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Originally designed as a cloud-based alternative to expensive software that was not flexible, Salesforce.com has become the platform of choice for many companies. To take full advantage of the many capabilities Salesforce provides and to avoid re-creating department silos that exist with most CRM/ERP platforms, more operational business groups are moving to Salesforce to take advantage of built-in features such as 360-degree prospect and account views, workflow, approval queues and tasks. Until now though, credit departments have typically operated in their own silo, accessing customer credit information through proprietary credit and risk management systems. At Experian, we are seeing an increasing need by finance and credit departments to be able to request, review and store our commercial data within Salesforce and quickly respond to credit requests from prospects as well as perform periodic account reviews of existing customers. To solve this disconnect, we have created Experian FusionIQ™, a new Salesforce.com Lightning-compatible app that enables B2B organizations to easily integrate Experian business and commercial credit information into their Salesforce.com CRM instance. With Experian FusionIQ™, we enable credit departments to make better credit decisions while increasing efficiency through easy access to our data. Salesforce.com no longer just for the sales department According to a recent study of financial services companies looking to deploy Salesforce.com, sixty four percent of respondents anticipated productivity gains; fifty percent expected a boost to enhanced cross-functional collaboration; fifty four percent anticipated increased visibility to customer information and thirty eight percent expected improved customer experience. Financial services companies are transitioning from utilizing Salesforce solely as a sales application to leveraging it as a platform for delivering customer engagement. Here are some of the things you can do with Experian FusionIQ™: Get a 360-degree view of all your customer accounts Payment history, public records and credit ratings are key factors when determining whether to pursue new customers or grow existing accounts. The Experian FusionIQ™ app allows you to centralize this critical information within the Salesforce.com environment, giving full transparency to key stakeholders within your organization. Your sales, finance, credit and other internal departments now can work together to optimize resources and prioritize accounts. When the Sales Department can't easily share information with the Credit and Finance departments, the approval process slows down, opportunities are lost, and customers aren’t retained. The Experian® FusionIQ™ app seamlessly adds the business risk data all your key internal stakeholders need within your Salesforce.com environment. Reports, Scoring, Alerts and Decisioning features are available to everyone on your platform, allowing them to make key review decisions in real-time. Create more proactive account-management workflows What is your process for monitoring significant changes in your accounts? The Experian FusionIQ™ app provides instant notification of late payments, defaults, bankruptcies and other changes in your customer and prospect accounts right within your Salesforce.com environment. Migrate your existing BusinessIQ℠ services into Salesforce.com Are you already using Experian’s BusinessIQ℠ to track your accounts’ credit statuses? The Experian FusionIQ™ app allows you to migrate the BusinessIQ services you’re already using into Salesforce.com easily to eliminate bottlenecks and accelerate decision making. Virtually no IT resources required The Experian FusionIQ™ app is designed to integrate automatically with your existing Salesforce.com platform with virtually no additional coding required. Out-of-the-box features give you access to reports, alerts and decisioning. Configure existing Salesforce.com features such as workflow, notifications and reporting to streamline your credit process. FusionIQ for Salesforce.com Lightning Demo  

Credit departments have long performed the important role of assessing and monitoring the health of new and existing customer accounts. However, in the wake of the Great Recession and the ensuing slow economic recovery, the need to evaluate the health of supply chain partners has become even more important. In my role here at Experian, I talk to people every day in credit and supply chain management, and I’ve found striking similarities in the roles of both groups. First, each group has an interest in understanding risk when establishing new relationships, whether it be assessing the credit risk of a new customer or determining the financial stability of a critical vendor. Second, both have a shared interest in monitoring the financial health of both customers and vendors (although it could be argued that the potential disruption associated with the loss of a key vendor might carry a much higher impact for a supply chain manager than having to collect on or even charge off a customer account would for someone in credit management.) For example, a major battery supplier for one of the leading electronic vehicle manufacturers ran into financial trouble recently, and it caused all kinds of headaches. The stock price , sales and customers all suffered. The battery company was the sole supplier to this vehicle manufacturer. With proactive credit monitoring, the vehicle manufacturer may have been able to spot signs that the vendor’s financial stability was beginning to deteriorate, and the headaches could’ve been avoided. Thankfully things worked out in the end (the vehicle manufacturer went into the battery production