Margin test

By all accounts, the national housing market in the US stabilized with a recent report showing year-over-year growth at 6.8 percent for October 2015. However, while interest rates remain near all-time lows, it’s estimated that millions of Americans are unable to take advantage of this opportunity because they are unscoreable using the current credit score model mandated by Fannie Mae and Freddie Mac (“the GSEs”). Under their current guidelines, the GSEs require mortgage lenders to use an older version of a consumer’s FICO credit score when assessing their credit risk. This model is based on data from 1995 to 2000 and unnecessarily excludes millions of qualified borrowers. For instance, VantageScore 3.0 allows for the scoring of 30–35 million more people that are currently un-scoreable under the legacy credit score model. For example, VantageScore expands the depth and breadth of data collected to allow for more creditworthy consumers while balancing risk.  It would allow for more consumers to be scored without lowering credit standards.  With the demonstrated ability of non-legacy models to score more consumers, more consumers would also be eligible for the Home Affordable Modification Program (HAMP) program being conducted by the GSEs. In addition to limiting innovation that could help boost consumer access to credit, the continued reliance on a single credit score model by the GSEs presents substantial risks to industry, their regulators, consumers and the economy as a whole. Using newer credit score models like VantageScore 3.0 would provide for greater predictability given the expanded data available. It would reduce the both the operational and credit risk of the GSEs. Congress can help to address this imbalance by passing H.R. 4211, the Credit Score Competition Act of 2015, which was introduced on December 10 by Representatives Ed Royce (R-CA) and Terri Sewell (D-GA). The bill would instruct Fannie Mae and Freddie Mac to update their requirements so that lenders might be able to use other credit scoring models that are empirically derived and both demonstrably and statistically sound. Experian encourages lawmakers to pass this bill to help encourage the use of innovative and inclusive credit scoring models, while also helping to reduce exposure to potential operational and credit risk.

As data breaches become more prevalent, companies must try to stay ahead of the curve and be prepared to respond to any kind of security incident. In an effort to provide a glimpse into what 2016 could bring, Experian Data Breach Resolution released its third annual Data Breach Industry Forecast white paper. After having conversations with leading industry experts and handling more than 3,000 data breaches in just this year, Experian Data Breach Resolution was able to harness this information and create five key predictions outlined in the white paper. Some issues still will remain relevant in 2016, but there are a few emerging areas that will get on the radar. What can organizations expect in 2016? Global cyber conflicts, the rise of hacktivism, and disruptions during the presidential campaign are just few of the topics addressed in the paper. We hope this information helps businesses with their data breach preparedness and incident response. As we have seen, no data breach is the same. And no one is immune. Executives from across an organization’s spectrum from IT to HR and industries ranging from retail to healthcare should keep abreast of the data breach landscape and how evolving threats will affect their company. To read all five predictions, download the complimentary white paper at http://bit.ly/1l05dq8.  Hear from industry experts on what they foresee in 2016 in our Talking Data Breach video series: http://bit.ly/1N6iELD.

The following interview was conducted by William Vorhies and featured on Data Science Central. Q: What work does a data scientist do and what knowledge do they need? A: 90% of the data in the world has been created in the last two years. Data Scientists retrieve, sift, analyze, process, and store all the data according to business or consumer needs. Simply put, Data Scientists convert the collected and analyzed data into business intelligence. Thus, there are multiple attributes a Data Scientist should have. Not only should they have technical expertise and coding capabilities, but they should also have good intuition and communication skills. Q: How does the work data scientists do improve and protect the lives of people? A: There are breakthrough experiments going on every day that are doing good things with data.  For consumers, it can help them with things such as secure an affordable loan and improve their credit score. It can even help protect identities by detecting and stopping suspicious activity. For businesses, the data can mitigate risk, help prevent fraudulent transactions, or even ensure marketing to proper audiences. Businesses need data scientists to stay competitive and up to date with products, processes, and business operations. Q: What are some of the challenges that face Data Scientists today? A: One of the biggest challenges for Data Scientists is the ability to access and use data.  Since the field is relatively new, many businesses’ security and compliance regulations have yet to catch up, blocking data scientists from the necessary data. Without access, Data Scientists cannot accurately analyze the data set and find helpful insights that can impact consumers, business and society.  As long as privacy rights are respected, adequate security measures are in place to protect personal information, compliance protocols are carefully maintained and there remains a total commitment to data accuracy, the opportunities brought by the use of data by Data Scientists should not be hindered. Q: What does the future hold for Data Scientists? A: Over the last several years, organizations have invested significantly in data collection, storage and analytical platforms.  In the future, their focus will be on developing impactful analytical intelligence and applying it to business processes.  Data scientists with business acumen and solid analytical capability will play an instrumental role in this process.  This presents tremendous opportunities for data scientists to have a positive impact on business and society. Powered by big data analytics, business will happen more in real-time and be tailored for individuals. Examples include, consumers being able to design their own car online, having their medicine customized for their specific needs and delivered to them even before they know they need it. The productivity increase from big data analytics will help us use data for good by benefiting people, our society and our economy. Q: What are some tips for those who would like to work in Data Science? A: As the field grows, keep an open mind and evolve with it. Work hard, think outside the box, and learn as much as you can about the technical side of being a data scientist. Be responsible with the data and realize the potential the data can have to solving problems. Always ask yourself how the data can be used to positively impact the lives around you, and use that to guide your design and development. Bio Dr. Shanji Xiong is the Chief Scientist of Experian’s Global DataLabs. Prior to his current role, he held senior positions with Morgan Stanley, FICO, HNC, and ID Analytics.  For the past 20 years, he has been working in the “Big Data” area, developing analytical solutions for financial, telecommunication and insurance companies.  Dr. Xiong received his doctoral degree from Columbia University in Engineering Mechanics.

