AML Audit Backend

Anti-Money Laundering Audit App Backend Template
Transaction Monitoring, SAR Logging, and Risk Flag Review

Q: Which AML audit controls matter most when operations span multiple sites?

An AML audit backend is a BaaS schema and API for transaction monitoring, SAR logs, and risk flag review: investigators, transactions, filings, and action status.

Q: How can AML audit teams reconcile daily operations with periodic compliance checks?

It includes Investigator (name, email, role), Transaction (transactionId, amount, currency, merchant, status), SARLog (caseId, transaction, filingStatus, submittedAt, notes), and RiskFlag (transaction, severity, ruleCode, reviewer, actionStatus), plus an ER diagram, API playground, and AI Agent prompt.

Q: Is it practical to export AML audit evidence for external reviewers in a structured way?

Back4app provides managed database, auth, real-time queries, and flexible schema so you can ship transaction monitoring, SAR logs, and risk flags without running your own backend.

Q: How do I run queries for transactions in Flutter?

Use the Transaction and RiskFlag classes to query and display the AML queue, leveraging the Back4app SDK.

Q: How do I manage AML audit access with Next.js server actions?

Use a server action to create a Parse Object for SARLog with a Transaction pointer and filingStatus. Optionally validate in Cloud Code.

Q: Can React Native cache AML records offline?

Yes. Enable Local Datastore and pin Transaction, SARLog, and RiskFlag results so investigators can browse saved case data without connectivity.

Q: How do I prevent unauthorized AML record access?

In Cloud Code beforeSave for RiskFlag and SARLog, enforce reviewer checks and reject updates if the investigator is not assigned.

Q: What is the best way to show AML queues on Android?

Query Transaction and RiskFlag classes to display suspicious activity queues and filing status, using the Back4app SDK for data management.

Q: How does the transaction monitoring flow work end-to-end?

Investigators log in, load Transaction rows, create a RiskFlag when a rule is triggered, and then write a SARLog entry if the review is escalated.

A production-ready AML audit backend on Back4app with transaction monitoring, SAR logs, and risk flags. Includes ER diagram, data dictionary, JSON schema, API playground, and an AI Agent prompt for rapid bootstrap.

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AML Audit Key Takeaways

This template gives you an AML backend with transaction monitoring, SAR logs, and risk flags so investigators and operations staff can review activity faster.

Transaction monitoring structure — Model Transaction rows with amount, currency, merchant, and status for day-to-day review.
SAR log tracking — Store SAR Log entries with filing status, case notes, and submittedAt timestamps for audit follow-up.
Risk flag review — Link Risk Flag records to suspicious patterns, severity, and reviewer actions.

Anti-Money Laundering Audit App Backend at a Glance

When AML audit teams operate across sites, consistent taxonomy prevents “same problem, five different names” in the audit trail. The cost shows up in callbacks and credits. Back4app keeps Investigator, Transaction, Log, and Flag timestamped and attributable — the baseline AML audit teams need when scrutiny arrives. The schema covers Investigator (name, email, role), Transaction (transactionId, amount, currency, status, merchant), SAR Log (caseId, filingStatus, submittedAt, notes), and Risk Flag (transaction, severity, ruleCode, reviewer) with auth and audit-friendly workflows built in. Connect your preferred frontend and ship faster.

Best for:

AML monitoring appsSAR filing dashboardsRisk flag review toolsTransaction surveillance systemsCompliance operations teamsInvestigative case tracking

How this AML Audit backend is organized

AML audit is not only about speed; it is about defensibility when someone asks “show me how you knew that was true.”

Review Investigator, Transaction, and Log first, then open a stack card to see SDK-specific notes and integration patterns.

Core AML Audit Features

Every technology card in this hub uses the same AML backend schema with Investigator, Transaction, SAR Log, and Risk Flag.

Investigator access and assignments

Investigator stores name, email, and role for each reviewer.

