Identity Resolution Daily

By the Infoglide Team

Long Beach Press-Telegram: 3 more truck firms named in port probe

“In the latest cases, the companies were able to avoid paying overtime, payroll taxes, health insurance and workers’ compensation by labeling their drivers ‘independent contractors’ — a label applied to some 90 percent of truckers in the ports of Long Beach and Los Angeles.”

All Things Data: Master Data Management and the Mid-Market Need

“Basically, the MDM Summit in New York confirmed that the process to implement a Master Data Management initiative is generally the same regardless of whether the organization is a Mid-Market company or a larger enterprise.”

SmartBrief: Homeland Security releases more details on Secure Flight program

“The Department of Homeland Security estimates 99% of passengers will breeze through security next year when federal officials take over the job of screening names provided by the airlines.”

Confessions of a database geek: Updates to the Information Quality Aggregator

“It’s great to see more activity in the data quality arena. Dylan Jones started the Data Quality Pro site, and dropped me a note with some additional blogs to consider. A couple look pretty good!”

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[Post from Infoglide] Identity Resolution at the MDM Summit

“Identity Resolution clearly plays a key role in the MDM space. Many of the conference sessions highlighted how Identity Resolution has become a key ingredient within an overall MDM solution. Without the ability to accurately match and resolve various attributes of an entity or identity, MDM solutions can’t succeed.”

CNN.com: Better air passenger prescreening expected in 2009

“Under the new program, the airlines will be responsible for collecting a passenger’s full name, gender and birth date, as opposed to the current practice of only collecting the passenger’s name. ‘We know that threats to our aviation system persist,’ Chertoff said. ‘Secure Flight will help us better protect the traveling public while creating a more consistent passenger prescreening process, ultimately reducing the number of misidentification issues.’”

B-Eye-Network: Would You Like Fries With That? And Does Cross-Selling Justify Master Data Management?

“The concept of customer data integration into a consolidated master view is appealing because there is the perception that a ‘golden copy’ of customer records enables business benefits that were unachievable in the absence of the ‘360-degree view.’”

Warrington Guardian: Benefit cheat sentenced to 240 hours community service

“Deliberately withholding information that affects your claim is stealing. We have introduced new methods of data matching – and the obvious message to benefit cheats is you will be caught.”

Jill Dyche Blog: Lessons from the SourceMedia MDM Summit

“This only proves my point that MDM’s success is often directly tied to a company’s specific definition of what it should be. Companies should know the problem(s) they’re solving before they acquire MDM.”

CarInsurance.com: Allstate Sues Companies, Alleging Claims Fraud

“Allstate Insurance has sued 13 Florida companies, including auto body shops, tow truck operators, chiropractic clinics and their owners and some policyholders, alleging the group staged at least 17 auto accidents and filed fraudulent claims.”

Evolution of Security: TSA’s Take on the Atlantic Article

“Watch-lists and identity checks are important and effective security measures. We identify dozens of terrorist-related individuals a week and stop No-Flys regularly with our watch-list process.”

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By Ram Anantha, Infoglide Director of Product Management

Master Data Management (MDM) is gaining a lot of traction as evidenced by the number of vendors (SAP, Siperian, D&B/Purisma, Oracle, Initiate Systems, and a host of others) and end customers (such as AIG, Grange Insurance, McGraw-Hill, Merck, Merrill Lynch, and Nationwide) who shared their experiences in deploying MDM solutions at the MDM Summit in New York City this week.

Identity Resolution clearly plays a key role in the MDM space. Many of the conference sessions highlighted how Identity Resolution has become a key ingredient within an overall MDM solution. Without the ability to accurately match and resolve various attributes of an entity or identity, MDM solutions can’t succeed.

Some of the key requirements for MDM Identity Resolution were in evidence at this week’s Summit:

• Strong, flexible customer data matching algorithms must provide a real-time view of customer entity – must handle anomalies, variations, tokenization, etc.
• Tunable algorithms must minimize false positives and false negatives.
• Solutions must permit correction of easy mistakes on the fly, such as values that have been typed in a wrong field (e.g., Social Security Number used for Driver License Number).
• Deployments must handle an unlimited number and size of data sources.
• Matching accuracy must be controlled using attribute weighting.
• Matching decisions should be as automated as much as possible.
• The matching process must be able to leverage external reference data sources.

For you MDM practitioners out there, let us know if this list agrees with your experiences.

