Last week I was meeting with one of our company’s Accounts Payable clerks, who told me she was not concerned about some upcoming General Ledger changes.
2 changes that were submitted by developers on her behalf.
2 changes she didn’t know anything about, so she didn’t consider them her problem.
This post is a Quote of the Weak post. For more info on these types of posts, see the Quote of the Weak topic under About.
I’ve received an artificial intelligence (AI) marketing failure in the mail recently. Well, I think it was an AI failure; it sure was a marketing failure.
About a month ago, I received a letter saying that I could save a lot of money on my 15-year mortgage. It gave my current rate, the rate I could get if I refinanced, and the amount of the new payment.
I recently posted about 4 common AI fallacies or myths regarding artificial intelligence (AI). I wanted to dive a little deeper into some of these myths, and discuss why AI will NOT take over the world.
First of all, it is easy to fear what we don’t really understand, especially when some people push the narrative of computers becoming ‘aware’, which would result in them dominating the human race.
An article posted on MachineLearningTimes.com discusses 4 common fallacies or myths regarding artificial intelligence (AI). These misconceptions lead to many misunderstandings and fear* regarding AI.
Wikipedia defines AI as “intelligence demonstrated by machines, unlike the natural intelligence displayed by humans and animals, which involves consciousness and emotionality.”
I like Investopedia’s definition better*: “the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions.”
In the post, Melanie Mitchell, Davis Professor of Complexity at the Santa Fe Institute and author of Artificial Intelligence: A Guide For Thinking Humans, lists the 4 most common fallacies that I would summarize as follows:
- Narrow intelligence (being really good at one task) leads to general intelligence (being good at many things, the way humans are). In other words, computers will become super-smart and take over the world.
- Easy tasks are hard to automate/hard tasks are easy to automate.
- AI works like the human mind. This comes from using ‘human-y” terms like learn, understand, read, and think, which leads some to believe AI can achieve humanness.
- Intelligence is all in the AI brain. In other words, “the right algorithms and data…can create AI that lives in servers and matches human intelligence.”
As an auditor, I am told all the time by the business that “we have a current project plan that is addressing that risk”, which implies that I shouldn’t waste everyone’s time writing up an audit issue regarding the problem.
It means that the risk isn’t as big as it appears.
The other day I was in a meeting to discuss a new analytics project and discovered the team had no end goal.
When the discussion started with the software to be used, I knew they were already off track.
When you’re trying to get a data science job, you need experience, but to get experience, you need a job, right? Not always, and this is the case for many jobs, not just data science.
But in data science, you can generate the experience you need yourself.
You might have seen one of my earlier posts, How to get an IT Audit job with little or no experience. Let me say from the beginning that getting an IT audit job with no experience is easier than a data science job with no experience. But according to an article from KDnuggets, it can be done. And like everything else, it takes hard work.
The article defines data science as “an interdisciplinary field that focuses on solving problems and gathering information.”
It seems to me that auditing as a profession is not full of critical thinkers, much less thinkers.
If you read my last post about auditor judgment, I’m struggling with some of the junior auditors that I’m working with.
But I’m also struggling with quite a few of the senior auditors that I work with, those that are my peers (which means they peer at what I’m doing and how I’m doing it and then continue on their merry paths).
I came to this opinion based on most of the auditors I’ve met through the years across many companies, small and big, and across sectors, including public service. And also by the many articles calling for the profession to do more critical thinking, and yes, it is needed.
But let’s start with plain old thinking (walk before run).
Companies need to create a help desk for data, similar to the help desk they created for hardware, software, application, network, and user problems.
Can you imagine if companies didn’t have a computer help desk and each department had figure out their own computer issues? If each department had to find, load, configure, and troubleshoot their own hardware and software?
But isn’t that how most companies operate when it comes to data and data projects?
I’ve written before how some periodic reviews provide management with little assurance, but management doesn’t realize how little.
My previous post focused mostly on server access￼. In this post, I want to look at normal user access.
