Audit and Finance Procedures Alwin by DataSnipper Can Run End-to-End

How Alwin works

Alwin is an agentic automation platform for audit and finance. Agents plan, collect evidence, verify, and report. In plan mode, Alwin reads your documents and workpaper template, then proposes an approach. The biggest takeaway you should know about Alwin is that nothing runs until you approve it. You remain in the driver seat. There is no black box AI. Every output is fully transparent: you can trace each result back to its source and see exactly which calculations and actions were performed to get there.

When a regulator or an audit oversight bodies asks what the agent did, what its thought process was, and what the reasoning was behind it, you have trails for everything.

In Alwin, every task moves through five stages:

1. Draft
2. Running
3. Needs input
4. Needs review
5. Done
   

Snipped cells link back to the source document. Reviewers leave notes in the workbook and send them back to the agent.

How your team can benefit before busy season

Firms can't hire their way through busy season. Clients expect more assurance for similar fees, so margin depends on how the work gets done. And whatever changes, you still have to show a partner or regulator what was done, by whom (human or agent), and on what evidence.

The Example procedures

Revenue substantive testing at scale

The problem: Revenue testing means matching invoices, purchase orders, and shipping documents across hundreds of files. As a significant, in-scope account with a presumed fraud risk, revenue often calls for a sample of 60 or more transactions, and each one has to be vouched to its supporting documents for occurrence, accuracy and cut-off. Every match and every exception then has to be evidenced in the work papers.

What Alwin does: In the webinar, we uploaded 222 files, from bank statements and contracts to a revenue ledger and the work paper templates. Alwin read through the template instructions to understand what the test required, then proposed a step-by-step plan. After reviewing it, we asked Alwin to also flag missing documents or approvals, and it updated the plan to include them. Once we approved it, Alwin ran in the background, working through every sample and matching each invoice, purchase order and shipping document, while we moved on to other work. The completed work paper had exceptions, each with a clear reason. Every result linked back to the exact spot in the source document, and every calculation Alwin performed was visible. Alwin also produced a summary of the work, the matches and the exceptions, so the reviewer could see the outcome at a glance and then drill into any sample directly in Excel.

What the reviewer checks: The plan before it runs, the reason behind each exception, and the quantity checks. Every snip opens the supporting document, and the formulas are auto-populated, so you can follow the work.

Analytical review

The problem: Analytical procedures start with documents you need from the client. Trial balances, prior-year financials, management accounts and budgets all have to be requested, received and pulled into a usable format before any analysis begins. Only then can the auditor build expectations, compare them to actuals and flag fluctuations above the threshold. Each significant variance then needs an explanation from management, corroborated with evidence and documented in the work papers.

What Alwin does: In the webinar, the documents came from a client request in Uplink, DataSnipper’s PBC portal. Once the client uploads their files and you review and approve them, you can pull them straight into a new Alwin task without leaving the platform. We pulled in nine documents and ran the task in plan mode. Plan mode lets you see how Alwin intends to approach the work before it starts, so you can steer it toward the right direction, whether that’s focusing on specific accounts, using a particular threshold or following your firm’s methodology. If your team already has an agent set up for the procedure, you can select it and add any engagement-specific instructions on top. From there, Alwin works through the documents, builds the analysis in the format you need, whether that’s ratio analysis, a variance analysis against prior year or budget, or trend analysis across periods, and flags fluctuations that need explanation. Every figure traces back to its source, and every calculation is visible, so you can review the analysis, investigate the variances and conclude on the procedure.

What the reviewer checks: Review starts before any work is done. The reviewer first checks the proposed plan to confirm Alwin understood the procedure and is taking the right approach, and adjusts the direction if needed. Once the task is complete, the finished work paper moves to Needs review. From there, the reviewer can go through the analysis step by step: checking the formulas and calculations Alwin used, tracing each figure back to its source document and reading the reasoning behind each conclusion. Nothing is final until the reviewer is satisfied, so the auditor keeps professional judgment and sign-off.

Contract and vendor compliance testing

The problem: Exceptions often lead to follow-up. The client sends more support, and you revisit the test. In practice, that means chasing the client for missing invoices, approvals or contracts, waiting for them to arrive, then going back into a work paper you thought was nearly done. Each new document has to be matched to the right exception, the original testing re-performed and the conclusion updated and re-documented. With several exceptions open across several procedures, this back-and-forth can drag on for weeks and become one of the most time-consuming parts of closing out the audit.

 What Alwin does: In the webinar, the vendor compliance test returned two exceptions, with a summary of what was tested and why each one failed. When the client sent additional documents, we attached them to the task and left a review note asking Alwin to revisit the exceptions. Alwin re-tested those items against the new evidence and updated its conclusions, keeping the original exception, the note and the revised result linked. Notes can go one at a time or in a batch once you’ve finished reviewing.

What the reviewer checks: Whether the revised conclusions hold up against the newly attached documents. The reviewer traces each updated result back to its new evidence, follows Alwin’s reasoning for clearing or keeping each exception, and flags anything still unresolved. It’s the same review you’d give a junior colleague’s follow-up work.

Beyond the procedures: how Alwin fits your audit

Beyond the individual procedures, the webinar showed the capabilities that make Alwin practical for real engagements. Because agents can do the heavy lifting, audit teams can expand their testing scope, and Alwin handles the larger volume of documents and the more complex procedures that come with it, as seen in the 222-file revenue test. Each client has its own workspace, so teams can switch between engagements easily and keep track of work across clients. Tasks run in the background, so you don’t need to stay at your laptop: assign a task to Alwin at the end of the day and come back to finished work waiting in Needs review. Plan mode lets you check and steer the approach before any work begins, and reusable agents keep procedures consistent across teams. When the work comes back, the review experience keeps the auditor in control, with visible formulas, documented reasoning and a full audit trail linking every result back to its source.

What you get: Traceability to the source

In a world where defensibility is paramount, being able to trust the outputs you receive and see the work that is being done is a non-negotiable. Every conclusion links to its evidence. The audit trail records each agent and human action with time stamps, including our agent's reasoning.

There’s a general misconception that all AI is unreliable. Our product team at DataSnipper consists of former auditors and knows that each step must be able to trace back to its source. That has been our ethos since day 1 and hasn’t changed over the years.

Our CEO also takes a firm stance on the value of human-in-the-loop. “We can’t move forward without humans verifying AI outputs. This principle is core to every product we build at DataSnipper.”

Calculations and some procedures run deterministically, field-level guardrails apply to extracted data, and the source link lets you inspect everything. My colleague Eric Moakley, Sr. Manager, Product Management, puts it this way: “Any technology that uses an LLM in any part of it is always subject to this risk. That’s why we always connect evidence back to the source material, so it can all be inspected.”

You approve the plan, answer questions when the agent needs input, and mark the task done. We’re not replacing people with AI. We’re using AI to make them unstoppable.

See it in action