business.) All in the family Business family relationships are also important in credit and supply chain management. Credit professionals would be interested in Corporate Linkage because they really want to know how to manage a particular customer. Understanding if an account is a subsidiary of a parent company that they have an existing relationship with is vital, as it can affect potential opportunities or responsive strategies if they are delinquent. These insights can help make a more informed decision. For example, a credit manager may think twice about aggressively pursuing an account that may even be moderately delinquent if they realize that they also have a sizable relationship with the account’s parent company. By contrast, they might take a firmer approach with a smaller customer who is behind on their payments, but represents a significantly smaller overall spend. On the supply chain side, visibility into the structure of a parent company is also important, because if the parent company runs into financial trouble it’s likely to cause a domino effect that could quickly steamroll into a supply chain crisis. Understanding and monitoring a supplier’s corporate family relationships enables managers to ensure that they truly have adequate supply chain redundancy. As much as Corporate Linkage informs relationship management in credit accounts, it can help the supply chain manager understand how their spend contributes to the suppliers bottom line, creating additional opportunities for spend management. A supply chain manager that knows they are doing business with three subsidiaries of the same company puts them into a much stronger negotiating position when it comes to volume discounts than if they were viewing the businesses as separate suppliers. Industry Groups Focusing Attention One example of an organization paying attention to the converging credit and supply chain management methodologies is Burbank, California-based Credit Management Association, who recently established a Supplier Risk Management Group. Group Facilitator Larry Convoy agrees that credit management is critical to the health of the supply chain saying recently “During my time in credit management, I’ve often heard the following: ‘We can survive if a customer relationship goes bad, but we cannot survive if one of our primary or secondary vendors has an interruption in delivering product, raw materials or services to us.’ For that reason, we invest an equal amount of resources investigating our vendors. We've created an industry credit group based around this idea for our members, as these relationships can make or break their businesses.” Reducing Friction, Increasing Efficiency To take it a step further, credit professionals and supply chain managers are focused on reducing cost and friction, while increasing efficiencies. A client recently said that it takes 15 minutes for an analyst to review the paperwork they require of a new account that does not pass automated vetting, but on average it takes 10 days for the analyst to get the required documentation from the applicant. In some cases, businesses are limited to working with suppliers that are located within their geographical area for logistical reasons. These companies walk a fine line between operational efficiencies and assuming the right amount of risk. If the risk assessment process is too intrusive, the supplier may walk away. Asking for additional information and delays in establishing the account may put a strain on the relationship at the outset, so using third-party data sources in the risk assessment process can help enhance efficiencies and reduce exposure while maintaining a positive supplier relationship. Delinquency vs. Default One difference between credit management and supply chain is that credit departments are typically concerned with predicting customer delinquency and cash flow, while supply chain management tends to be more focused on assessing the risk of supplier default. However, if a supplier plays a critical role in the supply chain, or is not easily replaced, monitoring the supplier’s financial health is vital. It may be the difference between having to shore up a key supplier financially if there begins to be signs of increasingly delinquent payment versus having the supply chain come to a screeching halt if the supplier suddenly fails. Risk Management Trends Many credit management professionals in financial institutions used macro-economic data during the Great Recession to identify potential regional credit trends that could impact the health of their portfolios. This approach may also be valuable to supply chain managers who want to keep regional economic downturns from disrupting their supply chain. It’s smart to assess not just the supplier’s credit, but also how regional credit trends in the supplier’s area may impact the supplier’s financial health. For example, according to Experian , four of the top five metro areas for bankruptcies in the transportation industry are in California. If a company relies heavily on a transportation company in California and that supplier is somewhat dependent on their local market for their ongoing financial wellbeing, it might be wise to have additional transportation suppliers who can provide similar services, but who are headquartered in less economically volatile areas of the country. At the end of the day, there are far more commonalities than differences between credit and supply chain management. Utilizing proven credit risk management tools, and the data that powers them can help reduce weak links in the supply chain and help steer clear of unpleasant surprises. To learn more about Experian risk management solutions contact us at https://www.experian.com/b2b or call 877 565 8153.  

