6 ways to make a financial audit less painful

What's in this for you?

Picture this: A group of analysts from an external firm is hold-up in one of your board rooms. They’ll be there for the next three weeks. They’re running a standard financial audit on your numbers.

Chances are both parties want this financial equivalent of a colonoscopy over as quickly and with as little discomfort as possible. So, no, you’re not interested in helping them visualize your data. No, you aren’t looking for them to give you faster insights. No, they don’t need to help you make “better business decisions.”

Ultimately what you’re looking to do is give them exactly what they need, without compromising any internal governance controls, and make their process as smooth as possible so that they don’t keep bugging your people for more information. So to that end, here are six features your analytics infrastructure should include to help get you through the next audit.

1. Guest Data Marts

Guest Accounts can be “view only”, and are becoming more common with reporting software. What many tools are lacking, however, is the ability to stack row-level and column-level security roles in a way that creates a “custom” data mart in just a few seconds. Guest accounts should be tied to an email address that’s external to the organization (ie. those of the auditors) and should expire after a set period of time (the length of the audit). Expiration automatically de-activates the account.

The nice thing about the custom data marts is that they can be saved and re-used again for future audits.

2. Single Chain of Custody

Data goes through a number of transformations before a final decision is made. It can be reshaped through pivots, unions and joins. It can be cleaned by removing spelling mistakes, removing duplication, or consolidating similar values. And finally data will go through some Business Rules – If/Then/Else rules or a Custom Calculation.

In many ways data arriving at the boardroom is a lot like evidence arriving at the courtroom. There needs to be a clearly traceable chain of custody.

An auditor will need to “trace” the data back through that chain of custody to see exactly what rules touched the data and how it was changed. Sometimes they go all the way back to the original source system.

Because data can change so many hands when it leaves the source system (like an ERP) and arrives in a report (that the auditor sees), traceability becomes extremely difficult when you build your analytics infrastructure from separate, off-the-shelf components. This means that an auditor will have to bug your data team to help them trace the data from start to finish.

Having self-directed data traceability is one of the promises of the Minimalist Approach to analytics.

3. The Data Time Machine

We’ve all heard of the “Time Machine” on Macbooks. It’s when your computer takes a backup of itself at a point in time that you can “rollback” to. Many people think of backing up your data in case of disaster recovery. But disaster recovery isn’t the application we’re talking about.

While your Analytics Infrastructure should back up data in case of disaster recovery, what we’re referring to here is Non-volatility, one of the hallmarks of a data warehouse. It’s the ability to look at the business “as of” a certain date in time, even if there’s no disaster to recover from.

Data is always in flux. Systems get swapped out. Schemas change unexpectedly. APIs can break. New rules will be added to replace old ones. Your data infrastructure is a living, breathing organism, which can make the audit process that much more complicated. If your infrastructure is set up to enable this “time machine” ability out-of-box, you can set a fixed point in time that the auditors should view the business, a sort of “as-of” date, while the rest of the company can continue with their operations.

4. Capture Institutional Knowledge

Data is very good at answering five questions: Who? What? When? Where? and How Much? But it’s notoriously bad at answering Why. For this, you need human intervention.

This is the human part of the insight, the actual analysis portion. These are conversations, emails, decision that are made in meetings that need to be captured somewhere, and the right analytics infrastructure will help you capture that in the form of discussion comments or articles. Depending on what your auditors need, this can be hugely helpful in re-tracing the thought process that went into some decision or another.

5. Capture and Answer Auditor Questions

Similar to capturing Institutional Knowledge, the same features can be used to collaborate with your auditors. While you can certainly do the same over email, doing so directly in the discussions or commentary features of your analytics infrastructure allow you to keep a record for future reference.

6. Embedded Documents

Last but not least is the ability tie in “enriched” data. This is unstructured data that can’t go into a table of row and columns. Auditors will frequently need to go back the original source system to see the actual transaction. If that transaction was a receipt, an invoice, or some other kind of document, that can be attached to the physical row in the analytics infrastructure (data warehouse), and made easily viewable in the pivot table. The beauty is that the visibility of these invoices or other documents is constrained by the Guest Data Mart that we talked about above. So you can give your auditors both the high level financial figures, but also the ability to drill down and view the physical receipt, without ever bugging you to print those off. And everything will be governed by the access you give them.

Conclusion

The problem with the above features is that they generally aren’t offered out-of-box, or at least when they are, they aren’t crafted to work together for this purpose. What this means is your data team is tasked, yet again, with building features internally to fit a business use case. That’s where a Minimalist Approach to analytics comes in. Under this approach, a single, all-in-one system provides features that are crafted to work together to solve exactly these problems. Achieving the vision of this Minimalist Approach is exactly why we built TypeSift.

Get our help

If you’re worried about an upcoming audit disrupting your day-to-day back-office operations, and would like more information on how a Minimalist system like TypeSift can help mitigate that disruption, please contact us.

TypeSift is a Data Engineering & Design Minimalism Firm. Our expertise is decluttering information and solving problems in your data that are holding back your growthWe build software that corrals data and invokes ingenuity with the fewest moving parts.