Identity Resolution Daily

By Mike Shultz, Infoglide Software CEO

In March 2006, the Communications Fraud Control Association (CFCA) estimated that annual global fraud losses in the telecom sector were between $54 billion and $60 billion, and the losses continue to be substantial. Many types of fraud have been identified, but by far the most prevalent is subscription fraud.

A new subscriber signs up for mobile service using false or stolen identification, with no intention of paying the bill. Since new subscribers are given a grace period of one to three months before the account is shut off, the criminal can make thousands of dollars worth of calls before being detected.

Subscription fraud can be difficult to differentiate from simple bad debt when genuine customers are unable to pay. It’s been estimated that 30% or more of all bad debt is actually subscription fraud.

Different solutions have been tried yet fraud continues to be a problem. One common method is to look for patterns of use that suggest potential fraud, but criminals adapt and learn to probe the limits of these fraud detection systems fairly quickly.

Given the industry’s long history with fraudsters, it seems probable that enough is known about them that they could be spotted at the time they subscribe.  Using similarity searching technology, would-be fraudsters can be vetted against lists of known bad actors. Using multiple public and private data sources, non-obvious relationships can highlight risky individuals, and they can then be asked to submit to a more thorough qualification process.

Identity resolution is already used across multiple industries to solve similar problems. By matching an individual’s attributes with common attributes associated with those committing fraud, the “bad guys” are being detected in areas like lottery fraud, fusion centers, insider trading, and workers’ compensation employer fraud. Part of finding the bad guys is finding hidden relationships, connections that often uncover rings of criminals.

The “birds of a feather” axiom predicts that subscription fraud criminals often share the same types of social networks. Applying identity resolution to subscription fraud problem may be the way to finally solve it.

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By the Infoglide Team

NYTimes Dealbook: Insider Scheme Had Touches of James Bond

“Unlike the Galleon case, where senior officials at corporations passed tips on early earnings estimates to people at the fund, the Goffer case centers on allegations that may sound more familiar to students of the insider trading scandals of 25 years ago — early tips about deals from the people involved in doing them. According to the criminal complaints, Mr. Cutillo passed the information along through a friend, Jason C. Goldfarb, 31, who specialized in workers compensation law at a private firm in Brooklyn and who was also arrested on Thursday.”

Computerworld: Data quality vendors missing the mark, study finds

“One-fifth of respondents felt data quality is a prerequisite to an MDM initiative and wanted to see more vendor offerings integrating those two areas. Hayler says one would expect vendor partnerships between the areas of data quality and MDM, and that is precisely what is currently happening in the industry.”

docinthemachine: Encrypt EHR — Else HIPAA Violations Need Be Reported To Government & Media

“For example, if a physician maintains patient information in a laptop computer containing the unsecured information of more than 500 patients and the laptop is stolen, the physician would be required to notify not only the patients affected by the breach, but would likely need to also notify the DHHS and the media. A medical practice need not report a breach if the patient information has been properly encrypted – because information that is encrypted is not considered ‘unsecure.’”

Initiate Blog: The Brittle Nature of Data Warehouses

“Usually, only a small percentage of the data are ever used. So why bother? The TCO for extracting, copying, converting, transferring, transforming, integrating, propagating, backing-up, loading, and verifying the data skyrockets far beyond its value and injects significant risk and brittleness into the entire ecosystem.”

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[Post from Infoglide] Data Source Disintermediation?

“According to Wikipedia, ‘disintermediation is the removal of intermediaries in a supply chain: ‘cutting out the middleman’… Buyers bypass the middlemen (wholesalers and retailers) in order to buy directly from the manufacturer and thereby pay less.’”

[Jim Harris] OCDQ Blog: The Two Headed Monster of Data Matching

“Data matching is commonly defined as the comparison of two or more records in order to evaluate if they correspond to the same real world entity (i.e. are duplicates) or represent some other data relationship (e.g. a family household). Data matching is commonly plagued by what I refer to as The Two Headed Monster…”

CorpWatch: CorpWatch announces release of the CrocTail application and open CorpWatch API

“CrocTail provides an interface for browsing information about several hundred thousand U.S. publicly traded corporations and their many foreign and domestic subsidiaries. Information from company Securities and Exchange Commission (SEC) filings has been parsed and annotated by CorpWatch to highlight specific corporate accountability issues. CrocTail also serves as a demonstration of the features and data available through the CorpWatch API.”

