I still like Big Data! But there are big gaps in what it sees. It’s your job to know that.
Ø FRAUD LAWSUIT
Ø TIME SHARE CONDOMINIUM
Ø VACATION RENTAL IN THE CARIBBEAN
Ø 4 BUSINESS AFFILIATIONS
These were all key findings in a recent research assignment. I didn’t find them in any of the global or comprehensive reports I obtained at the outset of my research, or what I call “Big Data.” Nonetheless, I still like Big Data.
Way back in February 2022, Pursuit Magazine published my paean to Big Data. It was about 1,500 words arguing the value and worth of global database reports. I wrote it to address my angst — that Big Data reports should be relied on and used in research projects. I had to defend the honor of my Lexis subscription.
When I wrote that article, I cited a video knocking global databases. It was one example of many I see on social media, on LinkedIn, in seminars, and whispered in the haunts where open-source researchers hang out: Antipathy for global reports. A dislike of Big Data.
Sure, there are good reasons to be skeptical of Big Data. My hunch, however, is that much of the opprobrium stems from two factors:
· Many users get these reports instead of hiring OSINT professionals.
· Unscrupulous practitioners take these reports, slap their logo over them, and pass them off as due diligence.
The reality is that both of these things happen. Both are slipshod practices and result in crappy work product. And both can make it harder to get clients to buy your thorough research.
Nothing can prevent bad actors from using Big Data in the aforementioned crappy ways. But I’m still here to make the case to earnest, upstanding researchers and investigators that Big Data is worthwhile IF you know better than to rely solely on global databases. To make my case, I put before you the following: a time share, a vacation property, a fraud suit, and four more business affiliations. You’ll see how Big Data failed to find these things and why I still couldn’t have found them without Big Data. And maybe you’ll think twice about your Big Data Feelings.
The Big Data in Big Data
Wait. What is this Big Data of which we speak? What is this thing that can be used in crappy ways? For those of you who haven’t read the previous article, let me explain.
When I say “Big Data” or “global database report,” I’m referring to products sold by various vendors that combine many searches into one big fat report. The general feature is that these reports link to a person or company via some form of identifier — an address, phone number or other personal data. Then that person or company is run through a buffet of public records and sometimes, social media. The results are presented clearly and simply over a few pages. The trouble is that the public records buffet varies in scope and completeness — and so, the extent of these reports also varies.
You need to know what you do not know — and what the databases can’t find.
Thus, these global reports are never a substitute for detailed research. They may offer excellent insight and leads, and as I argued in February 2022, they should be a big tool in your research toolbox. But they will often omit things, and you may not know what’s missing.
You need Big Data. But you also need to do other searches.
This dovetails into the biggest skill you need as an open-source researcher: You need to know what you do not know — and what Big Data can’t find.
Instead of having a list with 500 sources, have one source or maybe a few, and know what each one can and cannot do. When you run your global report, know what’s there and think about what might not be.
You also need to know what is never there and what probably cannot be found where you are looking. For instance, very little by way of litigation records gets covered in these reports, so you need to point your browsers elsewhere for civil and criminal litigation filings, which we’ll come back to in a moment.
The other thing is, all sorts of public records are available in some places but not in others. Your global report may have voter registration records, or maybe it won’t. It depends on where your research subject lives.
What’s worse is that these Big Data reports are often misleading: Sometimes they’ll show search headings or categories but no results. But the “no results” heading doesn’t necessarily mean that the Big Data machine did the search and found nothing; it may just mean that the database didn’t have access to that set of records at all. That’s why it’s easy to get confused about what Big Data reports have actually covered — and whether a “no result” actually means that a certain record doesn’t exist or that the database simply doesn’t have access to it. A key skill is knowing this.
Do not give up your Big Data. Just know its limits. Know them well.
Go forth with this knowledge and accept Big Data for what it can do for you.
Next, I’ll give you some examples of how this played out in some cases I worked.
Finding a Fraud Lawsuit
As I mentioned before, you’ll almost always need to do additional searches beyond your initial Big Data hit to find litigation records, particularly civil litigation records. It didn’t surprise me that I failed to find the fraud lawsuit in my global database report. It wasn’t in Big Data, but it was not hard to find otherwise, especially because I knew the state court database search would be part of my research scope.
If there’s another truism in research, it’s that every name is common. At first blush, I thought I had a guy who had an unusual name. Not in his state, as it turned out. The data in my Big Data report helped me pinpoint which records (of many) to examine, by providing me vital information, like addresses, to nail down which guy by that name was my guy. Because this was an especially good state for public record research, I could cross reference addresses listed on lawsuit records to addresses listed on Big Data. Thus, I knew the fraud lawsuit involved him.
I did not need to send out a stringer to get the case file. I had it.
Finding the Time Share
The time share was not in the Global Report. Big Data missed it. It was not in his county of residence either; my search of those property records was useful, but it did not lead to the time share.
What led me to it was a lawsuit over unpaid assessments for the time share. And I used information in my Big Data report to make sure this lawsuit involved my subject. His ex-wife was a co-defendant. His address was in the litigation docket. If you’re sued regarding a time share, you probably own one. The deed is probably recorded in a different county. A county record I could otherwise search.
Big Data did not find the lawsuit. Did not find the time share. But without Big Data I would not have found the lawsuit or the time share. Without Big Data I would not have known that the lawsuit that led me to the time share was against my guy.
Finding a Vacation Property
The vacation property. It’s a nice house. On an island. And there’s a web page advertising it. Nowhere on this record was my target’s full name listed. Still, I knew enough, from Big Data (and other open-sources), that I could say this property was his based on other things I found on the vacation rental website.
It was a reverse image search that cracked the case. It was not just an image of my guy I found online; it was a deleted LinkedIn account that drove me to search for the image, but you do not really need a reason. If you find an image online of your research subject, always search on that image. Any image you find of your research subject is worth searching using Google Lens or other image searches.
Image searches help you in two ways: First, as in my case, they produce results when other Google keywords do not. In other words, your target can appear on a page without his or her name. Second, image searches cut through the morass of Google results and lead to vital information. Things that show up often on image searches are social media activity and web pages from previous positions. Both items are useful in gathering background information.
The moral of the story is that you need to do more searches. But you need leads to launch your search, and you need additional clues to confirm that what you found are the right things to find — 90 percent of research is spent eliminating “false hits.”
Those Other Business Affiliations
As to those business affiliations found that were not in the Global report: I don’t blame Big Data. They were old companies, not even listed in the state’s Secretary of State database. They showed up in open-source searching, not on the subject’s name, but on his address.
Don’t just search images. Search addresses, too.
Where did the addresses come from?
You know the answer. Except you would not know if you were afraid of Big Data.
Search Many Ways
The big lesson here is when you’re putting together a profile, doing due diligence, or tracking someone down, you need to search several ways and in several sources. You won’t get it all from Big Data. But you still need Big Data. You need those addresses, phone numbers, husbands and wives, all sorts of things that turn up in these reports.
You may not like how others misuse them. You should use them anyway.
A version of this article first appeared at Robert Gardner’s Manage Risks blog and was reposted with permission of the author.
About the author:
Robert Gardner likes to think he has been performing research so long, credit reports came on stone tablets. Over a long career, Robert has worked with private investigators, forensic accountants, fraud auditors, litigators and others who need vital information to make decisions and react to unforeseen problems. Robert works in all aspects of business research including due diligence, litigation support, fraud investigations, asset searching, and competitive intelligence. He has made inquiries in nearly every part of the world. Well versed in a variety of data collection methods, especially online and Internet searching, he has transformed public record findings into reports, charts, schedules, timelines, and databases to assist in many situations.