Bust out fraud: New Strategies for Fraud Prevention

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1 Bust out fraud: New Strategies for Fraud Prevention issue 2 Tap the power of predictive analytics to stop the guesswork and fight fraud inside this issue Activating Big Data Analytics to Drive Innovation Research From Gartner: Innovative Insurers: Harnessing the Nexus of Forces for Competitive Advantage Uncovering More Fraudulent Health Care Providers with FICO Identity Resolution Engine About FICO Activating Big Data Analytics to Drive Innovation The insurance industry is going through a sea change with operational costs, regulatory pressures, competition and claim expenses all on the rise. However, Big Data Analytics is a potential game changer that could save insurers billions of dollars. Annual losses to insurance claims fraud is estimated at $40 billion per annum. Fortunately, the emergence of Big Data, combined with predictive analytics and link analysis, offers insurers a powerful weapon for fighting fraud. While many insurers have yet to leverage Big Data, forward-looking insurers stand to reap enormous benefits by embracing it. Big Data Analytics: A Double-edged Sword for Insurers Predictive analytics helps combat insurance fraud by identifying patterns in claims that are indicative of fraud. Analytic models analyze transactional and relationship data, enabling insurers to uncover formerly unknown types of fraud, identify ongoing schemes, and discover fraud networks. It would seem obvious that more data would only help in this effort. However, Big Data sometimes presents too many potential paths and overwhelms an insurer s ability to sift through the really meaningful data. Insurers must invest either in-house or through outsourcing in the analytic expertise to filter Big Data. In other words, insurers need to know what questions to ask to focus their anti-fraud efforts on the most relevant data. Only by asking the right questions can insurers get meaningful answers in the fight against fraud. Featuring research from

2 Source: FICO Link Analysis: Stretching Big Data a Mile Wide When a reviewer examines an insurance claim, it s helpful to see the bigger picture. This is where link analysis comes in. It s a data-analysis technique that examines relationships between organizations, people and transactions. Link analysis ferrets out related claims that may not appear to be related. For instance, a suspicious auto body shop may be handling an unusually high number of accident repairs. Link analysis might show the body shop isn t the culprit, but may be part of a pool of crooked attorneys, victims and vehicle owners taking vehicles to the same shop. Viewed individually, each claim may look legitimate. But viewed in a broader context, the fraudulent pattern becomes clear. Link analysis is a data-hungry process that is bolstered by Big Data s broad reach. The key to link analysis is identifying relationships across as many sources as possible. More data yields more information about more relationships. Big Data, Big Opportunity Big Data is a potential game changer. Added to predictive analytics and link analysis, it helps insurers detect more fraud, reduce false positives, and improve customer satisfaction by streamlining payment of legitimate claims. While the industry s record of embracing new technology is mixed, the potential payoff from Big Data is extremely compelling. But to reap the benefits of Big Data, insurers must do more than build larger databases. They must invest in the technology and expertise needed to apply Big Data in a fruitful and efficient manner. 2 l Bust out fraud: New Strategies for Fraud Prevention Bust out fraud: New Strategies for Fraud Prevention is published by FICO. Editorial content supplied by FICO is independent of Gartner analysis. All Gartner research is used with Gartner s permission, and was originally published as part of Gartner s syndicated research service available to all entitled Gartner clients Gartner, Inc. and/or its affiliates. All rights reserved. The use of Gartner research in this publication does not indicate Gartner s endorsement of FICO s products and/or strategies. Reproduction or distribution of this publication in any form without Gartner s prior written permission is forbidden. The information contained herein has been obtained from sources believed to be reliable. Gartner disclaims all warranties as to the accuracy, completeness or adequacy of such information. The opinions expressed herein are subject to change without notice. Although Gartner research may include a discussion of related legal issues, Gartner does not provide legal advice or services and its research should not be construed or used as such. Gartner is a public company, and its shareholders may include firms and funds that have financial interests in entities covered in Gartner research. Gartner s Board of Directors may include senior managers of these firms or funds. Gartner research is produced independently by its research organization without input or influence from these firms, funds or their managers. For further information on the independence and integrity of Gartner research, see Guiding Principles on Independence and Objectivity on its website,