Vos Is Neias: Washington - TSA Advising Travelers To Book Airline Tickets Using Full Real Names

“While the T.S.A. has announced Aug. 15 as a target date for the airlines to begin asking for each passenger’s full name, gender and date of birth, and has already begun publicizing the program, called Secure Flight, the agency acknowledged that it would go into effect in phases as the airlines update their systems.”

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By Robert Barker, Infoglide Senior VP & Chief Marketing Officer

According to Wikipedia, “disintermediation is the removal of intermediaries in a supply chain: ‘cutting out the middleman’… Buyers bypass the middlemen (wholesalers and retailers) in order to buy directly from the manufacturer and thereby pay less.” Some famous disintermediation examples are:

•    Bookselling (e.g., Amazon’s long-tail marketing of millions of books online)
•    Travel (e.g., Southwest Airlines selling tickets direct to consumers on the web)
•    Computers (e.g., Dell selling computers direct to consumer and businesses over the internet).

Disintermediation was THE hot topic during the dot com boom, but the heady prediction that virtually every industry would be disintermediated has yet to become a reality. Nevertheless, over the past decade or so we’ve all tracked the news as one business model after another is attacked by competitors who seek a way to “disintermediate” a particular sector.

Part of the power of identity resolution solutions derives from the data sources upon which they’re based, and both the quantity and quality of data sources can affect the results. One challenging identity resolution problem we’ve written about that relies on a variety of data sources is insider trading (see Leveraging Identity Resolution Data Sources). Drawing on multiple data internal and external, public and private data sources, identity resolution unwinds multiple degrees of business, friendship, and familial relationships to uncover likely illegal stock market gains.

Now potential disintermediation plays related to data sources are emerging. CrunchBase is a well-known example, offering a free database of technology companies, people, and investors that anyone can edit. San Francisco-based CorpWatch is a non-profit engaged in “investigative research and journalism to expose corporate malfeasance and to advocate for multinational corporate accountability and transparency”. They’ve just announced an API that makes it easier to search SEC data:

“Although the SEC provides a search interface for locating company filings (EDGAR / IDEA), and the subsidiary information is not presented in a standardized format suitable for automated use or insertion into a database. The CorpWatch API uses parsers to “scrape” the subsidiary relationship information from Exhibit 21 of the 10-K filings and provides a well-structured interface for programs to query and process the subsidiary data.”

The free CorpWatch API enables identity resolution and other applications to look up the formal names of corporations, ascertain their relationships to other corporations, find their locations around the world, learn their alternate and formal names, and access other useful information. Up to now, you could only get this kind of information from relatively expensive paid subscriptions from commercial data providers.

Is it possible that the efforts of organizations like CorpWatch point to a future in which an abundance of new, free sources of data will make it even easier to create identity resolution applications?

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By the Infoglide Team

Reuters: Insider trading case sends chill through PR firms

“Most firms Reuters spoke with said they are taking a second look at their policies for handling information considering tighter restrictions on taking documents home and access to computer systems. Most had already sent out policy reminders to their staffers and are consulting their lawyers.”

TCPalm: St. Lucie West worker guilty of workers’ comp fraud

“Concetta Marie Prianti also was ordered to repay more than $37,000 following a referral to the Division of Insurance Fraud by the Florida League of Cities’ Special Investigation Unit.”

Cheapflights.com: TSA Sets Out to Bust Watch List “Myths”

“So how many lists are really out there, and how many people are on each list? TSA says the prevailing myth is that more than one million people are on these ‘lists.’ Not so, insists the government.”

Sacramento Bee: Local investigative firm sees rise in workers’ comp fraud cases

“In California, potential losses to workers’ compensation fraud ran about $223 million in the 2006-2007 fiscal year, according to the state Department of Insurance. ‘The economic situation is kind of bleak,’ said Sudha Rajender, a San Joaquin County deputy district attorney who noted a 25 percent increase in his office’s caseload. ‘Many people are out of work, so they get creative with raising funds.’”

