Posted by Tyler Wood, Operations Manager at Crime Tech Solutions
Although no fraud prevention measures are ever 100% foolproof, significant progress can be achieved by looking beyond the individual data points to the relationships between them. This is the science of link analysis.
Looking at data relationships isn’t straightforward and doesn’t necessarily mean gathering new or more data. The key to battling financial crimes it is to look at the existing data in a new way – namely, in a way that makes underlying connections and patterns using powerful but proven tools such as the Sentinel Visualizer software offered by Crime Tech Solutions.
Unlike most other ways of looking at data, link analysis charts are designed to exploit relationships in data. That means they can uncover patterns difficult to detect using traditional representations such as tables.
Now, we all know that there are various types of fraud – first-party, insurance, and e-commerce fraud, for instance. What they all have in common is the layers of dishonesty to hide the crime. In each of these types of fraud, link analysis from Crime Tech Solutions offers a significant opportunity to augment existing methods of fraud detection, making evasion substantially more difficult.
Let’s take a look at first-party fraud. This type of fraud involves criminals who apply for loans or credit cards but who have no intention of ever paying the money back. It’s a serious problem for banks, who lose tens of billions of dollars every year to this form of fraud. It’s hard to detect and the fraudsters are good at impersonating good customers until the moment they do their ‘Bust-Out,’ i.e. cleaning out all their accounts and disappearing.
Another factor is the nature of the relationships between the participants in the fraud ring. While these characteristics make these schemes very damaging, it also renders them especially vulnerable to link analysis methods of fraud detection.
That’s because a first-party fraud ring involves a group of people sharing a subset of legitimate contact information and bogus information, and then combining them to create a number of synthetic identities. With these fake identities, fraudsters open new accounts for new forms of loans.
The fraudsters’ accounts are used in a normal manner with regular purchases and timely payments so that the banks gain confidence and slowly increase credit over time. Then, one day… Poof! The credit cards are maxed out and everyone has disappeared. The fraudsters are long gone and ready to hit the next bank down the road.
Gartner Group believes in a layered model for fraud prevention that starts with simple discrete methods but progresses to more elaborate types of analysis. The final layer, Layer 5, is called “Entity Link Analysis” and is designed to leverage connections in data in order to detect organized fraud.
In other words, Gartner believes that running appropriate entity link analysis queries can help organizations identify probable fraud rings during or even before the fraud occurs.
Tag Archives: ACFCS
Using Link Analysis to untangle fraud webs
Posted by Douglas Wood, Editor.
NOTE: This article originally appeared HERE by Jane Antonio. I think it’s a great read…
Link analysis has become an important technique for discovering hidden relationships involved in healthcare fraud. An excellent online source, FierceHealthPayer:AntiFraud, recently spoke to Vincent Boyd Bryant about the value of this tool for payer special investigations units.
A former biometric scientist for the U.S. Department of Defense, Bryant has 30 years of experience in law enforcement and intelligence analysis. He’s an internationally-experienced investigations and forensics expert who’s worked for a leading health insurer on government business fraud and abuse cases.
How does interactive link analysis help insurers prevent healthcare fraud? Can you share an example of how the tool works?
Boyd Bryant: Link analysis is most often used to piece together different kinds of data from multiple sources–to identify key players, connections between those players and patterns of behavior frequently missed. It can simplify an understanding of the level of involvement of individuals and criminal organizational hierarchies and can greatly simplify visualizing and communicating the operations of complex criminal enterprises.
One thing criminals do best is hide pots of money in different places. As a small criminal operation becomes successful, it will often expand its revenue streams through associated businesses. Link analysis is about trying to figure out where all those different baskets of revenue may be. Insurers are drowning in a sea of theft. Here’s where link analysis becomes beneficial. Once insurers discover a small basket of money lost to a criminal enterprise, then serious research needs to go into finding out who owns the company, who they’re associated with, what kinds of business they’re doing and if there are claims associated with it.
You may find a clinic, for example, connected to and working near a pharmacy, a medical equipment supplier, a home healthcare services provider and a construction company. Diving into those companies and what they do, you find that they’re serving older patients for whom multiple claims from many providers exist. The construction company may be building wheelchair ramps on homes. And you may find that the providers are claiming payment for dead people. Overall, using this tool requires significant curiosity and a willingness to look beyond the obvious.
Any investigation consists of aggregating facts, generating impressions and creating a theory about what happened. Then you work to confirm or disconfirm your theory. It’s important to have tools that let you take large masses of facts and visualize them in ways that cue you to look closer.
Let’s say you investigate a large medical practice and interview “Doctor Jones.” The day after the interview, you learn through link analysis that he transferred $11 million from his primary bank account to the Cayman Islands. And in looking at Dr. Jones’ phone records, you see he called six people, each of whom was the head of another individual practice on whose board Dr. Jones sits. Now the investigation expands, since the timing of those phone calls was contemporaneous to the money taking flight.
Why are tight clusters of similar entities possible indicators of fraud, waste or abuse?
Bryant: When you find a business engaged in dishonest practices and see its different relationships with providers working out of the same building, this gives rise to reasonable suspicion. The case merits a closer look. Examining claims and talking to members served by those companies will give you an indication of how legitimate the operation is.
What are the advantages of link analysis to payer special investigation units, and how are SIUs using its results?
Bryant: Link analysis can define relationships through data insurers haven’t always had, data that traditionally belonged to law enforcement.
