# Ledger Reconstruction for Investigations for Accounts Receivable Managers with Billtrust

> AI ingests bank feeds, statements, and HighRadius data, rebuilds a clean transaction timeline, and flags suspicious patterns — investigators start at analysis, not data entry. Purpose-built for teams running Billtrust — uses the native API or agent integration so nothing leaves the system of record.

- **Tool:** [Billtrust](https://calish.com/workflows/tool/billtrust/)
- **Role:** [Accounts Receivable Manager](https://calish.com/workflows/for/accounts-receivable-manager/)
- **Specialty:** AR Collections
- **Category:** Data Entry & Processing
- **Canonical URL:** https://calish.com/workflows/with/ledger-reconstruction-for-investigations-for-accounts-receivable-manager-with-billtrust/

## The Problem

AR Collections forensic engagements start with incomplete books, missing backup, and thousands of transactions to reclassify by hand before any analysis can run.

## What We Build in Billtrust

AI ingests bank feeds, statements, and HighRadius data, rebuilds a clean transaction timeline, and flags suspicious patterns — investigators start at analysis, not data entry. Purpose-built for teams running Billtrust — uses the native API or agent integration so nothing leaves the system of record.

## Billtrust Integration Approach

1. **Audit your Billtrust configuration.** We map the specific Billtrust objects, custom fields, and workflows the automation needs to touch for your ar collections practice.
2. **Build on the Billtrust API or agent.** Integration happens inside Billtrust — no data leaves the system, no parallel tool for your team to learn, no license changes.
3. **Human-in-the-loop handoff.** Every automation routes exceptions back to a human in Billtrust with full context — AI handles the 80%, your team owns the judgment calls.

## About This Workflow

- [Ledger Reconstruction for Investigations for Accounts Receivable Managers](https://calish.com/workflows/ledger-reconstruction-for-investigations-for-accounts-receivable-manager/)
- AI ingests bank feeds, statements, and HighRadius data, rebuilds a clean transaction timeline, and flags suspicious patterns — investigators start at analysis, not data entry.

## Other Billtrust Automations

- [AR Collections & Dunning for Accounts Receivable Managers](https://calish.com/workflows/with/ar-collections-and-dunning-for-accounts-receivable-manager-with-billtrust/)
- [1099 & Contractor Reporting for Accounts Receivable Managers](https://calish.com/workflows/with/1099-and-contractor-reporting-for-accounts-receivable-manager-with-billtrust/)
- [Transaction Anomaly & Fraud Flagging for Accounts Receivable Managers](https://calish.com/workflows/with/transaction-anomaly-and-fraud-flagging-for-accounts-receivable-manager-with-billtrust/)
- [Management Reporting Package for Accounts Receivable Managers](https://calish.com/workflows/with/management-reporting-package-for-accounts-receivable-manager-with-billtrust/)
- [Budget vs. Actuals Review for Accounts Receivable Managers](https://calish.com/workflows/with/budget-vs-actuals-review-for-accounts-receivable-manager-with-billtrust/)
- [Payroll Variance & Exception Review for Accounts Receivable Managers](https://calish.com/workflows/with/payroll-variance-and-exception-review-for-accounts-receivable-manager-with-billtrust/)
- [Tax Notice & Agency Correspondence for Accounts Receivable Managers](https://calish.com/workflows/with/tax-notice-and-agency-correspondence-for-accounts-receivable-manager-with-billtrust/)

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