“Today, everything seems to be moving into the cloud. In 2005, investment in cloud computing was about $26 million. But in 2009, the investment grew to $370 million, more than 10 times of what was invested in 2005.”
“Some of the nation’s largest banks are exiting or scaling back their dealings with foreign embassies and missions in the U.S. because of the burden of complying with money-laundering regulations… ‘It’s a commercial decision, but clearly it has ramifications for diplomatic relations,’ said Mark Toner, acting deputy spokesman for the State Department. ‘We want these foreign missions to be able to carry out their normal diplomatic functions here in the U.S.’”
“There are an estimated 50 million patient records, with 20 to 200 records per patient, resulting in billions of individual pieces of information, all of which need entity resolution: in other words, which records belong to her, him or somebody else.”
“International companies, particularly those in the financial services markets, have long struggled to comply with the varying data privacy laws of the countries in which they operate. Simple data analysis practices in one region of the world may or may not be acceptable in another, and the penalties of non-compliance can be harsh to say the least. This leads to inefficiencies in areas such as AML, Compliance and Fraud Investigation.”
“Despite their alleged lack of medical licenses, authorities say, the trio treated thousands of disabled and low-income patients, helping Masood bilk at least $1.8 million from Medicaid, the federally funded health care program for the poor. ‘Unsuspecting patients were placed at risk through deceit and substandard medical care, while taxpayers were being defrauded of millions of dollars,’ said Michael B. Ward, head of the FBI’s Newark office.”
“The specific initial recipients of the new automated service were identified as the TSA’s Office of Transportation Threat Assessment and Credentialing; the TSA Secure Flight Program; CBP’s Passenger Systems Program Office for inclusion in the Traveler Enforcement Compliance System; and US-VISIT for inclusion into the DHS Automated Biometric Identification System (IDENT).”
“‘There are so many databases out there, officers want to be able to get into one portal for information,” Romley said. “Technology capabilities have improved immensely over the years, the real future is in databases when it comes to helping solve crimes quicker. Everyone knows the value of having an intelligence sharing system. the meeting was a baby step, but a monumental step forward.’ One example Romley cited was the East Valley Gang and Criminal Fusion Center that consists of law enforcement agencies throughout the East Valley such as the Mesa, Tempe, Chandler, Gilbert and Scottsdale police departments sharing information through having all of their police reports in a database for investigative purposes.”
International companies, particularly those in the financial services markets, have long struggled to comply with the varying data privacy laws of the countries in which they operate. Simple data analysis practices in one region of the world may or may not be acceptable in another, and the penalties of non-compliance can be harsh to say the least. This leads to inefficiencies in areas such as AML, Compliance and Fraud Investigation.
For most companies, the data to identify and catch fraudsters already exists within the organization; however, because data is distributed across various data silos in different countries, resolving identities and non-obvious relationships requires rapidly accessing multiple data sources with different structures and access methods.
Consider then the requirement to comply with data privacy laws, which make it essential that the analyst returns only the calculated probability of a match in a foreign database, instead of the actual data associated with that match. Businesses have spent massive amounts of money trying to tip-toe through the minefield of privacy laws and acceptable practices. Determining “who’s who” and “who’s working with whom” has proven difficult where data privacy laws prohibit individual analysts from ‘seeing’ the results of a search into a database in another country.
Infoglide’s Identity Resolution Engine is uniquely capable of solving these requirements by searching into disparate data – irrespective of where it resides – and returning only the percentage likelihood that a match or relationship was found. The software then returns contact information of the appropriate data steward, if desired.
Taking the weight of data privacy concerns off analysts increases productivity and helps them focus on the cases that truly matter to your organization. For more information, contact sales@infoglide.com.
If you’re involved in fraud detection, then you’re probably aware of ACFE, the Association of Certified Fraud Examiners. With over 50,000 members, it’s the largest single fraud anti-fraud organization in the world. ACFE is also the publisher of FRAUD magazine.
The conference is geared to address the challenges faced by anti-fraud professionals, featuring top-level educational sessions and providing a great forum for participants to network with colleagues. Join us in Washington, D.C. and experience for yourself why this is the most important event for anti-fraud professionals.
If you would like to schedule some time to meet with Infoglide representatives, please contact us at sales@infoglide.com.
“Department of Homeland Security (DHS) Secretary Janet Napolitano today announced that 100 percent of passengers traveling within the United States and its territories are now being checked against terrorist watchlists through the Transportation Security Administration’s (TSA) Secure Flight program—a major step in fulfilling a key 9/11 Commission recommendation.”
