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Automation guide

How to Automate Financial Reconciliation with LangChain

Match transactions across bank statements, invoices, and accounting systems, and flag discrepancies for review.

The problem

Month-end reconciliation takes finance teams 2-5 days of manual matching. Every mismatch requires manual investigation.

The outcome

Reconciliation runs nightly. Month-end close takes hours, not days. Only genuine exceptions reach a human.

The tool

LangChain — Python/JS framework for building LLM applications.

How it works — step by step

  1. 1

    Bank feed, payment processor data, and accounting system all polled

  2. 2

    AI matches transactions using amount, date, and description

  3. 3

    Matched transactions confirmed automatically

  4. 4

    Unmatched items ranked by materiality and delivered for human review

About LangChain

Python/JS framework for building LLM applications. Best for developers building custom AI agents and RAG pipelines.

Strengths

  • Full control
  • RAG pipelines
  • Agent frameworks
  • Vector store integrations

Pricing

Open source. LangSmith observability from $39/month.

Documentation ↗

Related guides

Want this in production?

Altor builds financial reconciliation automation for US B2B companies.

We don't hand off code and disappear. We connect to your live systems, ship to production in 3 weeks, and stay until the system delivers measurable impact. Reconciliation runs nightly. Month-end close takes hours, not days. Only genuine exceptions reach a human.

Email us your workflow →