Ep. 9: Danielle Supkis Cheek - Analytics for Fraud Prevention

FULL EPISODE TRANSCRIPT

Music: (00:00)

Adam: (00:05)

Hey everyone. Welcome back to Count Me In. Thanks for coming back and listening to some new accounting and finance perspectives. If you're enjoying these learnings and don't want to miss out on future episodes, please be sure to subscribe, download, rate, and review. Now this week our episode puts a slight twist on some of the recent conversations we've had as we begin to talk about using data analytics for fraud prevention. Mitch, not many people better to talk to about fraud and forensics and accounting than Danielle Supkis Cheek. What kind of insight did she have to offer?

Mitch: (00:35)

Well, as you said, many of our recent episodes have talked about the data transformation happening in accounting, but today's conversation is going to cover how to build a data analytics program for fraud prevention. Danielle is a director at PKF Texas and served as a part time faculty member at Rice University in the Jones graduate school of business. She is a certified public accountant, certified fraud examiner and a certified valuation analyst as she also serves as the chair for the PCPS technical issues committee with AICPA. Five times she was named to the 40 under 40 by the CPA practice advisor and she was recognized four times as one of the most powerful women in accounting by CPA practice advisor and AICPA. Danielle is a true accounting expert and covers a number of topics relating to analytics and fraud for us. So let's start the conversation.

Music: (01:37)

Mitch: (01:39) Data analytics has been a hot topic in accounting, but are companies jumping into data analytics too quickly? In your opinion, what should they be aware of and make sure they do first?

Danielle: (01:45)

I actually think it's the opposite. I don't think they're jumping in fast enough. You know, you can actually do a data analytics program fairly cheaply and honest. So if you overly invest on the front end before you really understand what you have, it's going to be a very costly process and you have a risk of a lot of sub costs. So I actually think people should take a, you know, a page out of the agile project management methodology and kinda jump first, figure out what they have and then start fine tuning as well as there's actually a fair amount of learning about your data. As you start getting into a program and since the software has become so cheap, it's usually a fairly easy initial investment to figure out what you have.

Mitch: (02:28)

So then how do you begin even thinking about what needs to go into this program? How do you build an efficient data analytics program?

Danielle: (02:37)

I would say you kind of started a couple of different places. One, of course you have to inventory your data and figure out what you have. Sometimes you know, it's just a matter of, let's see if I can get an export out of my system just so I can start seeing what the data is. Clearly, if you have access to a data dictionary, which is kind of a summary of all the different fields of data behind the system and what it actually means, that's really, I mean best practice and really helpful. It saves a lot of heartache and grief, but a lot of times it's inventory. What you have, you know, sometimes it's as simple as let's start in Excel, let's move on to some of the bigger packages. You know, these days Tableau is so relatively cheap. Power BI is coming with your 365 implementation. So you can start doing a visual exploration of your data and seeing what you have and starting to focus on what are the areas that you think you have risks and really fine tuning it to your risk of your business.

Mitch: (03:30)

Well, let's talk about that risk a little bit more now. I know you've referenced in previous conversations with me something about a fraud tree and some of the common risks that you can help identify around your business. So what are some of the examples of fraud that you've seen that maybe, you know, could have been prevented or avoided if there was an effective data analytics program in place?

Danielle: (03:51)

Yeah, so the risks of your business really do come with whatever is your industry as well as how you operate. And a lot of companies have a hard time identifying particularly fraud risks of you know, it could never happen to me. And the cost of fraud is so high. So what you end up doing is you can use the association of certified fraud examiners, fraud classification tree. And what they do is they take three major classes of fraud, which is the fraudulent financial statements, so just fudging the numbers in effect, a misappropriation of assets. That's kind of all your thefts of cash. That's inventory expense report type frauds, payroll frauds and classify all those as well as they have a corruption tree. And so it's really useful to actually take this, it actually looks like a little flow chart tree diagram and in three different branches and go through each little box and say, how could this happen to my company? How would the data show this? Because one of the things that your, your financial statement data is always going to be what's getting manipulated when you're trying to cover up a fraud. But what you can find is some operational data, hopefully that, you know, you can hide the numbers potentially if you cover it up. But how do you hide that behavior that's happening operationally to cover it up and that's much more difficult. So starting to use the fraud tree classification tree, that was mainly an academic exercise that ACFE put together and use that as your starting place of what are my risks in my organization for fraud.

Mitch: (05:21)

What are some of the other I guess, you know, fraud prevention practices that you could recommend in addition to just kind of looking at the risks, the financial data, the operational data. What else do you see organizations doing to try and prevent this you know, illegal activity?

Danielle: (05:37)

Yeah, so I would say the absolute number one best way and ACFE agrees with me is having a whistleblower hotline or a reporting hotline of some sort of the hotlines are so cost effective these days. You get one of these third party systems. By the way, if anyone's listening happens to be a nonprofit, they usually give nonprofits discounts and you can a fair amount of information on those even if they charge by the minute for somebody leaving a tip for you. Cause most fraud is discovered by tip. Even if it's not actually fraud and it's just some kind of waste or abuse that is really valuable information. And even if it's like a dollar a minute, that's still far less than anyone else's hour of investigative work from somebody like me or more my colleagues. So putting that in place gives you a lead and it gives you, especially if you're nonprofit, you get a easier nine 90 checklist item. But for everybody else, it also gives you the ability to get that information, have that corporate culture of reporting and that we're trying to do everything very openly and transparently. And when there is a problem, there's a resource for people to go to and that's really helpful because you can get that data faster and have someplace to go first. And then right after that is that data analytics of proactive data monitoring pro...