“The center, which is housed in the FBI’s Fort Myers office near Gateway, is designed to digest and compare data from across the region. Once complete, Storrar said the center will help local officials bridge jurisdictional, historical and technological barriers. It will help law enforcement, fire and health officials look for red flags, connect dots and provide threat assessments, Storrar said.”
“In the case of Teodoro Nguema Obiang Mangue, the son of the president of Equatorial Guinea, the report said two lawyers helped him bypass anti-money-laundering laws by allowing him to use shell company accounts as conduits for his funds without telling U.S. bankers that Obiang was using the accounts. ‘If a bank later uncovered Mr. Obiang’s use of an account and closed it, the lawyers helped him set up another,’ it said.”
“Officials said health care providers at the centers who demonstrate ‘meaningful use’ of EHRs could be eligible for federal incentive payments through Medicaid and Medicare.”
“In the last few posts, we reviewed the basic architectures used to implement entity resolution (ER) systems. Although this gives us the big picture at the systems level, ER really takes place at the reference (record) level where the system must ultimately decide whether two references are for the same or for different real-world objects, i.e. to link or not to link. In this series I’ll discuss some of the most common methods for making these linking decisions.”
“NYAAIF noted that the New York-based Insurance Information Institute reported that fraud and abuse in the New York no-fault system accounts for roughly 20 percent of every no-fault claim paid—or about $1,561 per claim. Spread across the state, that amounted to nearly $230 million in ‘fraud taxes’ in 2009, according to the Alliance.”
Three states (Wyoming, Nevada and Delaware) do not require any proof of identification to set up a business. Another 26 states allow a limited liability corporation (LLC) to be set up without showing beneficial ownership. ‘When banks try to cross-reference within their own business customers, they’ll find the connection,’ she says. ‘But when they distribute it across several banks, it’s not clearly visible. It’s hard to do pattern relationships because banks don’t compare notes, so that’s how [the fraudsters] dilute and avoid detection.’”
“The Secure Flightwatch-list matching process occurs before a passenger even gets to the airport so if you get a boarding pass, the Secure Flight matching process is done. In other words, you are clear once you get that pass.”
The accepted meaning of “multi-factor authentication” is employing at least two of the three standard factors used to authenticate identities:
something the user knows (e.g. , PIN or password)
something the user has (e.g., ATM or smart card)
something the user is (e.g., biometric such as fingerprint)
Building upon this well understood concept in the banking and financial services world, I’d like to describe how identity resolution technology extends and greatly enhances the value of authentication systems to the enterprise.
A tacit assumption of multi-factor authentication is that the user mentioned above is legitimate: how else could he or she have the password, smart card, or biometric data? While this assumption may be enough to protect against stolen cards, it doesn’t guard against the user who finds a way to open an account through legitimate means with the intent to defraud. Let me explain.
Billions of dollars are laundered through banks and other financial institutions each year. Accounts (and account owners) that appear legitimate to the institution often move money into and out of the financial system undetected by various means, including trade-based money laundering. Presumably this activity happens despite the presence of authentication measures.
To catch the perpetrators, institutions often focus on improving data quality, either through simple measures like de-duplication or more sophisticated master data management systems. We’ve talked many times here about how these “data quality” efforts can actually harm the process of identifying multiple identities and hidden relationships held by bad actors.
Consider instead the benefits of of integrating authentication systems with high-powered identity resolution systems tied to multiple data sources. Existing multiple identities and hidden relationships become another layer of authentication and incorporate fraud identification into the process. If Joe Blow has multiple related identities, for example, the system can pose a question during authentication drawn from one of the identities that would validate whether the user was legitimate.
Food for thought, and we’d like to hear your thoughts!
Who’d have thought that iTunes could be used for money laundering? Yet that is exactly what five men in Great Britain were recently jailed for the other day. Using stolen credit card numbers, they bought £750,000 in vouchers, then sold them at cheaper prices over eBay.
Methods of money laundering continue to evolve. When authorities constrain certain types of money laundering, perpetrators migrate to other methods. Since law enforcement has focused its efforts on two methods – (1) the movement of value through the financial system using checks and wire transfers, and (2) the physical movement of banknotes via cash couriers and bulk cash smuggling – a third method called “trade-based” money laundering is growing in popularity.
Trade-based money laundering is defined by the Financial Action Task Force (FATF) as “the process of disguising the proceeds of crime and moving value through the use of trade transactions in an attempt to legitimize their illicit origins.” Kenneth Rijock, Financial Crime Consultant for international anti-money laundering risk intelligence firm World-Check, recently commented that disguising funds as goods is now the way a significant portion most of laundered money is moved illicitly. “If I can move $100 million from New York to Columbia via Venezuela, I’m certainly not going to smuggle it down there when I can move it through trade-based money laundering.”
