None of them require sophisticated detection to prevent.<\/strong> They require somebody checking, and controls that make checking practical.<\/p>\nThat is the frame for everything below.<\/p>\n
What anomaly detection does<\/h2>\n
It learns what your transactions normally look like, and flags what does not fit.<\/p>\n
What it catches well:<\/strong><\/p>\nDuplicate bills.<\/strong> Same vendor, similar amount, close dates. Simple and effective.<\/p>\nAmounts outside the usual range.<\/strong> A vendor who normally bills a few hundred suddenly billing tens of thousands.<\/p>\nChanged supplier bank details.<\/strong> This is the highest-value single flag in the list. Payment redirection fraud is common, expensive, and almost always visible as a bank detail change on an existing supplier.<\/p>\nUnusual timing.<\/strong> Transactions posted at odd hours, or backdated into closed periods.<\/p>\nNew vendors paid quickly.<\/strong> A vendor created and paid within days, with no prior history.<\/p>\nRound-number patterns.<\/strong> Amounts that avoid an approval threshold \u2014 several bills at just under the limit.<\/p>\n\n
FIGURE 1: THE FLAGS WORTH HAVING, MOST VALUABLE FIRST<\/p>\n
\n
\n
Changed supplier bank details<\/p>\n
\n- Payment redirection fraud is common and expensive. This one flag catches most of it.<\/li>\n<\/ul>\n<\/div>\n
\n
Duplicate bills<\/p>\n
\n- Same vendor, similar amount, close dates. Simple and it recovers real money.<\/li>\n<\/ul>\n<\/div>\n
\n
Amounts just under an approval limit<\/p>\n
\n- Several bills at 4,900 against a 5,000 threshold is a pattern worth seeing.<\/li>\n<\/ul>\n<\/div>\n
\n
New vendors paid quickly<\/p>\n
\n- Created and paid within days with no history.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n
What it does not do<\/h2>\n
Four honest limits.<\/p>\n
It does not find fraud that looks normal.<\/strong> A slightly inflated price from a real supplier, consistently, over years, does not stand out. That is caught by comparing against a market price, not by anomaly detection.<\/p>\nIt does not know intent.<\/strong> A flag says unusual, not dishonest. Most flags are errors or legitimate exceptions.<\/p>\nIt produces false positives<\/strong>, especially early. That is unavoidable and it is the learning period.<\/p>\nIt does not replace controls.<\/strong> This is the important one, and it deserves its own section.<\/p>\nThe controls that matter more<\/h2>\n
Segregation of duties<\/strong> does more to prevent fraud than any detection system.<\/p>\nThe principle is simple: the person who can create a supplier should not be the person who can pay one.<\/strong> The person who approves a purchase should not be the person who receives the goods.<\/p>\nWhere one person can do the whole cycle, fraud is easy and detection is your only defence. Where duties are separated, most of these schemes require two people to cooperate \u2014 which is a much higher bar.<\/p>\n
In a small company perfect separation is not always possible. Even partial separation helps significantly, and knowing where the gap is matters.<\/p>\n
Four other controls, all mundane and all effective:<\/strong><\/p>\nVerify bank detail changes by phone<\/strong>, using a number you already had, not one on the email requesting the change.<\/p>\nApproval limits that are actually enforced<\/strong>, not worked around when someone is in a hurry.<\/p>\nDeactivate leavers promptly.<\/strong> Access that outlives employment is a genuine risk and it is extremely common.<\/p>\nIndividual logins.<\/strong> Shared accounts destroy every audit trail your system keeps. You can see what was done and not who did it.<\/p>\n\n
FIGURE 2: WHAT PREVENTS AND WHAT DETECTS<\/p>\n
\n
\n
Prevention \u2014 do these first<\/p>\n
\n- Separate creating vendors from paying them<\/li>\n
- Verify bank changes by phone<\/li>\n
- Enforce approval limits<\/li>\n
- Individual logins, leavers deactivated<\/li>\n<\/ul>\n<\/div>\n
\n
Detection \u2014 useful, but second<\/p>\n
\n- Anomaly flags on unusual transactions<\/li>\n
- Duplicate bill matching<\/li>\n
- Three-way match variances<\/li>\n
- Audit trail review<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n
Three-way matching, again<\/h2>\n
It appears in every purchasing article for a reason. It is the single strongest control available.<\/p>\n