North Country Gazette: Tree Cutter Caught On Tape In Fraud

“Investigators said surveillance showed Stiegler receiving payment of $550 on at least one occasion for cutting trees at a private residence. As a result of his arrest, the potential future savings on Stiegler’s claim was estimated to be $202,813.”

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[Post from Infoglide] #3: If Only Data Quality Were That Simple

“Discovering hidden relationships is a crucial part of a market known by various aliases: entity resolution and analysis, entity analytics, and our favorite of course, identity resolution. Regardless of the name you use, identity resolution problems have distinct characteristics not adequately addressed by existing solutions for data quality (DQ). Neither are they addressed by customer relationship management (CRM), master data management (MDM), or business intelligence (BI).”

Associated Press: SEC: Lehman broker used wife, a Brunswick Group partner, in $4.8M insider trading scheme

“Federal prosecutors in Manhattan and the Securities and Exchange Commission brought the case Thursday against Matthew C. Devlin, who authorities said enabled clients and friends to make millions of dollars while he was rewarded with gifts including cash, a Cartier watch, a widescreen television and tuition at a Porsche driving school. ‘By providing inside information, Devlin curried favor with his friends and business associates and received in return cash, luxury items and other benefits,’ the SEC said in court papers.”

Toronto Star: Lotto winner paid four years later

“According to an OPP press release ‘the manager of a Burlington convenience store allegedly stole a lottery ticket with a winning prize of $80,341.’”

North Country Gazette: Rochester Man Pinched As Comp Cheat

“The state Insurance Department said Tripoli began collecting benefits after suffering a job-related arm and shoulder injury in January 2007. He claimed he could not work because of the injury, but was later discovered working as a painting sub-contractor throughout 2007 and 2008.”

The Desert Sun: Store clerks around county suspected of cheating lottery customers

“During the sting, decoys posing as lottery customers with winning tickets went into different stores and asked the clerks to confirm whether the tickets they had bought were, indeed, winners, according to California Lottery spokesman Alex Traverso.”

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By Robert Barker, Infoglide Senior Vice President & Chief Marketing Officer

Ever have this experience? You’re searching Google for specific examples of a topic when you come across an already compiled and complete list of related examples – what a find! I had this experience recently when looking for contact information for people we wanted to invite to a marketing event, and voila! – I found a list of them that was 90% complete and accurate. Without that find, the project could have taken a couple days longer.

Aggregations of this type abound. Besides lists that individuals put together and post on the web, public and private databases offer all sorts of information on people that are useful in addressing multiple types of business problems and opportunities. Here are a few links to “people data” that you may not be aware of, and there are many more:

CapitalIQ

ChoicePoint

KnowX

NETR Online

PublicRecordFinder

SearchSystems

Who’s Who

Identities contained in multiple databases with varying schemas as well as ambiguous and sometimes missing attributes can be resolved to deliver a clear picture of a person and activities they are involved in. Here’s an example that illustrates how you can draw on multiple data sources to solve a complex problem.

Everyone knows about insider trading, especially with the recent allegations about Mark Cuban. Essentially, someone uses confidential knowledge about a financial transaction to buy or sell stock to their personal advantage.

Many illegal insider stock trades can be readily identified. How? By “similarity searching” across records of stock trades, associated timelines (who knew what and when about the event) and public company financial institution data (e.g., CapitalIQ) then finding hidden relationships using biographical information (e.g., Who’s Who), background screening and residential information (e.g., ChoicePoint), and other public and private sources.

There are many more cases where identity resolution can exploit available data sources to address complex problems. Making sense out of these massive amounts of data by aggregating and sifting through them requires an ability to score the results accurately. Just as importantly, you need to be able to configure the scoring to fit the specific problem, i.e. the solution must be tuned to meet unique requirements.

Solving complex business problems often requires knowing more about who you’re dealing with and their relationships. Vast amounts of data are accessible online via APIs and web services, and they can be incorporated into new kinds of online applications that once were impossible.