Ten years ago movie night at our house would usually include a run to the video store where we would pick out a selection from the New Arrivals section, some candy, perhaps some popcorn and we would have our fingers crossed the selection was a good one. Nowadays it’s not uncommon to find us binge watching streamed episodes of “House of Cards” or “Mad Men on weekends.” What’s even more gratifying is after watching “House of Cards” unprompted, Netflix now recommends “The Newsroom” and other shows we invariably like. How do they know we would like these shows? This is predictive marketing at work, driven by big data. Netflix has developed sophisticated propensity models around each member’s viewing habits, and the net result is a better viewing experience with the service. We make amazing entertainment discoveries every week. In business marketing propensity models will determine which prospects or customers are likely to respond to a particular offer. For example, the marketing department of a large financial institution seeking to expand their commercial small business loan portfolio, might want to segment and target commercial lending offers to a concentration of customers most likely to accept a particular offer. When applied in business, propensity models can unlock opportunities for increased profit, share of wallet and deeper engagement with prospects and customers. At Experian, in a typical propensity modeling engagement we will first meet with our customers to understand their goals and objectives. We talk first about pre-screen criteria that enable us to screen out prospects that would not fit into the criteria. A sporting equipment manufacturer would probably not sell to companies in the mining or agriculture industries, so we weed out the ones least likely to lead to a successful conversion. Our data scientists and statisticians get to work on large data sets and evaluate a number of factors. Experian will then develop a customized response model that will identify significant characteristics of responders vs. non responders and therefore will maximally differentiate responders from non responders. Since (holding other factors constant) a higher response rate is preferred, a response model can help lower the cost per response. The response model will generate a “score” that can be used to rank order the prospects base in terms of response likelihood. The response model can be used in two different ways to achieve maximum effectiveness. It can be used to optimize the number of responders for a given sized solicitation, or it may be used to minimize the number of solicitations in order to achieve a budgeted number of responders. A high response score will indicate someone who is likely to respond, as is shown graphically in Exhibits 1 and 2. This work results in a model of the ideal target to which an offer would most likely resonate with. This is called a lookalike. The marketing department at our large financial institution might start off with a large list of potential candidates to send the offer via direct mail, 1 million for example. But mailing an offer to that many people may be cost prohibitive. A propensity model can identify prospects most likely to accept the offer, so your direct mail campaign is more targeted, thereby increasing ROI. A highly targeted mailing to your ideal targets is a safer bet, and would make for a much more predictable outcome. The marketer can feel more confident mailing an offer to lookalike prospects because the chances of successful conversion are that much higher. That’s the case for Woodland Hills based ForwardLine, who have been providing alternative short-term financing to small businesses since 2003. Working with Experian Decision Analytics, ForwardLine did an analysis of their direct marketing program and determined that 22 percent of direct mail was generating 68 percent of their underwriting approvals, exposing a significant gap in wasted marketing funds. The Experian Decision Analytics team developed a custom model which enabled ForwardLine to algorithmically target lookalike prospects with a higher propensity to convert into a successful loan engagement. Michael Carlson, V.P Marketing, ForwardLine ForwardLine Vice President of Marketing, Michael Carlson is thrilled with the initial results. “Working with Experian we were not only able to improve performance, but we are able to reduce our marketing spend, while achieving the same results. We have taken our direct marketing effort from a small program that was profitable, but not meaningful in terms of generating significant volume, to working with Experian to achieve remarkable results. It’s largely why we enjoyed 20 percent growth this year.”     Best in Industry Credit Attributes Experian clients use our archived Biz AttributesSM along with collection specific data elements as independent variables for propensity model development. Experian’s Biz AttributesSM are a set of commercial bureau attribute definitions (includes several key demographic attributes as well) which are accurately developed off Experian’s Commercial BizSourceSM credit bureau. When used for response model development, Biz AttributesSM provides significant performance lift over other credit attributes. Biz AttributesSM are also effective in segmentation, as overlay to scores and policy rules definition, providing greater decisioning accuracy. Additionally, at Experian we are constantly monitoring our growing data warehouse looking for ways to develop new attributes. We live in an ever changing market place which requires us to develop new credit and demographic attributes as well as making enhancements to existing attributes. This process takes a disciplined, rigorous, and comprehensive approach based on experience guided by data intelligence. Our goal is to provide world-class service and the industry’s best practices for modeling attributes. To keep pace with market changes, new attributes are developed as new data elements become available, while raw data elements and existing attributes are monitored and managed following rigorous and comprehensive attribute governance protocols to ensure continued integrity of attributes. If you would like to learn more about propensity models, contact your Experian representative today.

