Cada control. Cada transacción. Cada día.
Los controles probados una vez al año pueden fallar en silencio los otros once meses. CompliBear supervisa sus controles clave de forma continua, sobre el 100% de las transacciones, y envía cada excepción a su responsable con un valor y las pruebas, para que los problemas se corrijan en días y no se descubran al cierre del ejercicio.
Las pruebas periódicas dejan largos puntos ciegos
El muestreo no ve el patrón
Veinticinco partidas pueden superar la prueba mientras la vigésimo sexta, y las mil siguientes, fallan.
Sorpresas al cierre del ejercicio
Un control que falló en marzo se descubre en diciembre, cuando el dinero ya se ha ido.
Fatiga de alertas
Las reglas que lo señalan todo enseñan a las personas a ignorar las alertas que importan.
Las pruebas están dispersas
Workpapers, emails and spreadsheets. Nobody can trace a finding to its source.
Three frauds, 10,000 invoices, a sample of 25
Tres fraudes se esconden entre 10.000 facturas. Usted prueba 25 al azar. ¿Qué probabilidad hay de no encontrar ninguno?
Extraiga una muestra y vea qué encuentra.
(9.997 ÷ 10.000)²⁵ ≈ 0,993. Probar las 10.000, cada día, encuentra los tres.
From a policy clause to a daily test
- THE CLAUSE“Requirements shall not be split to avoid the approval of the competent authority.”
A line from a purchase manual.
- THE RULE, EXTRACTED BY AIFlag orders to the same vendor, for the same material, within a short window, that together exceed the approval limit while each stays below it.
The auditor reviews and approves the rule.
- THE TESTRuns every day, on every order
The window, the limit and the tolerance stay editable.
Private generative AI reads your documents inside your environment. 750+ ready-made tests are there from day one.
Where we look, and what warns early
| Ámbito | What we test | Early-warning signal |
|---|---|---|
| Procurement and tendering | Split orders, single or limited tenders, bid patterns, repeat orders beyond validity | Spend concentrating on a few vendors |
| Vendor master and payments | Duplicates, bank changes, dormant vendors reactivated, payments without receipt | Vendor risk score rising before payment |
| Contracts and capex projects | Billing against the awarded value, extra items, advances not recovered, damages not levied | Contracts trending to overrun |
| Inventory and product | Stock variance against loss norms, write-offs, slow-moving stores and spares | Variance drifting towards the norm |
| Logistics and freight | Claims against distance, duplicate trips, short deliveries, rate overrides | Transporter outlier score |
| Dealers and distributors | Credit-limit breaches, discounts and incentives beyond the scheme, claims, commissions | Dealer health score falling |
| Revenue and receivables | Price applied against the price list, credit notes, rebates, ageing | Collection slippage forecast |
| Payroll and expenses | Ghost employees, duplicate claims, overtime and allowance anomalies | Unusual pay changes |
| Tax and regulatory | GST input credit against GSTR-2B, TDS, the MSME 45-day rule, e-invoice gaps | Due-date breach forecast |
| IT and SAP controls | SoD conflicts, sensitive transactions, direct table changes, privileged access | Control drift alerts |
Six techniques, one engine
| Technique | What it catches | Example |
|---|---|---|
| Rules and thresholds | Known policy breaches | A payment above the delegated limit |
| Statistical tests | Valores atípicos | Freight claims per kilometre far above peers |
| Machine learning | Unknown patterns | A dealer that behaves unlike similar dealers |
| Link analysis | Hidden relationships | An employee and a vendor sharing a bank account or address |
| Text analytics | What narrations reveal | Vague narrations on large manual entries |
| Predictive models | Exceptions likely to occur | Invoices on course to breach the MSME 45-day limit |
Signals that come before the loss
| Leading signal | What it predicts | Action before the loss |
|---|---|---|
| MSME invoices nearing 45 days | Interest and a disallowed tax deduction | Prioritise them in the next payment run |
| Contract billing nearing the awarded value | A cost overrun | Review variations before approval |
| Dealer credit use rising while offtake falls | A credit breach or bad debt | Review the credit limit |
| Stock variance drifting towards the loss norm | Product loss | Physical verification |
| Vendor risk score climbing | Payment to a risky vendor | Hold before the payment run |
| Manual overrides rising | A control breakdown | A targeted review |
Every vendor, dealer, contract and user, scored daily
| Entidad | Tipo | Puntuación de riesgo | Trend | Top reason |
|---|---|---|---|---|
| Vendor V-20931 | Proveedor | 92HIGH | Rising | Bank details changed; tax registration inactive |
| Dealer D-4471 | Dealer | 86HIGH | Rising | Credit use up, offtake down for three months |
| Depot DP-07 | Location | 78MED | Rising | Stock variance close to the loss norm |
| Contract C-1187 | Contrato | 74MED | Stable | Billing near the awarded value |
| ERP user U-0332 | User | 69MED | Nuevo | Created and paid the same vendor |
Illustrative scores. Each score runs from 0 to 100 and shows the reasons and source transactions behind it.
