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Tax, Audit + Office of Finance

Welcome to the Alteryx Tax, Audit + Office of Finance User Group!

This user group is for anyone who works with money in their data. Maybe you're in the finance or accounting department at your organization, or maybe you use Alteryx to analyze tax and audit data. Perhaps you work at a bank or are a consultant in the financial sector. No matter who you work for or what your title is - if there's money in your data, this user group is for you.

Please join us in sharing experiences, best practices and knowledge.

User Group Leaders:

Foster King Rohit SomaniAlejandra LyonMarie Hibbert

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Bolide

Hello Shawn,

 

I've used it in a variety of ways to help clients with reviewing financials for the month end close and annual audits based on account rules (must be debit balance, variance over prior year, variance to budget, should not be zero, etc.).  I've also used it to review transaction level details, payroll data and to create data tables for a Excel based financials that are fed from pivot tables.  The sky is the limit.  Feel free to reach out if you have any specific questions or needs.

 

Alex

Asteroid

Hi @JenP ! 

 

I would like to connect with you but your private message setting is off so I couldn't send you a message. Whenever

you can, contact me at alyon@dcpmidstream.com. 

 

Best, 

 

Alejandra Lyon

Hi @JenP, sorry for the late reply...

 

Anyway, ... for the risk rank it is a simple 1 to 3 scale based on what we know is a stronger indicator (like paid more than 30 days after being terminated or before being hired) vs a complement indicator (not much on its own, but important when other things are at play, like being paid by physical checks that can be endorsed).

the score for the risk ranking each test may change (adjusted by hand) by what we learn during the review/follow-up. for example, based on the number of actual problems found by a test vs false positives; and in principle the scale can go as high as needed for tests that become actual smoking guns with fingerprints!

 

On the predictive test the idea was that the system would choose the factors of importance on its own (every time it ran), but from the early results we found that things like the higher the complexity of the expense report the higher chances of approval (likely rubber stamp). when I say complexity I mean things like: time separation between the first and last expense included, number of locations (one city vs several countries), number of line items, etc. 

 

Other factors that were interesting were the seniority of the submitter and the number of direct reports to the reviewer/aprover.