At the recent “Future of Data-Driven Innovation” conference, Emery Simon of the Business Software Alliance noted that each day 2.5 quintillion bytes of data is gathered. How much data is that exactly? To put it into tangible terms, if this data was placed on DVD’s, 2.5 quintillion bytes would create a stack tall enough to go from Earth to the Moon. As Experian’s CEO, Craig Boundy recently blogged, at Experian, we have deep experience harnessing the power of data, in fact; we have been doing it since 1897. Using our insights to help merchants and consumers by providing an annual credit reference directory, we were using “Big Data” before it became a buzz word. You can read Craig’s blog post here. But let’s talk for a moment about the economic impact Big Data can have on society. A recent McKinsey report estimates that improved use of data could generate $3 trillion in additional value each year in seven industries. Of this, $1.3 trillion would benefit the United States.     “Improved use of data could generate $3 trillion in additional economic value each year in seven industries.” McKinsey report: Open data; Unlocking innovation and performance with liquid information As consumers, we see the power of Big Data everywhere these days. Local and State governments are using data to tackle policy objectives like kick starting their economies and driving down crime-rates. In health care, Big Data is being used to reduce infant mortality. Researchers analyzing large data sets of vital signs from premature born babies discovered that whenever the vitals seem to stabilize, there is a high probability that a baby will suffer from a dangerous infection just a few hours later. Stable vitals are red flags, and recognizing them enables doctors to treat an infant before the full onset of the infection. And public health agencies are predicting and managing emergencies from the flu to Ebola with big data algorithms. HealthMap.org is an innovative mapping website that uses algorithms to scour tens of thousands of social media sites, local news, government websites, infectious-disease physicians’ social posts, and other sources to detect and track disease outbreaks. When healthcare workers in Guinea started to see patients with Ebola-like symptoms and blogged about their work, a few people on social media mentioned the blog posts. These blog post mentions were picked up by Healthmap. The result, an algorithm using big data told the story of a looming Ebola outbreak nine days before the World Health Organization formally announced the epidemic. Google can predict the spread of the flu, not through mouth swabs or by interviewing doctors, but simply by analyzing billions of search terms they receive from users of their search engine every day. The city of Syracuse, New York wanted to understand why certain neighborhoods declined over time. The city was struggling with abandoned housing, a phenomenon that is often associated with crime, poverty, and health issues. Analyzing local education, social services, economic, real estate, and police data, the city of Syracuse worked with a team of IBM Big Data analysts who demonstrated that certain trends can presage a decline in public safety, property value, and small business growth. Big Data applications in business In 2008 Starbucks CEO, Howard Schultz was forced out of retirement to get the company back on track after closing hundreds of under-performing stores. Starbucks now employs a disciplined data-driven approach to store openings by using Esri’s ArcGIS Online software, a sophisticated mapping platform which blends maps with demographic data. Starbucks can now pinpoint where their new stores should open, where they can be the most successful. Big Data correlations help Amazon and Netflix recommend products to their customers. In automotive manufacturing, predictive maintenance based on Big Data correlations enables companies to predict when a car engine part needs to be exchanged before the part actually breaks. In computer distribution, algorithms which analyze buying trends and payment data from millions of transactions can pinpoint the segment of customers who will soon stop buying. Identifying this cross-section of soon-to-quit customers enables sales organizations to proactively ramp up customer retention strategies to mitigate the risk of lost business. This helps our economy and our businesses thrive. In agriculture, there are companies and universities blending hardware with big data. Apple farmers in the Midwest are using bug traps fitted with sensors that can identify specific types of bugs in the trap. The traps are connected to the Internet in a data portal that the orchard manager can see where an infestation begins and stop it in its tracks. Being able to turn insights into action, farmers can use data analytics on bug infestations to use fewer pesticides, grow their crop more consistently and more profitably. Big data delivers tangible savings to tax payers The U.S. voter registration system is a challenge to manage. List maintenance can be difficult, and the system needs an upgrade. An inaccurate voter registration file can cost the government between $1 and $2 per year. For a state with 5 million voters, this could mean a cost of $0.5 to $2.5 million per year or more in additional costs, depending on the actual condition of the voter file. Orange County, California was able to update more than 297,000 voter records using information from TrueTraceSM, one of Experian’s most powerful data hygiene products. It draws from Experian’s core consumer credit database of more than 220 million consumers and 140 million households, as well as access to 100 million wireless phone numbers. Orange County saved over $44,000 in the first election alone – savings that will grow with each passing election as the county avoids mailing materials to out-of-date addresses. There are a lot of things to be excited about in the realm of Big Data. As Julie Brill, Commissioner of the Federal Trade Commission remarked at the recent Future of Data-Driven Innovation conference, “The data driven economy will not thrive unless the bits of consumer information collected and analyzed are used to benefit the consumer – plowed back into the relationship between businesses and their customers to make it stronger, deeper, and ultimately more profitable.”

