Paul had constructed thirty discrete tests to perform, most of them numerical, but some were qualitative, searching and comparing the names and addresses of vendors, banks, warehouses, and products, as well as key words related to transactions, assets, destinations, and personnel. Connecting people, places, and patterns of behavior sometimes proved more valuable in cracking a fraud case, especially when the fraudsters were good at hiding the numbers. In fact, one of the Singapore banks that did business with Dalfan had been connected to the North Korean rare-earth-element debacle a few years ago, though no charges were ever filed. It was an interesting coincidence he would check out later.
But it was number-crunching that dominated Paul’s work. He believed that most fraudsters weren’t as good at hiding the numbers as he was in finding them, and he had the track record to prove it. But he was no fool, and it usually took a combination of both investigative approaches to crack the hardest cases. As far as he knew, Dalfan was innocent of any wrongdoing, but for the sake of this exercise, he was going to assume they were hiding something, and hiding it very well.
Would he find Dalfan vendors that changed bank accounts frequently? Had any Dalfan employees authorized multiple payments for items below a certain threshold limit to avoid triggering a limit alarm? Were there invoice receipts paid for amounts greater than the goods receipts they were matched to? How many purchase payments were made that exceeded the purchase-order amounts?
And then there was his Benford’s law search engine.
Paul rolled up his sleeves. It was going to be another long day, but it was still going to be a lot of fun. It was hard for him to believe that anybody could find this kind of work boring.
28
Okay,” Jack said. “So what else is there?”
“Mostly technical details,” Singh said. “Maybe not that interesting.”
“Try me.”
Lian’s eyes narrowed, calculating.
Jack flashed a roguish smile. “I’m sure those technical details will look really great on that report.”
She nodded to Singh, defeated. “Fine. Go ahead.”
Singh pointed at the video wall. He punched another button.
The red and yellow terminal points flashed specific addresses, then a list of names and accompanying photos of the occupants of each residence on record. Singh paused the program again.
“Where did you get that data?” Jack asked.
“What you see on the screen right now is all OSINT. Facebook, Twitter, LinkedIn, YouTube — these are all big platforms in Singapore just like the U.S. We also utilize phone number listings, tax records, and all of the public filings.” Singh paused. “But because this is a pilot project for the SPF, we’re also linked into their databases — immigration, prison records, internal security, civil defense, and even Interpol. So we can get virtually any information we need about anybody at any time if they’re in Singapore.”
“And you’re pulling all of them together into one analytical platform?”
Singh beamed with pride. “My teams write great algorithms. That’s our secret weapon, Mr. Ryan.”
“Even more impressive.”
Singh then highlighted the photo of a twenty-eight-year-old male named Ho who was living in the red terminal point. He tapped another key and more data came up. “You can see that Mr. Ho is employed by the delivery company we’ve been tracking. So now we have a good confirmation that he’s one of our targets.”
Singh hesitated.
“Is there a problem?”
Singh glanced at Lian one last time for a final nod of confirmation.
Singh continued. “If we let the software keep tracing their movements from the previous day, week, month, or year, we can collect all sorts of interesting data. Every time they enter a building we can determine who they are meeting with. Then we can trace the movements of those new targets as well. In this way, we can reconstruct entire networks of people, establish relationships, property locations, patterns of movement, et cetera, and all in far less time and for far less cost than traditional methods.”
Jack ran the calculations in his head, multiplying the number of policemen times the number of hours in stakeouts, surveillance ops, shift rotations, vehicle miles driven, and a dozen other cost factors that added up to hundreds of thousands of dollars in salaries and expenses for even small intelligence operations over a decent length of time.
“Let me show you a quick example. We’ve been running this test program for the last sixty-four days. So let’s see what Mr. Ho has been up to.”
Singh tapped several more keys. First, he cleared the screen of the yellow line representing the other delivery driver, then extended the time-trace parameter to sixty-four days. Nearly instantly, the screen filled with a crazy spiderweb of red lines, all tracing Ho’s movements, and all centered on Ho’s residence. The red lines mostly tracked along the same routes, with a few loose strands snaking around the island to parks, recreation areas, and shopping centers.