LPRC - CrimeScience – The Weekly Review – Episode 131 with Dr. Read Hayes, Tom Meehan & Tony D’Onofrio

Episode Date: December 22, 2022

NEW INTERVIEW with Lead Director at CVSHealth – Adam Oberdick! In this week’s episode, our co-hosts discuss the continued planning of LPRC Integrate, Twitter allowing previously censored individuals back in, the continued cyberattacks this holiday season, and a riveting interview with Adam Oberdick about the innovation initiatives at CVS! Listen in to stay updated on hot topics in the industry and more! The post CrimeScience – The Weekly Review – Episode 131 with Dr. Read Hayes, Tom Meehan & Tony D’Onofrio appeared first on Loss Prevention Research Council.

Hi, everyone, and welcome to Crime Science. In this podcast, we explore the science of crime and the practical application of this science for loss prevention and asset protection practitioners as well as other professionals. Welcome, everybody, to another episode of Crime Science, the podcast from the LPRC. This is the latest in our weekly update series. And today I'm joined by Tony D'Onofrio and Tom Meehan, our producer, Diego Rodriguez, as well as Wilson Gavrino. And so what we're going to do is talk a little bit about the LPRC, a little bit about crime, a little about the dynamics, and hopefully looking for better and better ways for all of us to manage the issues that we are confronted with every single day.

I'm going to start off, talk a little bit about, again, just reiterating that we've got our January 18th LPRC kickoff event hosted by Bloomingdale's in New York City, Manhattan, in their flagship store. If you're an LPRC member and you're wanting to get involved and engage and help us plan, join 100 executives up there and our team, then we recommend you go to the lpresearch.org or email to operations at lpresearch.org. Again, for LPRC members that are part of the Board of Advisors or the LPRC Innovate Advisory

Panel and then select other guests, we'll be meeting in Gainesville for LPRC Innovate Advisory Panel, and then select other guests. We'll be meeting in Gainesville for LPRC Ignite, our annual winter planning meeting, as well as Integrate, which will be our integration scenario with embedded tabletop exercises designed to really leverage and test and strain and break and rebuild and enhance our knowing about what's going on sooner and sooner, having better definition around what these crime events are, what these offenders are talking about, what they're doing, what that means for risk for us and our places. So the sensors are arrayed across the five zones of influence, that journey to and from a crime event to harm victim one, place one. What's that look like? What can we know and how can we know it? How do we better analyze it, disseminate it for action?

What do we know during the event itself at bang or contact? And then again, what do we know right at bang after that place has been victimized? Maybe we have an opportunity to do a couple of things. One, maybe prevent a victim, too. If these people are heading toward another location in our scenario, they will be. Maybe we can prevent that second victimization. And then thirdly, of course, collect forensic evidence, digital, oral and and visual across that spectrum, across the behaviors before, at, and during, and after the event for better forensic evidence so that we can work more closely with law enforcement and with our prosecutors to take these individuals, these dangerous crews out of circulation so they're made and prevent and may not be a victim three, four, five, six,

or at least for a long time. So that's going to be Ignite. That's going to be Integrate in February in Gainesville in that 21st, 22nd timeframe. We'll switch over, talk a little bit about some of the criminology and some of the concepts we're putting into play and have been really with our research on individual projects, but across these more sweeping projects where we're looking across place and time of the offender, more holistic view. And again, it's all about an individual or a crew or a group of individuals, two or more that are working together in this case to harm somebody and or some place. And what is that exposure? Because we talk a lot about risk and having risk numbers, risk assessments, audits, software that helps us assess that and so on. And so we think a lot about

and do a lot about that. We research around that concept. And of course, we read the research, the literature, the published literature, or during criminology events to understand how others are looking at target risk. What is it about why one place or one individual gets hit and another does not? It's things about the offender and their behavior and their activity awareness spaces that they move in. Part of it, though, is about the target itself, right? That person, that money, that merchandise, that place, and so on. So in this case, that's what we're trying to look at is what's that target attractiveness?