For example, let’s assume your company has a policy that states that all IDs must be assigned within an Active Directory group. In other words, IDs are assigned to groups, and groups are assigned to assets; IDs should not be assigned directly to an asset.
Assume the control you are testing states that user access is reviewed annually.
A looooooong time ago, Leeann asked me to write a post about blogging about internal audit, so here goes. Most of this post applies to blogging on any subject, too.
First of all, there is a dearth of good internal audit blogs, and even less good IT audit blogs. So if you’re thinking about, we sure could use you in the blogsphere!
Writing a blog is hard work, and you often get tired of it. Life finds a way to get in the way. This is my 11th year of the blog (see the first post here), which, ironically, was written by skyyler. Fortunately, we’ve gotten better since that first year.
Blogging about internal audit is like a moon shining in a dark place… here’s my 10 tips…
Filed under Audit, Blogging
This is the third of 3 posts; this post describes how I audited the auditors and my perspective on the whole thing.
Read the first post (background) and the second post (audit results).
This is the second of 3 posts; this post describes the audit, some speed bumps, and the audit results.
Read the first post here, which provides the background on the audit and the audit’s scope.
Usually, I’m the one doing the auditing, but this time, I (Mack) was the one who was audited.
It was a great experience for me.
Well, sort of. No one likes being audited (ahem). But it gave me a fresh perspective of how others feel when I audit them.
This is the first of 3 posts; this post contains some background info on the project that was audited, and the second one discusses the audit and the results, and in the third post, I describe my perspective on the whole thing, and some takeaways.
Have you ever wondered why I selected the picture above to represent my blog?
This picture illustrates so many aspects and nuances of this blog’s theme.
Here’s your chance to put on your thinking cap, and based on what skyyler and I have written about over the years, tell me what YOU think it represents.
As the comments roll in, we’ll comment on them.
Then, after a few weeks, I’ll peel back my brain and give you a peek inside as to what my reasons were.
Not sure how many of you will take me up on the challenge, but here goes…
While you are checking out my blog, make sure you don’t miss all the free advice that’s laying around.
And I’m not talking about the blog posts (those are good too).
Whether you a new reader or you’ve been around since the beginning (2009!), when you find a post you like, don’t forget to do the following after you read it:
- Look in the upper right corner of the website for my Quick Links. This will take you to multiple posts on these subjects.
- Use the Search Box to search for key words.
- When you read a post, check out the Comments. We respond to a lot of questions and provide information that isn’t in the blog posts.
- Leave a question of your own in Comments. We will respond.
This is Part 4 of a Case File series that describes how real auditors tried to apply questionable methods to auditing and data profiling. See Part 1, Part 2, Part 3.
Does the Process X team provide metrics around their process?” I asked.
“Yes,” the most senior auditor replied, showing me the web page where the Process X metrics were displayed.
After reviewing the page briefly, I said, “I see they do metrics by month. You have a year’s data; are you planning to understand how they prepare their metrics and re-calculate them to see if you get the same numbers?”
This is Part 3 of a Case File series that describes how real auditors tried to apply questionable methods to auditing and data profiling. See Part 1 and Part 2.
I looked at the third page of the handout and asked, “What is this?”
“A list of Active Directory (AD) groups and the user IDs in each group. I searched AD for any group containing the system name,” the junior auditor said, “and identified these 6 groups. I then downloaded all the members of these groups from AD into Excel.”
Some auditors struggle with basic auditing. So when these auditors try to data analysis, well you can imagines how that goes.
I recently met with a team of auditors to give them input on what data profiling would be appropriate to perform. And what analytics might be insightful.
This is Part 1 of a 4-part Case File series that describes how real auditors tried to apply questionable methods to auditing and data profiling. Do not try these methods at home or work. Don’t even dream about them, awake or asleep.
Microsoft announced that they are adding a big brother to vLookup named xLookup.
The best things about xLookup: 1) it fixes some of the limitations of vLookup, 2) it is easy to understand and use, and 3) it replaces hLookup also.
