Data & Analytics

A recent Experian study on data insights found that 83% of chief information officers see data as a valuable asset that is not being fully exploited within their organization, resulting in the need for more organizations to appoint a dedicated chief data officer (CDO).

Data migrations are very common in today’s business environment. A recent Experian Data Quality study found that while 91% of businesses engage in data migrations, 85% encounter significant challenges.

Data quality continues to be a challenge for many organizations.

By: Barbara Rivera Every day, 2.5 quintillion bytes of data are created – in fact, 90% of the world’s data was created in only the last few years. With the staggering amount of data available, we have an unprecedented opportunity to uncover new insights and improve the way our world functions. The implications of these new capabilities are perhaps nowhere else as crucial as within our government. Public sector officials carry the great responsibility of conducting complex missions that directly affect our communities, our economy, and our nation’s future. The ability to make more informed, insightful choices and better decisions is paramount. Especially at a time of broader global unrest and uncertainty, Americans rely on our government to be transparent, fair, ready and to make the right decisions – our trust is in the hands of our elected officials and public servants. Data alone is not enough to inform and affect change. However, with integrated information assets, insightful analysts and collaborative processes, data can be transformed into something meaningful and actionable. Our government has already begun leveraging data for good across agencies and varied missions, with more potential unlocked each day. Local governments like Orange County, California are utilizing data through address verification services to keep their voting lists accurate – ensuring the integrity of elections and saving the taxpayers thousands of dollars otherwise wasted on mailings to outdated lists. The Orange County Registrar of Voters – the fifth largest voting jurisdiction in the county – has been able to cancel 40,000 voting records, with an estimated savings of $94,000 expected from 2012 through 2016. The examples are numerous and growing: A suite of optimization tools helps states find non-custodial parents, determine their capacity and likelihood to pay child support, and trigger alerts with new critical information, maximizing the likelihood of payment and recovery, ultimately improving the welfare of children and reducing poverty More than 150 state, county and local law enforcement agencies leverage data to help identify persons of interest, conduct background screening for employees and contractors and provide financial backgrounds for criminal investigations, ensuring our continued safety By using the power of data to manage user authentication, credentials and access controls, the government is working harder – and smarter – to protect our security The government is leveraging verified commercial data to help agencies validate the fiscal responsibility of potential contractors and monitor existing contractors, which helps provide transparency and reduce risk By using data and analytics to authenticate applicants and validate financial data, the government is ensuring access to benefits for those who meet eligibility requirements, while at the same time reducing fraud Private sector partners are supporting municipal efforts to improve financial stability in households by providing the current credit standing of consumers and monitoring overall changes in financial behaviors over time, to help counsel and educate citizens And that’s only the beginning. The possibilities are endless – from healthcare to finance to energy – data can be leveraged for the advancement of our society. It even happens behind the scenes, working to protect information in ways most citizens never realize. Data insights are used to ensure citizens have secure online access to their information – ever see those randomized, personal questions? That’s data at work. The same technology is the de facto ID Proofing standard for the VA and CMS. How does it all work? By combing through the data carefully, putting it in context, looking at it in new ways, and thinking about what all this information really means. Much of this is made possible through public-private partnerships between the government and companies like Experian. So the next time someone complains about the slow pace of government, let them know the truth is government is moving quickly, leveraging data and private sector partnerships to uncover new insights that impact the greater good.