Why are some targets more attractive, more desirable to strike or to steal than others. We look at that, how readily they're converted to cash if it's merchandise, for example, how portable or mobile it is, easy to get it in and out, get rid of it, convertible to cash and things like that. We look at exposure. So exposure is a little bit about what we're talking about today. Part of that is what does it look like, but how much, how exposed is an individual or a place to crime relative to another person or another place? How exposed are we in that case? And that's why you hear the old saying, nothing good happens after midnight and so on. But if we place ourselves, we place our property in a place in time where it's

more exposed to would-be criminal offenders that are either opportunistically might happen upon us or our stuff because we're more exposed and are attractive to whatever they're thinking in the moment, or to predatory criminals, an individual or a crew that are looking for attractive, desirable, but vulnerable, and of course, exposed targets. That's really what we're talking about today on this little mini discussion. Offender awareness is critical. If they don't know something's there, it's why we talk about with porch piracy, if the delivery person would conceal the delivered package behind a box or in a box or behind a planner some way that it's not exposed to, again, an opportunistic or predatory criminal,

an acquisitive type criminal, somebody that's trying to acquire other people's stuff for their own use or convert to cash, that's the first step, right? So there has to be some offender awareness of what we got. And that's how exposed we are plays hand in hand with the offender awareness of us or our stuff as desirable. So in our store, the more exposed we are means we're in the trajectory of a lot of criminals, Exposed we are means we're in the trajectory of a lot of criminals. Proximity to a lot of offenders, the density of those offenders or the places around us, those places that generate or even radiate risk. If we're near a biker bar and we're also near to an interstate with a quick on and off ramp, if we're nearby concealment areas and ambush areas,

if we're near quick escape routes and things like that, we're not only exposed, but we're much more desirable target and makes it easier for the criminal. And so we're more likely to be selected. And that area is probably not only going to have a problem now, but probably have persistent problems. And so another way to look at this is aggravating and protective features. And some of the aggravating features are what we talked about. We're close proximity to a dense amount of criminals and or places that harbor would be offenders, places that would conceal those people, places that make it easy to get to and from us, to ambush us, have, again, quick exit routes, especially ways to get away from any pursuers and so on. that these concepts are very important in understanding why some places experience more problems than other places and why those types of harmful events happen more readily and more frequently at some times of day or days of weeks or months of year than other times and dates. These are all ways that we look at and understand what do we do about this? Can we reduce the

exposure? Can we reduce the exposure? Can we reduce the desirability? We know with desirability, that's what we've tried to do with benefit denial, saying, look, we're going to make this target less attractive because it won't function or be readily convertible to cash, for example, unless you buy it. If you steal it, it's not going to work. So that's how we affect the desirability to a certain extent. But working on how exposed it is is another way that we can do that. And I mentioned that with porch piracy. Sometimes we have to take items off the shelf. We know with high-loss merchandise in some locations or during certain times of the day and just have cards. It's not preferred business practice. It's not a great

shopper experience ingredient, but sometimes we've got to reduce our exposure there. In our own behavior, if I go walking around at certain times of day or night, in this case, in an area that I know have had frequent attacks and I'm sporting some expensive watch on my arm, I might be more not only desirable but much more exposed and generate more likelihood that I could be victimized. So the same thing with our place is applied. But I think that one thing we're trying to do with the LPRC and with the University of Florida and with crime science is understand the science of crime, understand how people and places come together, how context plays a role in current crime, persistent crime places, emergent and displaced crime places, and these kind of ideas because they help us understand and analyze and improve the likelihood, reducing the likelihood that our place, our merchandise, our people will be victimized by those that are opportunistically or in a predatory way looking to harm. So with no further ado, if I could, let me turn it over to Tony D'Onofrio.

Tony, take it away. Thank you, Reid, for those great updates. Let me start this week with a report from Fox News and comments from Walmart CEO on retail crime. Theft is an issue. It's higher than what has been historically said Walmart CEO Doug McMillan, who told CNBC Squab Box earlier this month. He added that if the crime wave is not halted soon and if prosecutors don't bring charges against shoplifters, prices will go higher and those stores will close.