Transaction monitoring queue

Transaction captures transactionId, amount, currency, merchant, and status.

SAR log records

SAR Log tracks caseId, filingStatus, submittedAt, and notes.

Risk flag tracking

Risk Flag links a transaction, severity, ruleCode, and reviewer.

Why Build Your AML Backend with Back4app?

Back4app gives you transaction, SAR, and risk flag primitives so your team can focus on review quality instead of managing servers.

•Transaction and SAR log modeling: Transaction fields such as transactionId, amount, and status pair naturally with SAR Log caseId and filingStatus.
•Risk flag governance: Risk Flag records keep ruleCode, severity, and reviewer together for traceable review decisions.
•Realtime + API flexibility: Use Live Queries for new Transaction alerts while keeping REST and GraphQL available for every client.

Build AML review tools quickly with one backend contract across web, mobile, and analyst workstations.

Core AML Benefits

A backend that helps AML teams move faster without losing the trail on transaction review.

Fast AML launch

Start from a complete Investigator, Transaction, SAR Log, and Risk Flag schema rather than designing an audit backend from zero.

Review traceability

Keep ruleCode, filingStatus, and reviewer data attached to each case path for follow-up.

Clear access control flow

Manage Investigator access to Transaction queues and SAR logs with ACL and CLP rules.

Scalable alert model

Use the Risk Flag class to track high-risk events without reworking the data model every time a rule changes.

Transaction and filing history

Store Transaction rows and SAR Log entries together so analysts can compare alerts against filing decisions.

AI bootstrap workflow

Generate backend scaffolding and AML integration guidance fast with one structured prompt.

Ready to launch your AML audit app?

Let the Back4app AI Agent scaffold your AML backend and generate transaction monitoring, SAR logs, and risk flags from one prompt.

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Technical Stack

Everything included in this AML audit backend template.

Frontend

13+ technologies

Backend

Back4app

Database

MongoDB

Auth

Built-in auth + sessions

API

REST and GraphQL

Realtime

Live Queries

AML ER Diagram

Entity relationship model for the AML audit backend schema.

ER Diagram

View diagram source

Mermaid

erDiagram
    AnalystUser ||--o{ MonitoringCase : "assignedTo"
    MonitoringCase ||--o{ TransactionEvent : "case"
    MonitoringCase ||--o{ SarLog : "case"
    MonitoringCase ||--o{ RiskFlag : "case"
    MonitoringCase ||--o{ ReviewNote : "case"
    AnalystUser ||--o{ SarLog : "submittedBy"
    AnalystUser ||--o{ RiskFlag : "reviewedBy"
    AnalystUser ||--o{ ReviewNote : "author"
    TransactionEvent ||--o{ RiskFlag : "triggeredBy"

    AnalystUser {
        String objectId PK
        String username
        String email
        String password
        String role
        String team
        Date createdAt
        Date updatedAt
    }

    MonitoringCase {
        String objectId PK
        String caseNumber
        String customerName
        String status
        String assignedToId FK
        Date openedAt
        Date closedAt
        Date createdAt
        Date updatedAt
    }

    TransactionEvent {
        String objectId PK
        String transactionId
        String caseId FK
        Number amount
        String currency
        String channel
        String counterparty
        Date transactionAt
        String monitoringStatus
        Date createdAt
        Date updatedAt
    }

    SarLog {
        String objectId PK
        String sarNumber
        String caseId FK
        String submittedById FK
        String filingStatus
        Date submittedAt
        String regulatorRef
        Date createdAt
        Date updatedAt
    }

    RiskFlag {
        String objectId PK
        String flagType
        String severity
        String caseId FK
        String triggeredById FK
        String status
        String reason
        String reviewedById FK
        Date reviewedAt
        Date createdAt
        Date updatedAt
    }

    ReviewNote {
        String objectId PK
        String caseId FK
        String authorId FK
        String noteType
        String body
        Date createdAt
        Date updatedAt
    }

AML Integration Flow

Typical runtime flow for login, transaction review, SAR logging, and risk flag updates.

