI where outcomes are easy to measure, such as higher auto-match rates, fewer aged exceptions, shorter close cycle times, and stronger audit readiness.

With AI-powered matching, smarter exception handling, and embedded close support, retailers can turn the holiday hangover into a repeatable improvement cycle, so each season becomes cleaner than the last, making your close predictable, controlled, and far less dramatic.

Written By: Elizabeth Connors