Crime has weighted heavily on retailers across the country this year, ballooning to about $100 billion, according to the National Retail Federation. Walmart competitor Target reported this year that shoplifting incidents have increased 50% year-over-year, causing $400 million in losses. Some criminals, however, have gotten even more creative and bolder than shoplifting, just as a few items in well-known and relied upon stores such as Walmart reports show. This month, a pair of Pennsylvania residents were busted by police for participating in a multi-state Walmart crime street that has left the store with at least $25,000 in losses. Police were called to a Walmart location in Clearfield, Pennsylvania on December 5th

and arrested a 37-year-old who was accused of repeatedly filling shopping carts with items ranging from baby clothes to computer accessories and bracing walk out of the store. Police also arrested a 21-year-old in the scheme and an authority said there are other suspects in the case. The suspect allegedly filled the shopping cart for goods, then passed the cart to someone else in the self-checkout line to really try to get around security, and then simply walk out with the merchandise.

In another case, a couple managed to confuse a Walmart cashier and stole more than $6,000 in merchandise and gift cards, according to authorities. They allegedly went to the checkout line with a card full of expensive merchandise and tricked the cashiers into believing they paid it by using multiple credit cards and then asked the cashier to use the cash button to ostensibly make the credit card work. The sale was then rung up as a cash payment so a non-card was charged. And in Texas, a man described as a magician by local police

managed to steal $2,700 from Walmart cashiers with a quick change scheme, a quick change scheme in two separate instances in January and February. So that's Walmart news on crime. Switching over to San Francisco, similar news and more insights again from Fox News in terms of what's being done in San Francisco as it relates to activities that the police is doing to combat retail crime. San Francisco police have been staking out retail and grocery stores to catch shoplifters and have arrested 60 people since the covert operation launched last month, officials said. Details of the operation are slim, but police said that officers have been deployed to monitor pharmacies, grocery stores, and retail stores across the sea.

The stores include Walgreens, Old Navy, Target, Whole Foods, CVS, Macy's, that's reported by the Chronicle. These operations have resulted in 13 felony bookings and 47 misdemeanor citations, and their work continues at the San Francisco Police Department. Roughly half of the 60 arrested suspects were offered diversion, while the other half are facing prosecution ranging for commercial shoplifts in the Grand Theft. The operation will last at least another month, so police getting more aggressive in San Francisco. Also interesting this week is some news from the National Retail Federation and the Priests Retail on retail returns. So a brand new research just published.

Consumers are expected to return more than $816 billion of retail merchandise purchased in 2022, according to a report released by the National Retail Federation and Upplace Retail. As retails continue to grow, the average rate of return has remained flat at 16.5% compared to 16.6% in 2021. According to the retail survey, for every $1 billion in sales, the average retailer incurs $165 million in merchandise returns. Additionally, it was found that for every $100 in return merchandise accepted, retailers lose $10.40 to return fraud. Of the type of return fraud retailers have experienced in the past year, half-sided returns of used non-defective

merchandise, also known as wardrobing, and just over 41% cited return of shoplifts or stolen items. One-fifth attributed return for to organize retail crime. Interesting, again, what's happening in terms of returns. And again, there's a study that I actually made available on my website if you want to see it. It goes deep in terms of what's going on with returns, including what's going to happen during the holidays. And finally, since this is Christmas week, what actually let me summarize with all this and talk about inflation. What does do those 12 days of Christmas, that song about the 12 days of Christmas. What does it cost this year? So let's turn to 20years.com for the answer. PNC Bank, based in Pittsburgh, released its annual Christmas price index,

adding up the 12 items from the partridge to the drummers. All in, the total price of one set of each item is up 10 percent so the cost of the 12 days of Christmas is over is up just over 10 percent by far the cheapest item on the list are the milkmaids with PNC using the 7.25 federal minimum wage as the cost of their higher however other human gifts cost well over ten thousand dollars with so many animals on the list pnc said higher feed costs are a huge part of the price hike this year plus the price of gold spiked 40 percent in 2022 the highest increase of any items on the list so those golden rings are really expensive this year. So in total, those 12 days of Christmas will cost you this year, drum roll please, $45,523.27,

up 10.5% on last year because of inflation. So with that, I want to wish everyone that listened to this podcast a Merry Christmas and a Happy Holiday season. Looking forward to bringing you more great information next year. And let me turn it over to Tom. Hello, everybody. And thank you, Tony. Thank you, Reid.