Also, vLookup and hLookup are not going anyway, so if any of your colleagues struggle to learn new things, they can continue to use them as is.
When auditors need to identify and understand IT controls, they search the company intranet, review policies, look for Github repositories, review inventories, schedule meetings, and analyze IT asset data.
I stumbled on a better way to get insight into the IT controls in my company, and I didn’t have to email anyone, do any research, or frankly, anything outright. The IT controls came after me.
Fortunately, the IT controls were blind to the fact that I am an IT auditor. To them, I was just an ordinary bloke. But that didn’t last long (more on that later).
It Began a Few Years Back
It all started a couple years ago when I was building the infrastructure required to support our data analytic efforts in internal audit.
Before you start analyzing data, you need to 1) know you have the right data, and 2) understand the data and the process that produced it.
This post assumes, of course, that you already accomplished some of the hardest tasks already: figuring out what data you need, where to get it, and actually getting the data. Good luck with that. :)
This post is part of the Excel: Basic Data Analytic series.
Before you analyze data, you should profile it.
Otherwise, your analysis may not be too broad, too narrow, or you may miss some important insights or errors.
This post is part of the Excel: Basic Data Analytic series.
Data profiling is developing a profile of your data, just as facial profiles of a person, taken from various angles, helps you size up a person’s nose, identify whether his chin is sagging, and how far apart the person’s eyes are.
It’s official: ACL is changing its name AND its spots.
I’ve claimed several times that ACL has left its first love (analytics) and doesn’t put enough work into their flagship product, ACL Analytics.
Correction: their FORMER flagship product.
At least they are publicly admitting it finally–they NO LONGER are an ANALYTICS company!
Rumors have it that ACL will no longer be available on the desktop (laptop, or other local machine) in 5 years.
That is, according to an ACL user who attended the 2018 ACL Connections conference.
If you are in IT, audit, or security (or any other job requiring data analysis), you should NOT be cleaning data manually.
Let me share a recent experience with you….
A young IT auditor texted me at work and asked for some Active Directory user account data that I capture automatically every week, using some scheduled ACL scripts.
If you’re not familiar with my ‘Quote of the Weak’ series, I described it briefly in About. For a list of posts in this series, see here.
Test how much you know about automation technologies by taking the job automation quiz at Financial Management magazine.
Contrary to what ACL has been touting as their new ‘robotics’ feature, it is NOT robotics process automation (RPA).
[The ‘robotics’ feature is due out later in 2018. It appears to be ACL’s latest attempt to get you to use their GRC software.]
ACL, via John Verver, defines the term this way in his RPA article: “The idea is a relatively simple one: get computers to perform tasks normally performed by humans, and cut resource and time requirements for many repetitive activities.”
When you need to rename ACL tables, be careful to also rename the associated .fil file also.
Otherwise, you (or your ACL script) might get confused. You might delete the wrong table or .fil file, and create a head-scratching problem.
I know because I confused myself.
Recently, a large U.S. bank was found to have created unauthorized accounts; a similar bank closed one of my accounts, but doesn’t know why it happened.
More than a decade ago, I opened a safety deposit box at a local bank (a very large U.S. bank that all U.S. residents would have heard of). This wasn’t my regular bank, as my bank didn’t have such boxes; I only went to this other bank when I needed to access my safety deposit box, which was not often.
Filed under Audit, Security
To increase the amount and depth of the analytics performed, steal some agile methods, and apply them to your audits.
If you’re not familiar with agile methods, check out the first 5 topics listed here (just click Next at the bottom of each page; the topics are quick to the point and full of pictures).
Briefly, agile projects are performed in cycles, or iterations, rather than in a long, linear-waterfall fashion, which is: do all planning, then field work, then reporting. Each iteration of the project creates some value and includes feedback, which is used in the next iteration to increase the value of the project.
A while back, a reader named Kyle and I had a conversation about analytics.
It started with his reading my Excel:Basic Data Analytics post where I list a number of procedures that anyone can do in Excel.
Kyle said he was expecting some “super sophisticated process & methodology that works like magic.”