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By the Infoglide Team

Blog posts and marketing collateral often confuse identity resolution with data matching. When discussing master data management (MDM) solutions, you sometimes hear the term “identity resolution” applied when simple similarity matching is all that’s being used. That’s like calling a set of spark plugs an engine.

To create an engine that provides the power that MDM solutions need, you have to add five components to leverage great similarity matching algorithms.

First, the engine must orchestrate the actions of those algorithms so they provide confidence levels that define the degree of similarity among ambiguous data. But it also must distinguish relationships between different entities from identities. For example, you may have two records. One is for Mike Smith, 123 Maine Street, and one is for Michael Smithe, 122 Main St. You could reasonably assume these are the same person. But if the records also include date of birth, you could determine that since there is a 22 year difference in age between Mike and Michael, it’s likely that this is a parent-child relationship. So they’re not the same person but there is a relationship.

Second, the engine can enable the discovery of more complex networks of relationships (e.g., insider trading). Tracing relationships through multiple levels can reveal surprising connections, especially where people are working to hide their activities.

Third, these identities and relationship networks become the foundation for enhanced processing within the engine that determines the deeper meaning of the results by employing decisioning and rules processing to suggest - or take - action. So, let’s apply our example of Mike and Michael to the problem of insider trading. If Mike sits on the board of a company that is about to make a major acquisition announcement and Michael purchased stock in the company that is being acquired prior to that announcement, then that’s something that needs to be investigated.

Fourth, the engine needs to flexible. If it’s only targeted to a rigid structure, problem, or domain, making it solve a particular problem could range from expensive to impractical. So the engine needs to allow an organization to tune and adjust it to best meet the needs of that organization and the particular problem they’re solving. It can be targeted at problems ranging from insider trading to master person or master product indices.

Finally, this powerful engine is useless unless it’s easy to harness. The entire engine needs to be available to MDM solutions as a set of services that can be easily incorporated into new and existing business processes.

We’d be the last to say that a strong ability to match similar data isn’t important - yes even critical - to identity resolution. After all, your engine won’t run very long without good spark plugs.

However, MDM solutions that do more than just de-duplicate mailing lists should be supported by a complete identity resolution engine that is much more effective than simple matching algorithms in resolving multiple identities, uncovering hidden relationships, and applying domain specific rules to provide a recommended course of action.

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[Post from Infoglide] California Lottery Fraud

“[N]ow state and provincial authorities are shifting resources to address another rapidly growing problem: lottery fraud committed by retailers. The most highly-publicized case of retailer lottery fraud in recent years occurred in Ontario but cases reported by the California Lottery Commission, perhaps the largest lottery in the U.S., indicate that they have a rapidly growing problem as well.”

Information & Data Quality Conference 2008 Blog: IAIDQ Announces Plans for Certified Information Quality Professional certification

“The IDQ 2008 conference is over (but I’ve a tonne of posts to upload tomorrow sketched out on my laptop). However, one piece of news was announced at this week’s conference which too important to hold until the airport departure lounge….”

Telegraph.co.uk: Standard Life in call for HBOS insider trading probe

“Details of the takeover talks between Lloyds and HBOS were announced by BBC business editor Robert Peston on Wednesday morning at 9am, sending shares soaring from their low of 88p to 215p in an hour. The deal was not formally announced until four hours later. However, in two trades at 8:57am and 8:58pm, two buyers alone acquired more than 20m HBOS shares at 96p. In total, around 160m shares changed hands in the moments before the takeover was announced, making a paper profit of nearly £190m for the traders and leading to suspicion of a leak.”

b-eye.com - Business Intelligence Network - Blog: David Loshin: IDQ 2008 - Initial Observations

“As I am slowly emerging from the cocoon imposed by the needs of getting my new book on Master Data Management out the door, I am able to get back to everyday life, including two of my favorite activities (together!!) - conference attendance and blogging. Anyway, I am currently in San Antonio attending the 2008 Information and Data Quality conference.”

Data Governance and Data Quality Insider: Are There Business Advantages to Poor Data Management?

“However, this got me thinking. Could the inability for the stores to maintain more that 18 months of records actually be a business advantage? How many customers lose the paperwork, or even forget about their road hazard policies and just pay the replacement price? How much additional revenue was this shortcoming actually generating each year?”

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