ER Diagram

View diagram source

Mermaid

sequenceDiagram
  participant Analyst as AnalystUser
  participant AMLApp as Anti-Money Laundering App
  participant Back4app as Back4app Cloud

  Analyst->>AMLApp: Sign in
  AMLApp->>Back4app: POST /login
  Back4app-->>AMLApp: Session token

  Analyst->>AMLApp: Open monitoring queue
  AMLApp->>Back4app: GET /classes/MonitoringCase?include=assignedTo&order=-updatedAt
  Back4app-->>AMLApp: Cases and assigned analysts

  Analyst->>AMLApp: Review transaction events
  AMLApp->>Back4app: GET /classes/TransactionEvent?include=case
  Back4app-->>AMLApp: TransactionEvent rows

  Analyst->>AMLApp: Create a risk flag or SAR log
  AMLApp->>Back4app: POST /classes/RiskFlag or /classes/SarLog
  Back4app-->>AMLApp: Saved risk flag or SAR log

  AMLApp->>Back4app: Subscribe to case updates
  Back4app-->>AMLApp: LiveQuery updates for MonitoringCase and RiskFlag

AML Data Dictionary

Full field-level reference for every class in the AML audit schema.

Field	Type	Description	Required
objectId	String	Auto-generated unique identifier	Auto
username	String	Login name for the analyst or coordinator
email	String	Work email address
password	String	Hashed password (write-only)
role	String	User role such as investigator, manager, or operator
team	String	Assigned compliance team or operations unit	—
createdAt	Date	Auto-generated creation timestamp	Auto
updatedAt	Date	Auto-generated last-update timestamp	Auto

8 fields in AnalystUser

Security and Permissions for AML

How ACL and CLP strategy secures investigators, transactions, SAR logs, and risk flags.

Investigator account controls

Only the investigator can update their profile; role checks determine who can view or edit review assignments.

Transaction and SAR integrity

Only approved reviewers can create or modify Transaction notes and SAR Log records; Cloud Code can validate status changes.

Scoped review access

Restrict Transaction and Risk Flag reads to the assigned compliance group, and expose SAR Log filing details only to authorized staff.

AML Schema (JSON)

Raw JSON schema definition ready to copy into Back4app or use as implementation reference.