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[Post from Infoglide] MDM Needs An Engine, Not Spark Plugs

“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.”

Canada Media Centre: International Data Protection Authorities Call for Action to Protect Children’s Online Privacy

“Young people today are sophisticated users of the Internet, and they use this medium with ease and enthusiasm,” says Jennifer Stoddart, Canada’s Privacy Commissioner. While the opportunities are tremendous, we must ensure that they understand the impact that these technologies can have on their privacy, and provide them with the tools and information they need to make smart decisions.”

B-Eye-Network: Voter Registration and Data Quality (Or Lack Thereof…)

“As a data quality practitioner always seeking ways to communicate the value of data integrity, it is always a pleasure when you wake up in the morning and the Washington Post hands you a juicy data quality-related story.”

The Bunker Blog: Inside LP - Social Network For LP Professionals

“Inside LP is a relatively new social network especially for Loss Prevention Professionals. The site offers networking opportunities, discussion forums, and a community blog.”

B-Eye-Network: Elusive Data Quality

“Even though certain values are known to be incorrect, they nevertheless are what were written when the application was made. And then there is the more widely held case where names are misspelled or street addresses are misspelled. There is a good argument to be made that says that even incorrect entries here should not be corrected.”

Hub Solution Designs: Evan Levy’s Workshop at MDM Summit

“Evan’s session was interesting, with a wealth of examples from his years of real-world MDM experience. I heard some great quotes today.”

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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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By the Infoglide Team

PR-USA.NET: Gartner Reveals Nine Fatal Flaws in Business Intelligence Implementations

“Data quality issues are almost ubiquitous and the impact on BI is significant — people won’t use BI applications that are founded on irrelevant, incomplete or questionable data. To avoid this, firms should establish a process or set of automated controls to identify data quality issues in incoming data and block low-quality data from entering the data warehouse or BI platform.”

Edmonton Journal: ‘Misplaced generosity’ led to fraud

“A former Workers’ Compensation Board case manager who received tens of thousands of dollars in kickbacks is a deeply troubled woman whose “misplaced generosity” led her to overpay claimants more than $1 million, according to a defence report submitted at her sentencing hearing.”

Secrecy News: Intelligence Policy Would Reward Information Sharing

“‘We have taken a critical step toward ensuring that information sharing becomes ingrained in the way the federal government operates,’ said Amb. Thomas McNamara, the ODNI Information Security Environment program manager, in an October 6 news release.”

Retail Technology Blog: Retail theft skyrockets

“The 20th annual retail theft survey found 24 retailers, with more than 19,000 stores, apprehended a record 708,962 shoplifters and dishonest employees in 2007 and recovered more than $150 million in stolen property.”

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[Post from Infoglide] Start Early on Data Quality

“Identity resolution plays a vital role in data quality applications. Applying identity resolution on the front-end can ensure that error-filled and fraudulent identity information is detected and kept from entering production systems.”

Nashua Telegraph: Owners take on workers at issue

“In addition, the business avoided more than $368,000 in worker’s compensation insurance premiums by under-reporting the number of workers they had hired, prosecutors claim.”

Kiplinger Business Resource Center: Government to Take over Screening from Airlines

“Under a program dubbed Secure Flight, the Transportation Security Administration (TSA) will assume responsibility for checking passengers against a watch list of known and suspected terrorists. Currently, that job is performed by the airlines, and each one has its own process.”

CSO Security Leadership: Opposing Forces in a Down Market

“In a tightening economy, history has proven that the risks faced by businesses increase significantly. When times begin to get tough for individuals, many will turn to crime to abate their diminishing financial situations.”

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“A problem well stated is a problem half solved.”
Charles F. Kettering (1876 - 1958)

Have you been wondering how something as big as the sub-prime mortgage fiasco could have not been forecast well before it happened? Ellen Pearlman pondered this while writing in CIOZone about the thoughts of Thomas Redman in his recent book on data quality. Interestingly, Redman wrote that the mortgage crisis “illustrates perfectly how bad or missing data contribute to issues of international importance and the costs and uncertainties that result”, and he wrote it before this past week’s federal intervention.

The data quality predicament in the mortgage arena is one example of a much more ubiquitous problem. Data doubles every 12-18 months, and that includes bad data. Redman estimates that bad data costs as much as 10-20% of revenue. Doesn’t that mean that the earlier in the data life cycle we get a handle on the data quality problem, the lesser the financial impact?