Link analysis results in a visual reference that can take many forms: It can look like a family tree, an organizational chart or a time line. This reference helps investigators assess large masses of data for clustering and helps them arrive at a conclusion more rapidly.
Using link analysis, an investigator can dump in large amounts of data–such as patient lists from multiple practices–and see who’s serving the same patient. This can identify those who doctor shop for pain medication, for example. Link analysis can chart where this person was and when, showing the total amount of medication prescribed and giving you an idea of how the person is operating.
What types of data does link analysis integrate?
Bryant: Any type of data that can be sorted and tied together can be loaded into the tool. Examples include telephone records, addresses, vehicle information, corporate records that list individuals serving on boards and banking and financial information. Larger supporting documents can be loaded and linked to the charts, making cases easier to present to a jury.
Linked analysis can pull in data from state government agencies, county tax records or police records from state departments of correction and make those available in one bucket. In most cases, this is more efficient than the hours of labor needed to dig up these types of public records through site visits.
Is there anything else payers should know about link analysis that wasn’t covered in the above questions?
Bryant: The critical thing is remembering that you don’t know what you don’t know. If a provider or member is stealing from the plan in what looks like dribs and drabs, insurers may never discover the true extent of the losses. But if–as a part of any fraud allegation that arises–you look at what and who is associated with the subject of the complaint, what started as a $100,000 questionable claims allegation can expose millions of dollars in inappropriate billings spread across different entities.
Perhaps a nice change at NICE Actimize?
Posted by Douglas Wood, Editor. http://www.linkedin.com/in/dougwood
Though not publicly released, news out of NICE Actimize is that long-time CEO Amir Orad is leaving the company effective May 1. Indicative of the ‘what a small world this is’ nature of the financial crimes technology marketplace, former Pegasystems co-founder and head of Americas for BAE Systems Detica, Joe Friscia, will be taking over the helm at that time.
Mr. Orad led NICE Actimize’s product and strategy functions prior to his five year tenure as CEO. During his tenure, he scaled the business size over six-fold. He is also a founding board member at BillGuard the venture backed personal finance analytics and security mobile app company.
Prior to Actimize, Orad was co-founder and CMO of Cyota a cyber security and payment fraud cloud company protecting over 100 million online users, acquired by RSA Security for $145M. Following the acquisition, he was VP Marketing at RSA.
I’ve known both Amir and Joe for several years, and have a tremendous amount of respect for both gentlemen. While it’s sad to see Amir leave the organization, I know that his rather large shoes will be more than adequately filled by Mr. Friscia.
Joe’s background is well-suited to this new position, and all of us here at FightFinancialCrimes wish him well. Joe joined Detica when BAE Systems acquired Norkom Technologies in early 2011, where he served as General Manager and Executive Vice President of the Americas. Joe led the rapid growth of Norkom in the Americas, with direct responsibility for sales, revenue and profit as well as managing multi-discipline teams based in North America. Prior to Norkom, Joe helped start Pegasystems Inc in 1984, a successful Business Process Management software company that went public in 1996.
Best of luck to Amir in his new ventures, and to Joe as he guides Actimize into it’s next phase.
Part Two: Major Investigation Analytics – Big Data and Smart Data
Posted by Douglas Wood, Editor.
As regular readers of this blog know, I spend a great deal of time writing about the use of technology in the fight against crime – financial and otherwise. In Part One of this series, I overviewed the concept of Major Investigation Analytics and Investigative Case Management.
I also overviewed the major providers of this software technology – Palantir Technologies, Case Closed Software, and Visallo. The latter two recently became strategic partners, in fact.
The major case for major case management (pun intended) was driven home at a recent crime and investigation conference in New York. Full Disclosure: I attended the conference for educational purposes as part of my role at Crime Tech Weekly. Throughout the three day conference, speaker after speaker talked about making sense of data. I think if I’d have heard the term ‘big data’ one more time I’d have gone insane. Nevertheless, that was the topic du jour as you can imagine, and the 3 V’s of big data – volume, variety, and velocity – remain a front and center topic for the vendor community serving the investigation market.
According to one report, 96% of everything we do in life – personal or at work – generates data. That statement probably best sums up how big ‘big data’ is. Unfortunately, there was very little discussion about how big data can help investigate major crimes. There was a lot of talk about analytics, for sure, but there was a noticeable lack of ‘meat on the bone’ when it came to major investigation analytics.
Nobody has ever yelled out “Help, I’ve been attacked. Someone call the big data!”. That’s because big data doesn’t, in and by itself, do anything. Once you can move ‘big data’ into ‘smart data’, however, you have an opportunity to investigate and adjudicate crime. To me, smart data (in the context of investigations) is a subset of an investigator’s ability to:
- Quickly triage a threat (or case) using only those bits of data that are most immediately relevant
- Understand the larger scope of the crime through experience and crime analytics, and
- Manage that case through intelligence-led analytics and investigative case management, data sharing, link exploration, text analytics, and so on.
Connecting the dots, as they say. From an investigation perspective, however, connecting dots can be daunting. In the children’s game, there is a defined starting point and a set of rules. We simply need to follow the instructions and the puzzle is solved. Not so in the world of the investigator. The ‘dots’ are not as easy to find. It can be like looking for a needle in a haystack, but the needle is actually broken into pieces and spread across ten haystacks.
Big data brings those haystacks together, but only smart data finds the needles… and therein lies the true value of major investigation analytics.