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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.