Hello, I’m Hiq Lee, president of Experian’s Business Information Services, and I’d like to talk to you about how we are using data for good to help companies, large and small, succeed in the marketplace. At Experian, our group plays a crucial role in the big data ecosystem as an enabler of commerce and insights for the business community at large. We deliver unbiased information on more than 25 million active U.S. businesses, plus our international data capabilities, enable our customers to make more confident decisions on companies overseas. In 2012, along with Moody’s Analytics, we developed the Small Business Credit Index, which provides a unique perspective on the health of small businesses in the United States. The report contains important trends on bankruptcy rates, delinquencies, and overall payment behavior, as well as macro-economic information. This deeper look at the business landscape helps financial institutions and businesses every day to make sound lending decisions, gain key insights on business credit health and prospect for the right customer. At Experian, we are committed to delivering quality data and are strategically focused on the innovation of new and advanced products and services that enable businesses to thrive. Whether it’s analyzing millions of business credit transactions to generate industry-leading commercial credit scores and business credit reports, or safeguarding and securing millions of records to protect businesses and their customers from fraud, Experian is at the forefront of big data, driving value for our customers the world over. For Experian’s Business Information Services, using our data for good means constantly innovating and looking for ways to benefit businesses, as well as consumers and the overall economy. Related Data Is Good - Analytics Make It Great - Craig Boundy, CEO  

According to a recent United States Department of Commerce Economic Statistics and Administration report, world trade volume for goods and services is expected to increase 5.3 percent in 2015, up from 3 percent in 2013. Working with companies overseas can have a lucrative impact on your business, however, the opportunity does not come without risk. There are many potential pitfalls to expanding overseas that must be addressed in order to mitigate risk and improve profitability. Three of the major information-based hurdles that should be considered are: 1 - Availability - International data often is unavailable to credit professionals or it takes them too long to acquire. 2 - Freshness - International data is often out-of-date, increasing the chance of making inaccurate risk assessments. 3 - Consistency - Credit professionals can’t use the same analytical models across multiple geographies due to data differences. Experian makes it easy for our customers to expand into new territories through our enhanced international capabilities. We provide comprehensive insight into your international customers and vendors — both prospects and existing — that is accurate, up-to-date, easily accessible and highly actionable. This data helps you assess risk, reduce exposure to late payments and defaults, and be more competitive overall. In the below video Experian product manager, Greg Carmean discusses some of the challenges in international business engagements. Experian’s International Developed Profiles help Rubicon Project safely expand into untapped markets Rubicon Project is a technology company that automates the buying and selling of digital advertising. Their trading platform reaches a global audience of 200 million U.S. and 646 million global monthly visitors. Before they began using Experian, the company was hesitant to grant credit internationally due to the limitations of its previous sources. Rubicon Project is focused on rapidly expanding into new territories while providing world-class service and minimizing risk. In some geographic regions, online ad trading is a new concept that is generating considerable excitement, but this poses the challenge of being able to adequately navigate risk in uncharted waters. "With Experian's Business Information Services, we have access to comprehensive information that helps us uncover new growth opportunities," said Lorraine Moses Rubicon Project’s director of credit and collections. Most recently, Rubicon Project has been challenged with monitoring customers located in high-risk countries affected by recent economic challenges in the Eurozone and Latin America. “Experian simply has updated information on many of the customers of concern,” Moses, continued. “We have been able to grant credit to a large number of international customers that would have been declined because we were unable to determine credit worthiness due to limited information.”