JSON

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{
  "classes": [
    {
      "className": "AnalystUser",
      "fields": {
        "objectId": {
          "type": "String",
          "required": false
        },
        "username": {
          "type": "String",
          "required": true
        },
        "email": {
          "type": "String",
          "required": true
        },
        "password": {
          "type": "String",
          "required": true
        },
        "role": {
          "type": "String",
          "required": true
        },
        "team": {
          "type": "String",
          "required": false
        },
        "createdAt": {
          "type": "Date",
          "required": false
        },
        "updatedAt": {
          "type": "Date",
          "required": false
        }
      }
    },
    {
      "className": "MonitoringCase",
      "fields": {
        "objectId": {
          "type": "String",
          "required": false
        },
        "caseNumber": {
          "type": "String",
          "required": true
        },
        "customerName": {
          "type": "String",
          "required": true
        },
        "status": {
          "type": "String",
          "required": true
        },
        "assignedTo": {
          "type": "Pointer",
          "required": true,
          "targetClass": "AnalystUser"
        },
        "openedAt": {
          "type": "Date",
          "required": true
        },
        "closedAt": {
          "type": "Date",
          "required": false
        },
        "createdAt": {
          "type": "Date",
          "required": false
        },
        "updatedAt": {
          "type": "Date",
          "required": false
        }
      }
    },
    {
      "className": "TransactionEvent",
      "fields": {
        "objectId": {
          "type": "String",
          "required": false
        },
        "transactionId": {
          "type": "String",
          "required": true
        },
        "case": {
          "type": "Pointer",
          "required": true,
          "targetClass": "MonitoringCase"
        },
        "amount": {
          "type": "Number",
          "required": true
        },
        "currency": {
          "type": "String",
          "required": true
        },
        "channel": {
          "type": "String",
          "required": true
        },
        "counterparty": {
          "type": "String",
          "required": true
        },
        "transactionAt": {
          "type": "Date",
          "required": true
        },
        "monitoringStatus": {
          "type": "String",
          "required": true
        },
        "createdAt": {
          "type": "Date",
          "required": false
        },
        "updatedAt": {
          "type": "Date",
          "required": false
        }
      }
    },
    {
      "className": "SarLog",
      "fields": {
        "objectId": {
          "type": "String",
          "required": false
        },
        "sarNumber": {
          "type": "String",
          "required": true
        },
        "case": {
          "type": "Pointer",
          "required": true,
          "targetClass": "MonitoringCase"
        },
        "submittedBy": {
          "type": "Pointer",
          "required": true,
          "targetClass": "AnalystUser"
        },
        "filingStatus": {
          "type": "String",
          "required": true
        },
        "submittedAt": {
          "type": "Date",
          "required": false
        },
        "regulatorRef": {
          "type": "String",
          "required": false
        },
        "createdAt": {
          "type": "Date",
          "required": false
        },
        "updatedAt": {
          "type": "Date",
          "required": false
        }
      }
    },
    {
      "className": "RiskFlag",
      "fields": {
        "objectId": {
          "type": "String",
          "required": false
        },
        "flagType": {
          "type": "String",
          "required": true
        },
        "severity": {
          "type": "String",
          "required": true
        },
        "case": {
          "type": "Pointer",
          "required": true,
          "targetClass": "MonitoringCase"
        },
        "triggeredBy": {
          "type": "Pointer",
          "required": false,
          "targetClass": "TransactionEvent"
        },
        "status": {
          "type": "String",
          "required": true
        },
        "reason": {
          "type": "String",
          "required": true
        },
        "reviewedBy": {
          "type": "Pointer",
          "required": false,
          "targetClass": "AnalystUser"
        },
        "reviewedAt": {
          "type": "Date",
          "required": false
        },
        "createdAt": {
          "type": "Date",
          "required": false
        },
        "updatedAt": {
          "type": "Date",
          "required": false
        }
      }
    },
    {
      "className": "ReviewNote",
      "fields": {
        "objectId": {
          "type": "String",
          "required": false
        },
        "case": {
          "type": "Pointer",
          "required": true,
          "targetClass": "MonitoringCase"
        },
        "author": {
          "type": "Pointer",
          "required": true,
          "targetClass": "AnalystUser"
        },
        "noteType": {
          "type": "String",
          "required": true
        },
        "body": {
          "type": "String",
          "required": true
        },
        "createdAt": {
          "type": "Date",
          "required": false
        },
        "updatedAt": {
          "type": "Date",
          "required": false
        }
      }
    }
  ]
}

Build AML with AI Agent

Use the Back4app AI Agent to generate a real AML audit app from this template, including frontend, backend, auth, and transaction, SAR log, and risk flag flows.

Back4app AI Agent

Ready to build

Create an anti-money laundering audit app backend on Back4app with this exact schema and behavior.

Schema:
1. Investigator (use Back4app built-in auth for login and role gating): name (String, required), email (String, required), role (String, required); objectId, createdAt, updatedAt (system).
2. Transaction: transactionId (String, required), amount (Number, required), currency (String, required), merchant (String, required), status (String, required), notes (String); objectId, createdAt, updatedAt (system).
3. SARLog: caseId (String, required), transaction (Pointer to Transaction, required), filingStatus (String, required), submittedAt (Date), notes (String); objectId, createdAt, updatedAt (system).
4. RiskFlag: transaction (Pointer to Transaction, required), severity (String, required), ruleCode (String, required), reviewer (Pointer to Investigator), actionStatus (String, required), comment (String); objectId, createdAt, updatedAt (system).

