Tag Archives: crime investigation software

Crime Mapping. More than Law Enforcement?

Posted by Crime Tech Solutions
Geographic information systems aren’t exactly new. Drugstore chain Walgreens has used the technology for close to 15 years for market planning.
More recently, however, the company has endowed that visual information with location-specific data—and published far more broadly, so that store managers and its corporate real estate team can use it for planning.
The system, called WalMap, can be used to visualize local community trends. A spike in flu medication prescriptions could help store managers decide earlier to order more vaccine, preventing shortages. Walgreens sales executives can reference trends in supplier conversations. Plus, the interactive maps can be used by the corporate planning team to determine the best place for a new store, based on community demographics, competitor information, and sales trend information. They can even be viewed on an iPad.
“Ten years, our teams had to print out a map and take it with them. Now they can bring their mobile device, and have access to updated sales, demographics and other targeted information,” said Jillian Elder, director of enterprise location intelligence for Walgreens.

Occasionally the maps serve a higher purpose. Managers in Texas in September were able to help local authorities predict the next targets for a local crime spree. “With some of our visualizations, we were able to put a stop to this,” Elder said.

The resource houses millions of maps available to companies that want to overlay proprietary data with the most up-to-data public information about specific locations. There are literally millions of maps published there. Most internal teams have access to basic information; Elder’s team created a special addition specifically for Walgreens’ real estate, strategy, and mergers and acquisition teams.
As of the latest FAQ information on its corporate web site, Walgreens generated more than $76 billion in sales last year across more than 8,300 locations across the United States and Puerto Rico.

LexisNexis® Acquires BAIR Analytics, Leading Provider of Crime Analytics Solutions for Public Safety

WASHINGTON, DC and ATLANTA (January 6, 2015) – LexisNexis® Risk Solutions today announced its intent to acquire BAIR Analytics, a provider of analytics solutions for public safety.  LexisNexis is acquiring BAIR Analytics to better provide the public safety community with comprehensive investigative solutions that aid them in their law enforcement mission.  BAIR Analytics deploys strong technology, robust analytics, mapping, and visual tools to identify and predict patterns of crime.  The transaction is subject to regulatory review.
“The acquisition of BAIR Analytics builds on LexisNexis’ commitment to public safety, providing us the ability to combine BAIR Analytic’s analytical capabilities with our public records and linking technology to add context to crime patterns and enhance our ability to identify and locate persons of interest,” said Haywood Talcove, chief executive officer, LexisNexis Special Services, Inc.  “The acquisition will be unique in the industry and help public safety officers make better decisions to close cases faster and improve community safety.  In an era of constrained budgets, analytics are essential to optimize limited resources and increase overall efficiencies.”
BAIR Analytic’s analytical tools have been used by large and small public safety organizations worldwide for more than 20 years to help reduce and prevent criminal activity.
“Becoming part of LexisNexis will bring new opportunities to expand and build the best possible solutions to help our public safety customers,” said Sean Bair, President, BAIR Analytics.   “BAIR Analytic’s ability to help agencies identify, analyze and resolve problems created by criminal offenders will be an exceptional complement to LexisNexis, its proven solutions and vast public records database to offer a more complete view of individuals to accelerate the investigation process.”
About LexisNexis Risk Solutions
LexisNexis Risk Solutions (http://www.lexisnexis.com/risk) is a leader in providing essential information that helps customers across all industries and government assess, predict and manage risk.  Combining cutting-edge technology, unique data and advanced analytics, LexisNexis Risk Solutions provides products and services that address evolving client needs in the risk sector while upholding the highest standards of security and privacy.  LexisNexis Risk Solutions is part of Reed Elsevier, a world leading provider of professional information solutions.
BAIR Analytics

Established in 1997, BAIR Analytics (http://www.bairanalytics.com) is an analytical software and services company providing innovative tools and subject-matter expertise for public safety, private security, and national security and defense entities. Nearly half of the largest public-safety agencies in the United States use BAIR Analytic’s products & services to fight crime.  BAIR Analytic’s current software tools are utilized by police departments, government agencies, and throughout the private sector worldwide to increase and promote smarter, community-oriented preventative policing.
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Media Contact

Stephen Loudermilk
LexisNexis Risk Solutions
678.694.2353
stephen.loudermilk@lexisnexis.com

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.