The newly revised Bank Secrecy Act and Anti-Money Laundering Examination Manual contains an expanded section on trade-based money laundering. These operations are successful because of the difficulty in detecting complex relationships between trading operations, operators, and money movements. Three key barriers make it tough to detect trade-based money laundering:
1. The tremendous volume of trade makes it easy to hide individual transactions;
2. The complexity that is often involved in multiple foreign exchange transactions; and
3. The limited resources available to agencies wanting to detect the fraud.
These barriers are difficult if not impossible for traditional methods to address. The volume of trade means that highly scalable automated methods are needed, but the complexity of sifting through multiple transactions and finding hidden connections is beyond the capabilities of normal methods.
For those familiar with identity resolution (e.g., Identity Resolution Engine [IRE]) technology, its strengths address these barriers directly:
Volume - IRE can process millions upon millions of transactions daily in the largest and most demading application environments.
Complexity - Non Obvious Relationship Analysis finds hidden relationships, or neural networks,across multiple disparate and remote data sources, including both internal and external data.
Resources - Configurable, automated processes optimize the use of available human resources by eliminating “clean” transactions and prioritizing potential “dirty” ones.
The hottest non-fiction book at the moment is The Big Short: Inside the Doomsday Machine. Best-selling author Michael Lewis explores and explains what went on behind the scenes during the years leading up to the big stock market crash in 2008 and answers a crucial question: “Who understood the risk inherent in the assumption of ever-rising real estate prices, a risk compounded daily by the creation of those arcane, artificial securities loosely base on piles of doubtful mortgages?” While misguided government policies together with greed and stupidity provide the larger answer, events during that time beg certain questions about the specific ways in which credit risk is evaluated.
For decades, several well-known organizations have assessed credit risk, i.e. the likelihood that a loan applicant will default on a loan. Financial services organizations like banks, credit card companies, and mortgage lenders base decisions to lend on credit scores like FICO. The scores are based primarily on a person’s financial history, including whether they have taken out loans and paid them back. Two major trends work together to hinder the effectiveness of traditional credit scores.
First, the use of credit cards as a form of payment has become ubiquitous, and a large percentage of people carry a balance from month to month. For example, according to creditcards.com the average credit card debt per household carrying a balance is over $16,000. It’s clear that an ever-increasing number of households depend on credit cards to manage cash flow.
The second trend is a behavioral one. For many years, past loan history was a reasonable predictor of future behavior. People in general were committed to paying off their mortgage, and if they were in a tight cash flow situation, their highest priority was keeping up their mortgage payments. Now, with zero interest down and interest-only loans, the lack of equity in the home translates to lower commitment, and defaulting on a loan is a less traumatic event. When credit cards are used for cash management and the penalty for mortgage foreclosure is not so high, it’s not hard to predict a much higher rate of foreclosures.
So, if past behavior is less predictive than before, expect a growing desire in the industry for more sophisticated measures that draw on both historical data and other sources, e.g. up-to-the-minute income and banking status. With its ability to combine and score disparate data, identity resolution technology is certain to play a key role in improving the financial industry’s ability to assess risk.
“Jeff Jonas of IBM recently quoted from a chapter called “Data Finds Data” that he co-wrote for a book entitled Beautiful Data: The Stories Behind Elegant Data Solutions, and I was impressed by how well this passage describes the effective use of entity resolution software (e.g., IRE 2.2)…”
[Philip Howard]”If you think about these different forms of risk, they can mostly be managed within existing GRC frameworks: business risk, data and IT governance and compliance cover five of these seven types of risk. But they don’t cover fraud or cyber attacks or similar security issues.”
“Investigators with the state’s Division of Insurance Fraud said Robert McDonald, owner of Gulfstream Roofing Inc., funneled $3 million in payroll through several fake companies between 2002 and 2006, claiming the money was being paid to insured subcontractors instead of his own workers.”
“The three countries also use universal patient identification numbers in health care. This is much easier to do in Europe than it is in the U.S., where the mistrust of government is so high that the issue of having a single patient identifier number is no longer even under discussion. There’s also the small matter of our low EHR adoption rate, which is less than 20 percent for physicians and lower for hospitals. By contrast, most physicians in the three European countries are using some kind of EHR.”
Infoglide Software provides entity resolution and analysis solutions for retail, banking, insurance, government, and law enforcement. Without the need for data cleansing or warehousing, Infoglide Software's Identity Resolution Engine™ (IRE) analyzes all of the information relating to individuals and/or entities from multiple sources of data and then applies...
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