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How Do You Reduce Employee Theft at the Register?

Reduce register theft by putting controls on the three transactions where a cashier can move goods or money without a matching sale: voids and no-sales, discount overrides, and no-receipt refunds. Then review the exceptions those controls flag on a fixed schedule, so a pattern tied to one cashier login gets caught while it is small. Pilot each change in one store before rolling it out chainwide.

What NRF’s internal theft numbers cover, and why they’re dated

The National Retail Federation’s 2023 National Retail Security Survey, run with the Loss Prevention Research Council, covers FY2022 loss. It put internal theft at 29% of shrink loss and process and control failures at 27% (NRF survey). Treat those figures as dated: after more than three decades of annual shrink research, NRF did not publish a shrink report in 2024 and pointed to the 2023 survey as the latest available statistics (Retail Dive). The same survey reported merchandise theft, refund fraud, cash and deposit theft, and sweethearting as the top four internal theft methods and an average internal theft loss of $2,180 per investigation (NRF survey). Map your own voids, discounts, no-receipt refunds and cash handling against those four methods before you add any new register control.

Which register controls are backed by evidence, and which aren’t

The controls below fall into two evidence tiers. A few rest on studies or survey data from a named setting. The rest are reasonable responses to what NRF’s survey says retailers lose, with no cited study testing the control itself. None of the studies cited here was run at a retail register, so each row names where its evidence comes from.

Register control What it targets Evidence status Evidence setting
Exception-based reporting and POS anomaly alerts Voids, no-sales and refund patterns tied to one login Partly supported Among retailers’ top five internal-theft tools in NRF’s 2023 survey (use, not a measured effect)
Discount and override limits Sweethearting and discounts to friends Pilot hypothesis NRF names sweethearting a top-four method; no cited study tests override limits
No-receipt refund controls (limits, approval, ID capture) Refund fraud Pilot hypothesis Reasoned from NRF’s refund fraud finding; no cited study tests these controls
POS-data monitoring software Theft and revenue at the restaurant level Partly supported 392 restaurants in 39 states, food service
Active, scheduled exception review All of the above Partly supported Occupational fraud data across industries

The strongest measured result came from outside retail: when 392 restaurants in 39 states added point-of-sale monitoring software, theft dropped 22 percent and revenue rose about 7 percent (Pierce et al.). Build the no-receipt refund control anyway, because the problem it targets is already named in the survey data, and measure it in a later pilot once the exception review is running. Discount and override limits are the least supported row: the cited research names sweethearting as a top-four method but gives no tested override mechanism, so set who can approve an override, and up to what amount, as local policy and measure it in the pilot.

How do I control no-receipt refunds and how often should I review register exceptions?

NRF’s 2023 survey names refund fraud as one of the top four internal theft methods (NRF survey). The refund controls below follow from that finding. None has been tested in the research cited here, so each is a pilot hypothesis.

Refund control Mechanism
Dollar limit before manager approval Caps what one cashier can refund unsupervised
Manager approval on every no-receipt refund Adds a second person to the decision
ID capture on no-receipt refunds Ties the refund to a customer record as well as a register login
Return to original tender Removes cash as the default no-receipt payout
Review practice Who reviews Evidence status Setting
Daily review of flagged exceptions Shift lead or asset protection associate Partly supported Active detection finds fraud faster than passive methods, cross-industry
Escalation when one login repeats across flagged exceptions Supervisor or LP Partly supported Exception-based reporting is among retailers’ top five internal-theft tools
Tip-driven review outside the normal cycle Whoever receives the tip Partly supported Tips detected 43% of frauds in ACFE’s cross-industry study

Set a refund limit your POS can enforce automatically, so the rule holds on a busy shift without anyone having to remember it. Reviewing exceptions on a fixed schedule is this article’s recommendation, and a daily review is the version it favors. ACFE’s 2026 report suggests fraud can be uncovered up to four times faster with active detection methods than with passive ones (ACFE 2026 report), and 43% of the frauds in its study were detected after a tip was reported (ACFE 2026 report). Both figures cover fraud cases across industries. Start the daily exception review this week, then pilot the automatic refund limit once your POS can enforce it.