Wanted to kind of talk about a couple different things today. Not a lot to cover today. I don't want to be too repetitive here. But I wanted to talk about something that some researchers are starting to see, which is fake malware and fake ransomware. And the idea here is that the malware confuses researchers. here is that the malware confuses researchers. So one of the things that we're starting to see is this malware that's being detected that obfuscates. So it's designed to look like traditional malware, but it's actually not. So they're throwing researchers off. And then in addition, they use that same type of technology in the malware, in real malware. So basically, what you're doing is it's almost a Trojan horse of an attack attempt. So you create a,

what looks to be a malicious code that ends up not being, delivers a fake payload and actually throw a fake threat payload and actually doesn't do anything and then you mimic that in a negative piece so the we now have the the bad actors really taking the approach of let's see if we can even in the most advanced detection systems create a design software that can beat it but what they're also doing is almost sending out false payloads so that when someone is going to look at this or either ai or a person it's actually harmless so this is a really sophisticated way to attack some of this malware goes through several different fake payloads confusing research and basically evades detection.

And then it actually does become real malware later on or ransomware. So this is not necessarily new, but we're seeing a big increase. So what does this mean for the listeners? Not necessarily a lot, but what it does is it takes your traditional method of detections and really, but what it does is it takes your traditional method of detections and really, really challenges it. So it's almost in the, I like to call it the boy who cried wolf, right? You see this event, it doesn't turn out to be events. So then you basically discredit that. But then while that's going on, there's another event that occurs. Now I'm oversimplifying this,

but basically you have multiple events that actually aren't, don't do anything. They create a challenge for both researchers and AI. And then behind the scenes, there's another one. So I do believe AI, there'll be models that can address this. And now once it's out in the wild, we'll be able to address it. But it's just interesting how much this is advancing in the malware ransomware situation. I wanted to switch gears a little bit to TikTok. So TikTok is really doing a good job of trying to address some of the challenges that are out and about. I know that TikTok's been under scrutiny

from the connection to the Chinese government, the ability for minors to use their service. But now they're really starting to flush out a why this video reason recommendation. So it actually is starting to say, we're going to show you, you know, why you're getting this video, what recommendations come about it, and what's occurring to get this recommendation. Why is this important? There have been a recent kind of unfortunate event where there have been children who have died. And I covered this briefly once before in the blackout challenge. They're seeing these suffocation games and these things and they're

dying and there's been legal action taken. And there's a lot of due diligence done from the defense standpoint to say, hey, there's no real tie to this occurred. Well, this is giving visibility to an end user or a parent to say, okay, this is why you're seeing this video. You liked this video before, you connected to this video before. It's really not giving the secret sauce of the algorithm, but it's giving visibility to why you might see this connection. So a big win, I think, for the community that we're talking when we talk about TikTok and some of the things that are occurring around it really brings more granularity and transparency in why content is being recommended. So it's a really huge win. Really, I think this is a step forward, and I think we'll continue to see it then wanted to talk a little bit about

in the internet space OpenAI it's chatbot GBT it's basically what this is it's called generative AI and this is like a large machine learning models and if you haven't heard about this OpenAI's

chat GBT has really become a conversation starter for a lot because it's the – not the first, but one of the more recognized first large model projects that have been released to the public. And what you can do with this is you could arguably and anybody can go on, open a free account and see how this works. And one of the things I would say is that you can go a generative AI model that really takes the next step in AI. And when you think of large model pieces here and you have these really complex, it's taking a whole bunch of data at the real time. whole bunch of data at the real time. And this is probably something that we're going to see in the near future. Certainly something from a content creation standpoint, it works, it's proven. Definitely you'll see more of this coming out. You could go on and literally go to this chatbot and ask it to write a story about loss prevention and give it some key, you know, key factors and you'd be shocked at how accurate it is. I've seen this gotten huge, huge press in the past three weeks. So for the listeners, OpenAI, chatbot, GBT,