The following article was written by Kassandra Kurth, Director of Strategic Initiatives for Experian Health, and featured in Executive Insight:  Touchless Healthcare is Becoming More Prevalent The revenue cycle, however, is anything but Telemedicine has transformed the healthcare industry. From rural America, where in-person doctor visits are difficult, to the farthest reaches of the globe, internet technology allows doctors to visit the sick, diagnose illness, prescribe medicine and even perform surgery without ever actually touching a patient. The recent focus of healthcare automation for providers has been on electronic clinical documentation, but providers also have opportunities to automate revenue cycle functions. Identity verification, insurance validation and payment responsibility now demand a disproportionate amount of a medical staff's time. This is true for both specialist care and elective services, in which approval and payment processes require the provider to supply clinical information to the payer prior to treatment. This need for human involvement invariably bogs down the revenue stream. For patients, the overall healthcare experience suffers. Administrative payment uncertainties become a greater concern than the actual treatment. It's difficult for a medical center to predict the extent of insurance coverage and the patient's out-of-pocket costs. There are just so many variables impacting projected liability that it's unreasonable for facilities that rely on manual processing to provide estimates. While a facility may have an established book of clinical charges, specific procedures can carry variable costs, which must be verified with the appropriate department. In addition, individual insurance carriers have contracted coverage rates and policyholders have varying deductibles, copays and limits that must be considered. The cost-estimation process is so time-consuming – and requires such an abundance of coordination between the physician's plan of care and services provided and the healthcare facility -that many caregivers do not attempt to provide estimates. These concerns are echoed by Lisa Rickey, Patient Access Manager at Brazosport Regional Hospital in Texas. "We had three employees working on estimates for scheduled events and never knew how long each would take to produce," she said. "Because it was not a seamless part of registration, it actually became a negative part of the patient experience." Another concern is remote access to documents – not just by caregivers, but also by insurance providers, labs and patients themselves – via patient portals. While this is becoming the norm, it introduces the same security vulnerabilities seen in financial transactions. To address these issues, robust revenue cycle management (RCM) solutions are being developed that combine a number of analytical tools similar to those used by the credit industry. Medical document processors are now adopting the same information-processing and security technologies used in the financial services and credit industries. In fact, RCM is one of the fastest-growing health information segments. A recent article cited no fewer than 83 companies that are staking a claim in this space. These integrated patient information access, claims management and collections products automate many patient care administrative functions. By leveraging data and analytics, manual tasks such as eligibility and benefits verification, preauthorization, medical necessity, and billing and collections can be streamlined, reducing handling and shortening the payment cycle. Initially these systems were adopted by larger hospitals, which have the technical staff needed to support RCM implementation and benefit most from RCM automation. However, recent advances in ease of deployment have led to more individual practices and private physicians' offices recognizing the benefits as well. Information management companies with legacy workflow, business intelligence and data analytics tools also recognize the overlap between their existing products and the need for comparable tools tailored to healthcare. These providers either have customized established products or partnered with (or acquired) healthcare information companies. Experian Health's acquisition of Passport Health, for example, ties Passport's well-established RCM technology to Experian's established data analytics and revenue-recovery expertise. This powerful combination is expanding RCM to more than 3,000 hospitals and more than 10,000 other medical and ancillary groups across the U.S. Integrating RCM Practices are challenged by the need to integrate RCM with their existing workflows and those of partnering providers. Referring doctors, testing labs and a host of insurers each have their own technology. On the back end, credit and collections procedures may carry another set of tools that must be compatible. For many medical professionals or specialty medical facilities, this is a major barrier to adopting better platforms. A practice can't stop its current process while it ramps up a new one, and few have a large internal IT staff to complete the task. For this reason, it's important to partner with a skilled integrator to maximize the benefits of a revenue cycle solution. A product integrator can assess the unique workflow and objectives and determine the optimal combination of solutions. Ideally, users will be able to make updates to their existing process to align with RCM products. For specialty medical practices such as oncologists or radiologists, each step in the care process carries a measurable cost. Minimizing the time and labor required for each workflow stage translates into better patient care and improved revenue cycles. Each phase – from initial patient identification, service ordering and scheduling through patient admission and treatment, insurance coverage verification, and finally payment collection and archiving – can benefit from a streamlined process. A comprehensive RCM solution can help providers manage the entire patient continuum from registration through recovery. Tasks such as eligibility and benefit verification can be analyzed in batches or in real time at the point of service, ultimately reducing readmissions. Manual data functions like patient verification and prospective financial responsibility assignment can be streamlined. In addition, risk scoring, preauthorization and medical necessity evaluation (critical for Medicare eligibility) can be analyzed. "Many healthcare delivery organization CIOs resist making changes to revenue cycle management applications at their own peril," cautioned HIM Consultant Melanie A. Meyer, writing for Gartner. "CIOs should make investments now to achieve an enterprise view of RCM and deliver these next-generation capabilities." Integrated patient and payment RCM systems, which offer insights from real-time data-handling capabilities and advanced analytics along with competent integration and consultative services, are giving healthcare providers greater control over their revenue processes. By leveraging data in beneficial ways, caregivers finally can move away from pushing paper and get back to the business of healing patients.

