すべてのラインからより多くを生み出し、その過程での損失を減らす。
何千もの取引先、ディーラー、部品が、お金が漏れる何千もの場所を生み出します。ERPデータからそれらを見つけ、金額換算し、工場ごとに対応をお手伝いします。
マネーライン工場・事業部門ごとに、利益率を守り、在庫を解放し、支払いを止める。
01製造業でお金が漏れる場所
01節約 $
取引先への支払い
工場や事業体をまたいだ重複請求書、分割発注、銀行口座情報の変更。
02稼ぐ $
ディーラー・販売代理店向けスキーム
スキームのルール外で支払われた請求や値引き。
03稼ぐ $
在庫
動きの遅い在庫が現金を拘束する一方で、他のラインは不足しています。
04節約 $
運賃
半分空のトラックと、確認されていない運送会社の請求書。
詳しく見る →02Twelve use cases
Twelve use cases across commercial, plant, IT and people risk
COMMERCIAL
- Vendor risk scoringVendor master, change logs, payments
- Price creep against contractContracts, orders, invoices
- Rebates and credit notesRebate terms, billing, credit notes
PLANTS AND TECHNICAL
- Scrap rate and scrap priceMaterial movements, scrap sales
- Warranty claim anomaliesClaims, serial numbers, dealer data
- Capex and toolingProjects, tool payments, parts produced
IT AND SAP
- Same-user park and postDocument headers, workflow logs
- Firefighter sessionsSecurity audit log, postings
- SoD conflicts actually usedRoles joined to transactions
PEOPLE AND COMPLIANCE
- Duplicate expense receiptsReceipt images, image hashing
- Pay after exit; shared accountsPayroll, HR master
- Third-party screeningSupplier master, registries, sanctions
Each use case names the data it needs. Several of those sources sit outside the ERP.
03Two cases
What a sample misses, in the plant and in SAP
Plants and service: the evidence is a rate against peers
- Situation
- A multi-plant manufacturer; scrap sales and warranty claims reviewed by sampling.
- What a sample misses
- Every scrap note and claim is documented. The anomaly is the rate, not the record.
- Data and technique
- Analytics and machine-learning anomaly scores: scrap by plant, line and shift; scrap prices against an index; claims per service partner.
- Typical findings
- Scrap at twice the peer rate on one line’s night shift; one service partner with repeat serial numbers and claims after expiry.
- Control fix
- Scrap weighed and priced against an index; serial-number checks before any warranty payment.
SAP S/4HANA: access reviews show who could. Logs show who did.
- Situation
- An S/4HANA migration: roles remapped, and firefighter and migration users active through cut-over.
- What a sample misses
- The same user parks and posts, or edits a parked document after approval. Each posting looks authorised.
- Data and technique
- Process mining on parked-by and entered-by users, change documents and the security audit log, joined to the postings.
- Typical findings
- Same-user park and post on payments; postings by migration users after go-live; vendor bank changes made in firefighter sessions.
- Control fix
- Workflow blocks same-user park and post; migration IDs locked at go-live; firefighter sessions reviewed against postings.
Plant data is audit data. And test the migration window like a fraud window: it often is one.
Illustrative composite cases, read-only access. ACFE 2026: non-cash theft features in 41% of manufacturing cases.
04Plant tests
Inventory, scrap and warranty: 12 tests to run first
| Inventory and scrap | Warranty and service |
|---|---|
| Scrap rate outliers by plant, line and shift | Repeat serial numbers across claims |
| Scrap sold below market, or always to one buyer | Claims after the warranty has expired |
| Write-offs just before stock counts | Service partner claim rates against their peers |
| Negative stock and backdated movements | Parts claimed against labour hours claimed |
| Count adjustments posted by the same user | Claims clustered at month end |
| Slow-moving stock reclassified as scrap | The same technician or customer across many claims |
Thresholds are set for each entity and tuned on the results. Plant and quality data may sit outside the ERP.
05製造業で稼ぐ $ と節約 $
- 稼ぐ $
- 価格と利益率（Vittora CPX） 運転資本と在庫（Vittora SCM） 収益の漏れ（CompliBearの受注から入金までのテスト）
- 節約 $
- 不正と二重支払い（CompliBear） サードパーティリスク（CompliBear TPRM） 運賃と物流（ToS）
実績
ALTeX Hubは、ひとつの工場のためのコントロール監視のプロトタイプとして始まりました。ある自動車部品メーカーは、4つの倉庫で動きの遅い在庫を22%削減し、USD 2.8 Mnの運転資本を創出しました。
御社のお金はどこに隠れている？