This is the third post in a three-part series. Experian® is not a doctor. We don’t even play one on TV. However, because of our unique business model and experience with a large number of data providers, we do know data governance. It is a part of our corporate DNA. Our experiences across our many client relationships give us unique insight into client needs and appropriate best practices. Note the qualifier — appropriate. Just as every patient is different in his or her genetic predispositions and lifestyle influences,  every institution is somewhat unique and does not have a similar business model or history. Nor does every institution have the same issues with data governance. Some institutions have stabile growth in a defined footprint and a history of conservative audit procedures. Others have grown quickly through aggressive acquisition marketing plans and unique channels and via institution acquisition/merger, leading to multiple receivable systems and data acquisition and retention platforms. Experian has provided valuable services to both environments many times throughout the years. As the regulatory landscape has evolved, lenders/service providers demand a higher level of hands-on experience and regulatory-facing credibility. Most recently, lenders have required assistance on the issues driven by mandates coming from the Comprehensive Capital Analysis and Review (CCAR), Office of the Comptroller of the Currency (OCC) and the Consumer Financial Protection Bureau (CFPB) bulletins and guidelines. Lenders are best served to begin their internal review of their data governance controls with a detailed individual attribute audit and documentation of findings. We have seen these reviews covering  fewer than 200 attributes to as many as more than 1,000 attributes. Again, the lender/provider size, analytic sophistication and legacy growth and IT issues will influence this scope. The source and definition of the attribute and any calculation routines should be fully documented. The life cycle stage of attribute acquisition and usage also is identified, and the fair lending implication regarding the use of the attribute across the life cycle needs to be considered and documented. As part of this comprehensive documentation, variances in intended definition and subsequent design and deployment are to be identified and corrective action guidance must be considered and documented for follow-up. Simultaneously, an assessment of the current risk governance policies, processes and documentation typically is undertaken. A third party frequently is leveraged in this review to ensure an objective perspective is maintained. This initiative usually is a series of exploratory reviews and a process and procedures assessment with the appropriate management team, risk teams, attribute design and development personnel, and finally business and end-user teams, as necessary. From these interviews and the review of available attribute-level documentation, documents depicting findings and best practices gap analysis are produced to clarify the findings and provide a hierarchy of need to guide the organization’s next steps: A more recent evolution in this data integrity ecosystem is the implication of leveraging a third party to house and manipulate data within client specifications. When data is collected or processed in “the cloud,” consistent data definitions are needed to maintain data integrity and to limit operational costs related to data cleansing and cloud resource consumption. Maintaining the quality of customer personal data is a critical compliance and privacy principle. Another challenge is that of maintaining cloud-stored data in synchronization with on-premises copies of the same data. Delegation to a third party does not discharge the organization from managing risk and compliance or from having to prove compliance to the appropriate authorities. In summary, a lender/service provider must ensure it has developed a rigorous data governance ecosystem for all internal and external processes supporting data acquisition, retention, manipulation and utilization: A secure infrastructure includes both physical and system-level access and control. Systemic audit and reporting are a must for basic compliance standards. If data becomes corrupted, alternative storage, backup or other mechanisms should be available to protect the information. Comprehensive documentation must be developed to reveal the event, the causes and the corrective actions. Data persistence may have multiple meanings. It is imperative that the institution documents the data definition. Changes to the data must be documented and frequently will lead to the creation of a new data attribute meeting the newer definition to ensure that usage in models and analytics is communicated clearly. Issues of data persistence also include making backups and maintaining multiple archive copies. Periodic audits must validate that data and usage conform to relevant laws, regulations, standards and industry best practices. Full audit details, files used and reports generated must be maintained for inspection. Periodic reporting of audit results up to the board level is recommended. Documentation of action plans and follow-up results is necessary to disclose implementation of adequate controls. In the event of lost or stolen data, appropriate response plans and escalation paths should be in place for critical incidents. Throughout this blog series, we have discussed the issues of risk and benefits from an institution’s data governance ecosystem. The external demands show no sign of abating. The regulators are not looking for areas to reduce their oversight. The institutional benefits of an effective data governance program are significant. Discover how a proven partner with rich experience in data governance, such as Experian, can provide the support your company needs to ensure a rigorous data governance ecosystem. Do more than comply. Succeed with an effective data governance program.

Data quality continues to be a challenge for many organizations as they look to improve efficiency and customer interaction.

As part of its guidance, the Office of the Comptroller of the Currency recommends that lenders perform regular validations of their credit score models in order to assess model performance.

Using a risk model based on older data can result in reduced predictive power.