Security:
- Only the investigator can update their profile. Restrict Transaction, SARLog, and RiskFlag edits to authorized reviewers.
- Use Cloud Code to validate filing status transitions and rule-based flag updates.

Auth:
- Sign-up, login, logout.

Behavior:
- List transactions, create SAR logs, update risk flags, and assign review ownership.

Deliver:
- Back4app app with schema, ACLs, CLPs; frontend for investigators, transaction queues, SAR logs, and risk flag review.

Press the button below to open the Agent with this template prompt pre-filled.

This is the base prompt without a technology suffix. You can adapt the generated frontend stack afterward.

Deploy in minutes50 free prompts / monthNo credit card required

AML API Playground

Try REST and GraphQL endpoints against the AML audit schema. Responses use mock data and do not require a Back4app account.

Loading playground…

Uses the same schema as this template.

Choose Your Technology for AML

Expand each card to see how to integrate Investigator, Transaction, and Log with your chosen stack.

What You Get with Every Technology

Every stack uses the same AML backend schema and API contracts.

Unified AML data structure

Easily manage investigators, transactions, SAR logs, and risk flags with a consistent schema.

Transaction monitoring for AML

Review suspicious payments and queue them for analyst action.

SAR log tracking for AML

Keep filing history and case notes tied to a specific transaction review.

Customizable reviewer roles

Define access levels and approvals tailored to compliance operations.

REST/GraphQL APIs for AML

Integrate with dashboards, mobile tools, and back-office review systems.

Extensible compliance architecture

Add new risk rules or case fields as your monitoring program evolves.

AML Framework Comparison

Compare setup speed, SDK style, and AI support across all supported technologies.

Framework	Setup Time	AML Benefit	SDK Type	AI Support
Flutter	About 5 min	Single codebase for AML review on mobile and web.	Typed SDK	Full
React	Under 5 minutes	Fast web dashboard for AML transaction monitoring.	Typed SDK	Full
React Native	~3–7 min	Cross-platform mobile app for AML review queues.	Typed SDK	Full
Next.js	Rapid (5 min) setup	Server-rendered web app for AML operations.	Typed SDK	Full
JavaScript	~3–5 min	Lightweight web integration for AML monitoring.	Typed SDK	Full
Android	About 5 min	Native Android app for AML investigators.	Typed SDK	Full
iOS	Under 5 minutes	Native iOS app for AML investigators.	Typed SDK	Full
Vue	~3–7 min	Reactive web UI for AML operations.	Typed SDK	Full
Angular	Rapid (5 min) setup	Enterprise web app for AML compliance teams.	Typed SDK	Full
GraphQL	Under 2 min	Flexible GraphQL API for AML case review.	GraphQL API	Full
REST API	Quick (2 min) setup	REST API integration for AML monitoring.	REST API	Full
PHP	~3 min	Server-side PHP backend for AML workflows.	REST API	Full
.NET	~3–7 min	.NET backend for AML operations.	Typed SDK	Full

Setup time reflects expected duration from project bootstrap to first Transaction or SARLog query using this template schema.

Frequently Asked Questions

Common questions about building an AML audit backend with this template.

Which AML audit controls matter most when operations span multiple sites?

How can AML audit teams reconcile daily operations with periodic compliance checks?

Is it practical to export AML audit evidence for external reviewers in a structured way?

How do I run queries for transactions in Flutter?

How do I manage AML audit access with Next.js server actions?

Can React Native cache AML records offline?

How do I prevent unauthorized AML record access?

What is the best way to show AML queues on Android?

How does the transaction monitoring flow work end-to-end?

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Anti-Money Laundering Audit App Backend TemplateTransaction Monitoring, SAR Logging, and Risk Flag Review