Comparing what was ordered, what was received and what was billed catches invoices for goods that never arrived, prices different from the agreement, and quantities inflated after delivery.<\/p>\n
And it only works if somebody counts the receipt.<\/strong> A receipt validated at the ordered quantity without counting makes the whole match meaningless \u2014 you are comparing an assumption against itself.<\/p>\nThis is not a technology point. It is a habit that has to be trained and occasionally checked.<\/p>\n
Expenses<\/h2>\n
The area where small fraud is most common, because amounts are small enough not to attract attention.<\/p>\n
What helps:<\/strong><\/p>\nReading receipts automatically, so the claimed amount is compared against the document rather than typed by the claimant. Flagging duplicate claims. Flagging claims without a receipt attached. Comparing claim patterns between people in similar roles.<\/p>\n
What helps more:<\/strong> a manager who actually looks. Automated flags surface candidates; somebody still has to look at them and be willing to ask.<\/p>\nHandling a flag<\/h2>\n
Worth planning before you switch anything on.<\/p>\n
Most flags are not fraud.<\/strong> They are errors, unusual but legitimate transactions, or the system still learning.<\/p>\nInvestigate quietly.<\/strong> Check the document, the order and the receipt before speaking to anyone. A wrong accusation causes lasting damage and is very hard to undo.<\/p>\nHave a defined route.<\/strong> Who investigates, who is told, what happens if something is genuinely wrong. Deciding this in the moment, under pressure, goes badly.<\/p>\nKeep records.<\/strong> Both of what was found and of what turned out to be nothing.<\/p>\n\n
FIGURE 3: WHAT TO DO WITH A FLAG<\/p>\n
\n
\n
Flag raised<\/p>\n
\n- Unusual, not necessarily wrong<\/li>\n<\/ul>\n<\/div>\n
\n
Check documents<\/p>\n
\n- Order, receipt, bill, quietly<\/li>\n<\/ul>\n<\/div>\n
\n
Escalate or clear<\/p>\n
\n- Defined route, decided in advance<\/li>\n<\/ul>\n<\/div>\n
\n
Record either way<\/p>\n
\n- Including the ones that were nothing<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n
What to set up<\/h2>\n
1. Separate duties<\/strong> as far as your headcount allows. Write down where you cannot, and accept that those points need more monitoring.<\/p>\n2. Enable duplicate bill detection.<\/strong> Simple and it recovers real money.<\/p>\n3. Flag supplier bank detail changes<\/strong> and verify every one by phone.<\/p>\n4. Enforce three-way matching<\/strong>, and train counting as a habit.<\/p>\n5. Require receipts on expense claims<\/strong> and read them automatically.<\/p>\n6. Review access quarterly<\/strong> \u2014 who has admin, who left, who changed role.<\/p>\n7. Add anomaly detection<\/strong> last, and tolerate the early false positives.<\/p>\nThe short version<\/h2>\n
Anomaly detection is a useful second line<\/strong>. It catches duplicates, unusual amounts, and \u2014 most valuably \u2014 changed supplier bank details.<\/p>\nThe first line is dull and it is what actually prevents loss: separated duties, verified bank changes, enforced approval limits, receipts counted, and access reviewed.<\/strong><\/p>\nA company with good controls and no anomaly detection is in much better shape than one with anomaly detection and one person who can create a supplier and pay them.<\/p>\n
\n
Not sure where your controls have gaps?<\/p>\n
Get in touch. We will look at who can do what in your Odoo \u2014 particularly who can both create a vendor and pay one.<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":"
Start with what actually happens Fraud in small and medium businesses is rarely dramatic. It is usually one of a small number of patterns: Fake or altered supplier invoices, paid because nobody checked them against a receipt Payment redirection \u2014 a real supplier impersonated, asking for new bank details Duplicate payments, sometimes accidental and sometimes […]<\/p>\n","protected":false},"author":3,"featured_media":9196,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[26],"tags":[],"class_list":["post-9195","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai"],"yoast_head":"\n
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