Through Experian’s long-standing partnership with the UCI Paul Merage School of Business, I had the pleasure of participating recently in UCI’s Distinguished Speaker Series. I spoke about the role big data plays in today’s economy, and how data is being used as a force for good. My message to the 300+ attendees was clear – big data is everyone’s business. And it’s only going to get bigger. We have 90% more data today than we had just 2 years ago. What will happen in the next 2 years, much less the next 10? As big data gets bigger, how can we use it in even better ways, as a much greater force for good in society? Where we’re headed In the next decade, I predict that: Every single industry – from food service to entertainment to technology to retail – will be using big data in some way. We’re moving quickly in that direction already. A recent Gartner survey found that three-quarters of companies plan to invest in big data over the next 2 years. We’ll be using big data to cure big diseases. I believe we can fully cure cancer and HIV, among others, if we can tap into new insights from wearable technologies and genetic mapping, and put all that data to good use. Big data will help our economy improve. The presidential candidates may argue about the best way to create jobs and increase wealth, but any way you look at it, big data has to be a part of it. The more we can capture trend data on spending patterns and investment returns, the more we can be smart about where we spend our tax dollars, and even how we manage our personal finances. In other words, big data is going to become the backbone of society in ways we least expect today. Sometime in the future, when you go to a museum or an art gallery, big data will make your experience  more personal, more customized, and more relevant to your interests. We’re starting to see hints of this now. Think of how you might receive coupons on your phone for cheaper drinks at the ballpark food counter, because your phone realized you were at the game. “But I think we’re going to take this to an even higher level.” Imagine if we could add virtual reality to your experience – so that, when you walk into an art museum, your phone generates a hologram of your favorite artist. Overall, you’ll be getting a lot more value out of your everyday experiences. Some of the best uses of big data will be in the public sector, an area we’re already achieving significant benefits. Right now, big data is helping to improve public services, transportation and land use. Of particular interest these days, big data is helping to protect public safety in large crowds. And it’s helping people at hospitals figure out how to pay for their care, and pinpointing the most cost-effective payment plans. I think opportunities for big data will continue to expand within the public sector. How we get there But this will only happen if we take the right steps now: We all need to keep learning. This is the message I emphasized with the audience at UCI. No matter where you are in your career, it can only help to sharpen your skills in data and insights analysis. There’s more to discover, every day. Develop policies that encourage data-sharing. We can only benefit from big data if we make it easy for companies and governments to exchange the type of information that will ultimately make our world better. We have a tremendous responsibility to help implement policies that support that goal. Look beyond the obvious. Keep thinking of new sources of data and new applications for it. We’ll all benefit from thinking creatively. That’s the focus we’ve been taking at Experian. One example is our DataLabs, where we are using breakthrough experiments to take risks, so we can do good things with data on behalf of our clients. And we think the world will be better in the long run because of it. Watch these video excerpts from this event: Using Big Data For So Much More How is Big Data Helping Entrepreneurs Big Data Hurdles ### Craig Boundy is the CEO of Experian North America