Asking data questions

Posted by Douglas Wood, Editor.  http://www.linkedin.com/in/dougwood.
A brief read and good perspective from my friend Chris Westphal of Raytheon. The article is by Anna Forrester of ExecutiveGov.com.
Federal managers should invest in technology that would help them extract insights from data and base their investment decision on the specific problems and information they want to learn and solve, Federal Times reported Friday.
Rutrell Yasin writes that the above managers should follow three steps as they seek to compress the high volume of data their agencies encounter in daily tasks and to derive value from them.
According to Shawn Kingsberry, chief information officer for the Recovery Accountability and Transparency Board, federal managers should first determine the questions they need to ask of data then create a profile for the customer or target audience.
Next, they should locate the data and their sources then correspond with those sources to determine quality of data, the report said. “Managers need to know if the data is in a federal system of records that gives the agency terms of use or is it public data,” writes Yasin.
Finally, they should consider the potential impact of the data, the insights and resulting technology investments on the agency.
Yasin reports that the Recovery Accountability and Transparency Board uses data analytics tools from Microsoft, SAP and SAS and link analysis tools from Palantir Technologies.
According to Chris Westphal, director of analytics technology at Raytheon, organizations should invest in a platform that gathers data from separate sources into a single data repository with analytics tools.
Yasin adds that agencies should also appoint a chief data officer and data scientists or architects to assist the CIO and CISO on these areas.

Part 2: Investigating the Investigations – X Marks the Spot

Posted by Douglas Wood, Editor.  http://www.linkedin.com/in/dougwood
Part One of this series is HERE.
Most of the financial crimes investigators I know live in a world where they dream of moving things from their Inbox to their Outbox. Oh, like everyone else, they also dream about winning the lottery, flying without wings, and being naked in public. But in terms of the important roles they perform within both public and private sectors, there is simply Investigating (Inbox) and Adjudication (Outbox). Getting there requires a unique blend of their own capabilities, the availability of data, and the technology that allows them to operate. In the diagram below, ‘X‘ marks the spot where crimes are moved from the Inbox to the Outbox. Without any of those three components, an investigation becomes exponentially more difficult to conclude.
Presentation1
In part one of this article two weeks ago, I wrote about the Investigation Management & Adjudication (IMA) side of financial crimes investigations. I coined that term to call out what is arguably the most integral component of any enterprise fraud management (EFM) ecosystem. The original EFM overview is here.

   “The job is almost unrecognizable to those who once used rotary phones in smoke filled offices…

Twenty years ago, IMA was based primarily upon human eyes. Yes, there were technology tools available such as Wordperfect charts and Lotus 1-2-3 spreadsheets, but ultimately it was the investigator who was tasked with finding interesting connections across an array of data elements including handwritten briefs, telephone bills, lists of suspect information, and discussions with other investigators. The job got done, though. Things moved from the Inbox to the Outbox, arrests were made and prosecutions were successful. Kudos, therefore, to all of the investigators who worked in this environment.
Fast forward to today, and the investigator’s world is dramatically different. The job is the same, of course, but the tools and mass availability of data has made the job almost unrecognizable to those who once used rotary phones in smoke filled offices. Organizations began building enterprise data warehouses designed to provide a single version of the truth. Identity Resolution technology was implemented to help investigators recognize similarities between entities in that data warehouse. And today, powerful new IMA tools are allowing easy ingestion of that data, improved methods for securely sharing across jurisdictions, automated link discovery, non-obvious relationship detection, and interactive visualization tools, and -importantly – packaged e-briefs which can be understood and used by law enforcement, prosecutors, or adjudication experts.