Lo que muestra el vídeo explicativo.
- Controls tested once a year can fail quietly for the other eleven months.
- Test a random 25 of 10,000 invoices and there is a 99.3% chance you miss all three frauds. Test all 10,000, every day, and you find all three.
- Private generative AI, inside your environment, turns a policy clause into a daily test. The auditor approves the rule.
- Each exception reaches its owner with a value and the evidence, so problems are fixed in days, not found at year end.
Not data ingestion. Not reporting. An early-warning system for internal audit.
07Cómo funciona
- 01Conectar
Solo lectura sobre su ERP
- 02Supervisar
Cada control, cada día
- 03Alertar
Excepciones ordenadas por impacto en el negocio
- 04Resolver
Los responsables deciden en OATS, con un registro con fecha y hora
- 05Explicar
Root Cause Analyzer muestra el porqué y el coste
08Pruebas
Un fabricante cotizado utiliza CompliBear en 6 plantas: 4.200 excepciones encontradas en el primer trimestre, por valor de USD 1.1 Mn, y 2.600 horas de auditoría ahorradas al año. · Más de 1.690 horas de pruebas manuales eliminadas cada año en las implantaciones
Empiece con un LaunchPad de dos semanas
Nos conectamos a sus datos, activamos cinco análisis y dos modelos de aprendizaje automático elegidos con usted, y le acompañamos durante dos semanas de soporte intensivo. Verá excepciones reales, valoradas, sobre sus propios datos.
Dos semanas. Sus datos, en solo lectura. Excepciones reales, valoradas.
10Preguntas frecuentes
¿En qué se diferencia del módulo GRC de nuestro ERP?
Las herramientas GRC gestionan la documentación de controles y las reglas de acceso. CompliBear prueba lo que realmente ocurrió en las transacciones y valora cada excepción. Funciona junto a su herramienta GRC.
¿Quién es responsable de los controles?
Usted. Configuramos los análisis según su marco de control; los responsables de sus controles reciben las excepciones y toman las decisiones.
¿Qué opinarán nuestros auditores externos?
Unas pruebas continuas con un registro de auditoría completo suelen facilitar su trabajo. Podemos explicarles el método.
¿Con qué rapidez podemos añadir controles?
Los nuevos análisis salen de la biblioteca de más de 750. Audit Flex añade 5 por trimestre y Audit Pro, 25. Consulte Precios y licencias.
How is this different from the audit analytics we already run?
Most analytics report what has already happened. Here the tests come from your own policies and run on every transaction, every day, and leading signals warn the owner before the loss. The observation is drafted for you.
¿Salen nuestros datos de nuestro entorno?
No. It runs on premises or in your chosen cloud, with read-only access. The generative AI that reads your policies is private and runs inside your environment.
¿Qué encontraría si lo probara todo?
Vea excepciones reales sobre sus propios datos en dos semanas.