So says Alena Semeshko in a post on ZDNet UK. “I keep wondering how come data quality check still exists as a procedure performed once in a while, rather than as a part of the front-end process? How come most companies start worrying about the quality of your data only when it’s already dirty and in use?”

Identity resolution plays a vital role in data quality applications. Applying identity resolution on the front-end can ensure that error-filled and fraudulent identity information is detected and kept from entering production systems.

How does it work? Take an example of a web application for applicants or new customers. After an online form is completed, the individual’s identity attributes (name, address, etc.) are compared in real-time to a list of known fraudsters to screen out bad guys. The identity info is also similarity searched to discover an already existing master record for that person, and the two can be matched and resolved to one before the data even enters the system.

Redman’s “rule of 10” states that “it costs ten times as much to complete a unit of work when the input data are defective (late, incorrect, missing, etc.) as it does when the input data are perfect.” With bad data just as with software bugs, the earlier they’re found, the more money is saved.

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By the Infoglide Team

CIOZone: What To Do About Bad Data

“The amount of data is doubling every 12 to 18 months—but much of it is inaccurate, incomplete or otherwise flawed. And bad data costs organizations between 10 to 20 percent of revenue. But there are steps CIOs can take to fix the data problem.”

ZDNet: Data Quality - Upstream or Downstream?

“How come most companies start worrying about the quality of your data only when it’s already dirty and in use? How come it doesn’t occur to them that the quality of data needs to be thought through before it’s actually captured? Even at the early stages of data capturing, data quality already plays an important role in the future of the company.”

Star-Ledger: eBay makes bid to oppose limits on online sales

“The big-box retail chains say they are concerned eBay and similar online sales sites offer professional shoplifters a largely anonymous venue for e-fencing their stolen goods. But eBay says brick-and-mortar retailers are using the argument as a ploy to try and stifle competition from online sellers. Coming as it does at the threshold of the holiday shopping season, there is a lot at stake for both sides in this Goliath vs. Goliath battle for the hearts and wallets of American consumers.”

CNW Group: Protecting lottery customers

“Over the past 12 months, OLG has taken significant action toward protecting lottery customers from theft and fraud.”

Your Industry News: Stopgap Bill Includes $101B For DOD Procurement

“The $630 billion-plus stopgap spending bill signed into law by President Bush includes $487.7 billion to fund the Defense Department and more than $40 billion to fund the Homeland Security Department through the end of fiscal 2009.”

Vancouver Sun: The war on retail crime

“Technology is becoming sophisticated enough to recognize when conventional patterns are broken, such as a door that is only entered by employees coming from a certain direction.”

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[Post from Infoglide] See You at the MDM Summit?

“Big Master Data Management (MDM) issues are swirling around these days, not the least of which is the role of identity resolution. We’ve posted multiple times about MDM, customer data integration (CDI), data quality (DQ), and related topics. People sometimes are unsure about the relationship between identity resolution and these areas. Most of the time, they are complementary. Identity resolution can play a critical and unique role in each case.”

TDWI: Master Data Management is Inevitable… So Get Ready

“Eventually master data management will extend beyond customer and product data into broad enterprise use. As this trend wends its way, the challenge for data professionals is to develop a strategy that addresses both isolated pockets of MDM today (for customer and product data) and broader enterprise use tomorrow (as MDM is applied to employee, patient, claim, supplier, and other business entities).”

b-eye.com - Business Intelligence Network - Blog: James Taylor: First Steps To and Beyond Operational Business Intelligence

“This article outlines some steps organizations can take as they move from ‘traditional’ business intelligence (BI) toward operational business intelligence and enterprise decision management.”

The Bunker Blog: Economic Pressures Affect Retailers In Many Ways

“As retailers, under pressure to sell more, relax their security measures on high ticket (high risk) product, the pressure will be on loss prevention professionals to double, even triple, their efforts to protect this merchandise, and therefore the company’s profits.”

Hub Solution Designs: Experts and Analysts Panel Discussion at MDM Summit

“I’m going to be attending the upcoming MDM Summit in New York on Sunday, 10/19/08 through Tuesday, 10/21/08.I’ll be on an ‘Experts and Analysts Panel’, moderated by Jim Ericson, Editorial Director of DM Review, along with Jill Dyché, Partner & Co-Founder of Baseline Consulting and Aaron Zornes, Chief Research Officer of The MDM Institute.”

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