     “Without any of these components, everything risks falling to the outhouse…

With all these new technologies, surely the job of the Investigator is becoming easier? Not so fast.
IMA tools – and other EFM tools – do nothing by themselves. The data – big data – does nothing by itself. It just sits there. The best investigators – without tools or data – are rendered impotent.  Only the combination of skilled, trained investigators using the best IMA tools to analyze the most useful data available results in moving things from the Inbox to the Outbox. Without any of these components… everything eventually risks falling to the Outhouse.
Kudos again, Mr. and Mrs. Investigator. You’ll always be at the heart of every investigation. Here’s hoping you solve for X every day.

To 314(b) or not to 314(b)?

Posted by Douglas Wood, Editor.  http://www.linkedin.com/in/dougwood
FinCEN today (November 1, 2013) released a fact sheet regarding data sharing between financial institutions under the Section 314(b) of the US Patriot Act.
314(b) provides financial institutions with the ability to share information with one another, under a safe harbor that offers protections from liability, in order to better identify and report potential money laundering or terrorist activities.  314(b) information sharing is a voluntary program, and FinCEN has always encouraged its use.
A few years ago, I spent considerable time looking at the overall 314(b) program. I interviewed dozens of Chief Compliance Officers (CCO) and AML/Fraud experts. I found that, despite the benefits to financial institutions – reduction of fraud loss, more complete SARs filings, shedding light on financial trails, etc – the program was not particularly well-utilized. The system, for all it’s good intentions, is very manual.
Imagine you are a 314(b) officer at a financial institution. Your job is to facilitate the data sharing amongst the community. So, much of your time is spent interacting with your CCO on which specific cases should be shared, and with whom. When you get that information, you open up you financial crimes investigation tools, and begin contacting your counterparts across the U.S. and asking them “Hey, do you know anything about Douglas Wood?” You’re calling the other officers completely blind with no idea whatsoever if they know Doug. In the meantime, your voicemail inbox is being flooded with other calls from other institutions asking if you know a bunch of other people (or entities).
Finding the institutions that know Douglas Wood is a lot like looking for a needle in a haystack… except you don’t know which haystacks to look in. The system too often grinds to a halt, despite some excellent work being done by 314(b) officers across the country. There has to be a better way, and some have proposed a data contribution system where financial institutions upload their bad guy data into one large third-party haystack, making the needle a little easier to find. As an advocate for the use of technology in the fight against financial crimes, I hope that model finds some success. The problem, of course, is that banks are LOATHED to put their data in the hands of a third party. Also, it’s typically up to each individual bank to decide if and when they choose to upload their data to be inter-mingled with other institutions. Far too often, it is not entirely reliable and not particularly current.
There is a better way. Several years ago, working with some tech-savvy employees, I envisioned a member-based 314(b) program where each institution maintained total control of their data. The model does not require individual banks to contribute their data for inter-mingling.  All ‘bad guy’ data sits and remains securely behind the banks’ respective firewalls. When an individual bank sends out a request to find out who, if anyone, may have information about a suspicious entity, the request is systematically sent out to all members using a secure network such as SWIFT, for example. That electronic search returns to the querying bank only a risk score which indicates the likelihood that another member is investigating the same entity.
No personally identifiable information (PII) is ever shared, yet the search is productive. The enquiring bank now knows that the person of interest was found in the bad guy data from other participating institutions. With this information in hand, the respective 314(b) officers can move their voicemail exchanges from “Have you ever heard of Douglas Wood” to “We’re both investigating Douglas Wood… let’s do it together.” The time-consuming, manual efforts are dramatically reduced and more bad guys are put away.
So if the question is to 314(b) or not to 314(b), perhaps the answer lies in data privacy compliant technology.