Why process changes are a better bet than reminders

A meta-analysis by Mertens and colleagues, covering many behavioral domains and not retail, found that interventions targeting the structure of choice alternatives consistently outperformed interventions that described the alternatives or reinforced intentions, a category that includes reminders (Mertens et al.). A later reanalysis by Maier and colleagues, correcting for publication bias, found evidence against an effect for information and assistance interventions and called the evidence for structural interventions undecided (Maier et al.). Neither analysis gives reminder-type interventions an edge. At the register, a poster asking cashiers to be honest works like a reminder, and a system that will not post a refund without a second login changes the structure of the choice. Put the budget into the login requirement first.

Explain new register controls before you enforce them, then back the supervisors who do

A field experiment at a Dutch local government department, outside retail, tested nudges to raise compliance with a policy requiring employees to wear an identifying lanyard badge, where compliance had been low. The researchers found insufficient support for the nudges working, and they hypothesize that the nudges failed to change attitudes about the policy and led to reactance among some employees (Dewies et al.). Announce a new register control in a five-minute huddle with the reason attached, such as refund fraud or drawer accuracy, before you enforce it.

A forest-products mill, also outside retail, set a goal with its union executive committee to cut theft from about a million dollars a year to zero (Latham). Theft dropped to near zero and stayed inconsequential by company accounting methods for three years (Latham). Latham warns the result likely generalizes only to settings where theft is a way to find excitement at work.

Latham recommends that upper management tell supervisors they will be supported for insisting on and monitoring honest behavior (Latham). Tell your supervisors before the rollout that you will back them when they enforce the new rule.

Pilot new register controls for 60 to 90 days before rolling them out chainwide

Pick one control from the partly supported rows. Exception-based reporting paired with a daily review is the strongest combination in the tables above. Run it in one store for 60 to 90 days against a comparison store that keeps its current process. A sibling store makes a better baseline than last year’s numbers, since seasonality and promotions move exceptions on their own.

Scale the control if the pilot store meets the go/no-go threshold you set before day one on flagged exceptions, refund dollars and drawer variance, measured against the comparison store. If it does not, the control may have missed the problem. Make the scale-up call by day 90.

What to do this week

Frequently asked questions

How can a store catch an employee stealing from the register?

Start with the exception reports your point-of-sale system already produces. NRF's survey lists exception-based reporting and point-of-sale anomaly alerts among the top five tools retailers use to prevent, detect or investigate internal theft (NRF survey). Sort flagged voids, no-sales and refunds by cashier login so one person's repeated exceptions stand out from the store total.

Can a retailer terminate an employee for stealing from the register?

Termination depends on documented evidence and company policy, and the exception reports your register controls produce are part of that evidence. Before acting on them, read employee theft investigation legal rights and check the decision with your HR team or employment counsel.

What counts as sweethearting, and how is it different from refund fraud?

NRF's 2023 survey groups sweethearting with sliding and free bagging as ways of passing merchandise to friends. Refund fraud is a separate method on the same survey's list (NRF survey). One gives goods away during a sale; the other pays out money through a return, so each needs its own control.

With NRF's shrink figures getting old, what should a store track instead?

Your own register data ages better than an industry average from FY2022. Track flagged-exception rates, refund dollars per cashier and drawer variance monthly, and compare each store against a similar sibling store and its own history, using a shrink calculator as a cross-check on the national percentage.

Sources

  • abscosolutions.com https://abscosolutions.com/wp-content/uploads/2024/03/nrf_national_retail_security_survey_2023.pdf
  • retaildive.com https://www.retaildive.com/news/no-nrf-annual-retail-shrink-report-2024/729009/
  • source.washu.edu https://source.washu.edu/2013/09/it-monitoring-effective-in-deterring-restaurant-fraud/
  • acfe.com https://www.acfe.com/-/media/files/acfe/pdfs/rttn/2026/2026-report-to-the-nations.pdf
  • pmc.ncbi.nlm.nih.gov https://pmc.ncbi.nlm.nih.gov/articles/PMC8740589/
  • pmc.ncbi.nlm.nih.gov https://pmc.ncbi.nlm.nih.gov/articles/PMC9351501/
  • repub.eur.nl https://repub.eur.nl/pub/136435
  • goal-lab.psych.umn.edu https://goal-lab.psych.umn.edu/orgPsych/2020/readings/9.%20Counterproductive%20Behavior/Latham%20%282001%29.pdf