By: Maria Moynihan Crime prevention and awareness techniques are changing and data, analytics and use of technology is making a difference. While law enforcement departments continue to face issues related to data - ranging from working with outdated information, inability to share data across departments, and difficulty in collapsing data for analysis -  a new trend is emerging where agencies are leveraging outside data sources and analytic expertise to better report on crimes, collapse information, predict patterns of behavior and ultimately locate criminals. One best practice being implemented by law enforcement agencies is to skip trace an individual much like a debt collector would.   Techniques involve using historic address information and individual connections to better track to a person’s current location. See the full write up from CollectionsandCreditRisk.com to see how this works. Another great example of effective use of data in investigations can be seen in this video, where one Experian client, Intellaegis of El Dorado Hills, CA, recently worked with local law enforcement to follow the digital data footprints of a particular suspect, finding her in in just five minutes of searching. p> And, yet another representation of improved data gathering, handling and sharing of information for crime prevention and awareness can be found on a site I was just made aware of by one of my neighbors - www.crimemapping.com. Information is collapsed across departments for greater insight into the crimes that are happening within a neighborhood, offering a more comprehensive option for the general public to turn to on local area crime activity. Clearly, data, analytics and technology are making a positive impact to law enforcement processes and investigations. What is your public safety organization doing to evolve and better protect and serve the public?     

Data quality should be a priority for retailers at any time of the year, but even more so as the holiday season approaches. According to recent research from Experian, organizations feel that, on average, 25 percent of their data is inaccurate and 12 percent of departmental budgets are wasted due to inaccuracies in contact data. During the 2013 holiday season, consumer spending is expected to increase by at least 11 percent. Retailers need to improve data quality early on in order to ensure that relevant holiday offers reach consumers and to take advantage of the expected increase in consumer spending. View our recent Webinar: Unique insights on consumer credit trends and the impact of consumer behavior on the economic recovery Source: View our data quality infographic: ’Twas the month before the holidays

The average bankcard balance per consumer in Q2 2013 was $3,831, a 1.3 percent decline from the previous year. Consumers in the VantageScore® near prime and subprime credit tiers carried the largest average bankcard balances at $5,883 and $5,903 respectively. The super prime tier carried the smallest average balance at $1,881.

Using data from IntelliViewSM, Credit.com recently compiled a list of states with the highest average bankcard utilization rates. Alaska took first place, with an average utilization ratio of 27.73 percent. This should come as no surprise since Alaska has recently topped lists for highest credit card balances and highest revolving debt.

When validating a model in the presence of overlay criteria, it is important to remember that any metrics computed at the aggregate portfolio level will not be indicative of the model's true performance. While traditional validation methodologies and portfolio metrics may provide directional insight into model performance, the overlay strategy is an additional variable that must be accounted for in each step of the validation analysis. An effective validation should include: Establishment of an appropriate base line Piece-wise validation of overlay segments An overlay strategy analysis Do you have model validation questions? Learn more and transform your business goals with Experian's Analytical Consulting Services. Source: VantageScore® Solutions LLC white paper: Validating a Credit Score Model in Conjunction with Additional Underwriting Criteria. VantageScore® is owned by VantageScore Solutions, LLC.

As part of its expanded guidance, the Office of the Comptroller of the Currency explicitly recommends that financial services firms utilizing predictive models and decision analytics run regular validations to gauge model efficacy. The VantageScore® credit score model was recently measured against the best credit score models from each of the three largest credit reporting companies (CRCs). When comparing KS values, there is exceptionally strong performance for mortgage originations, with the VantageScore® credit score model outperforming the CRC models in a range from 8 percent to 12 percent. The average range of outperformance is 3 percent to 4 percent across the board for most of the key industries. View the VantageScore® Webinar: Executing Effective Validations in 2011 and Beyond. Source: Executing Effective Validations, American Banker. VantageScore® is owned by VantageScore Solutions, LLC.

VantageScore® Solutions LLC polled risk professionals about how they are measuring score performance, and 60 percent of respondents said they are now using metrics beyond the Kolmogorov-Smirnov (KS) statistic value. One new metric is score consistency, which is defined as the ability to provide near-identical risk assessment of a consumer across multiple credit reporting agencies. In other words, this means having confidence that when a consumer gets a 700 from one agency, he or she is likely to get a 700 from another agency. The other metric that risk managers referenced was stability, which is defined as the ability of a model to retain its predictive accuracy across an extended time frame. Learn more about the VantageScore credit score® Source: VantageScore newsletter, April 2011 VantageScore® is owned by VantageScore Solutions, LLC