you could try this out, but it's not perfect, but it's definitely, definitely probably the closest that I've seen to a really, really well-rounded generative AI piece. There are some paid companies out there like Jasper AI and some other companies that have done this before. The models are still driven by humans, so there still is a risk of bias. But the interesting part about some of these large models is the models are driven by humans, but they do learn from current events or Google. So you could actually ask it a question it's going to do in almost real time searching of Google and create a story based on what it is. What does this mean for us? I actually think this is something that you'll see in the future a lot more. Essentially, this technology does have the capability to have a human-like conversation with

someone on a customer service basis or create a very, very human-like response to a question regardless of what it is. It also allows a very human-like storytelling process. If you ask this a question about what do you think about organized retail crime and bail reform, you would see a really interesting answer. Now, what you'd find is that you might get, depending on how you ask the question, it might answer it with one type of answer that leans to one side of a debate, but you'd find that it's fairly factual in what it is. So very interesting stuff. I encourage anybody listening to take a few minutes to look at it. I think it's a really wild technology. I was impressed. I heard it and read about it

before, but it really, in the last few weeks, it's gotten tons of attention. And then I want to kind of end the story on the Twitter piece here. I continue to keep bringing this up because I think it will affect all of us here. There's been just a rash of news around Twitter and Elon Musk's purchase with censoring accounts, uncensoring accounts, a leak of the FBI paying to not have information disclosed on Twitter. And this is one of those big challenges around censorship in general when you talk about big tech and where to start, where to stop. And when we think about misinformation, what is misinformation defined as? How do you know if it's intentional or not? And so I think we're going to continue to see these news stories that are coming up while at the same time, some of the Elon Musk

pieces here, like Elon Musk doing polls about whether he should still stay the CEO. What I would say is that we all should stay closely tuned to this because I think the bulk of people that have special operation command centers using some of the technologies out there, a lot of that active intelligence event-driven data is pulled from Twitter. It is a great source of information when you're trying to identify what's going on in a particular area, especially around a weather event or a civil disturbance event. It really is one of those few tools in social media that's still widely used that way. So we'll continue to stay close to this and monitor it for you because I do think it will impact each and every one of us that use Twitter to do this.

However, at the current gate, I think it's just news. So with that, I will turn it back over to Tony Reid. Before I do that, though, just in case this episode is being taped very, very close to the new year, and there's a chance that you might not hear this till after the new year. And if that's the case, happy new year. If that's not the case and you hear it right before, well, let's get ready for new year. I hope everybody stays healthy and warm during the next couple of weeks. And we will talk to you soon. Over to Reid and Tony. All right. Well, thanks so much, Tom. And thanks so much, Tony, for all that good information. It's amazing the amount of information that we're able to quickly, hopefully get out to each and every one of us out there through Crime

Science, the podcast. We'd ask you all to like us, to pass on Crime Science to your colleagues. If you recall, we've probably got close to 200 episodes now, and they're on almost every one of the podcast platforms out there. There are retailers, there are universities that are incorporating crime science podcast into their coursework, assigning that to their people out in the field to listen in, go back and place in time and find some podcast episodes, listen to all or part of them, see if there are things that help you think about, question, improve what's going on, the outcomes for the places and people you're trying to protect.

So stay safe out there, stay in touch, and we'll talk to you next time. Thanks for listening to the Crime Science Podcast presented by the Loss Prevention Research Council. If you enjoyed today's episode, you can find more crime science episodes and valuable information at lpresearch.org. The content provided in the Crime Science Podcast is for informational purposes only and is not a substitute for legal, financial, or other advice. Views expressed by guests of the Crime Science Podcast are those of the authors and do not reflect the opinions or positions of the Loss Prevention Research Council.