3 Research from Gartner Best Practice G , Innovative Insurers: Harnessing the Nexus of Forces for Competitive Advantage Kimberly Harris-Ferrante, 19 October 2012 The Nexus of Forces is transforming the P&C and life insurance industry, and providing new opportunities for information innovation. The combination of new data, enhanced analytics, flexible business processes and technologies will allow insurers to manage and modify business processes in real-time. Key Challenges The Nexus of Forces defined as the combined impact of social, cloud computing, enhanced information and mobility is showing dramatic potential to change the insurance industry. Unfortunately, only a few innovators have grasped the potential of these forces and have altered their business model and embraced these technologies for competitive advantage. While many insurers are investing heavily in data warehousing, business intelligence (BI) and analytics, most companies are focused on data insight, including reporting. Most insurers fail to understand the prerequisites for realtime action, such as accessible business logic in core systems, the need for business process management (BPM) systems that expose business rules, and real-time notifications to staff to expose risks or be leveraged in decisioning (for example, underwriting or claims investigation). Recommendations Assess how social media and wireless technologies (including machine to machine [M2M]) can support product development, usage-based products, claims, underwriting and product intelligence. Modernize claims and underwriting fraud management through the use of new data (including unstructured and social), solutions and processes to help reduce losses and predict fraudulent behavior in real-time. Ensure that customer-facing and core processing systems (including underwriting, claims and new business) are realtime, and allow key decision makers to quickly and easily change rules and processes to support real-time action. Identify how real-time information and analytics can be used in combination with BPM technologies to automate traditionally manual tasks, such as policy issuance, claims notifications and generation of cross-sell offers. Introduction P&C and life insurers are increasingly recognizing the power that enhanced data visibility and analytics can provide to their organizations. During the past few years, companies have improved their capabilities in BI and analytics. During this era, focus has been on leveraging internal data assets for real-time visibility into performance and reporting. More recently, the focus expanded to include enhanced visualization techniques (e.g., dashboarding) and predictive modeling, but remains targeted at information use and analysis, failing to focus on how to use the information derived in this analysis for realtime organizational action. Today, innovative insurers are going beyond traditional data management and analysis practices to seek ways to use information to innovate, and are centrally interested in having actionable insight directly related to business advancements. Gartner has identified the Nexus of Forces as a key transition element for many industries, including the insurance sector. The intersection of cloud, mobility, social and information is driving change and allowing future-thinking insurers to capitalize on these advancements for competitive advantage. Information innovation is one example where the nexus is opening up new opportunities for insurers never possible in the past, especially in areas such as new product development leveraging mobile and M2M processing, more powerful data analysis using unstructured data and real-time action, as information is combined with modern core business processing systems. However, Gartner customer interactions reveal that only a few innovative insurers have build strategies, to date, which identify business opportunities as a result of the Nexus of Forces and how they can use this to differentiate in areas such as product innovation, risk management, customer interaction or operations. Companies can establish new business processes, which leverage information for improved decisioning, process automation and corporate intelligence (e.g., including market, Bust out fraud: New Strategies for Fraud Prevention l 3

4 competitive, customer, risk, and operational). All of this will help fulfill enterprise agility, therefore making insurers able to stay competitive and shift with emerging market conditions during the next 10 years. Offering fleet managers behavioral feedback, using telematics. Black-box technology can be used to help manage the risks of commercial fleet insurance, as well as offer drivers and fleet operators information on driving risks. 4 l Bust out fraud: New Strategies for Fraud Prevention P&C and life insurers must understand the opportunities that new technology enhancements are making on the industry, and how leaders are embracing the nexus for business transformation. CIOs, IT leaders, chief marketing officers (CMOs) and other business leaders should carefully evaluate the short- and long-term impact of information innovation on their business model and identify ways to obtain better value from existing and emerging data assets and technologies. Gartner has identified four best practices that insurers should evaluate to get maximum value from their information assets and leverage to stay competitive. Analysis There are four best practices that life and P&C insurers need to evaluate when positioning information as an enabler of innovation. Companies should look at these options as they build their information management strategies and evaluate the examples provided. Leverage Social Media, Wireless Technology and the Cloud Within Product Development Product innovation has been rising in importance among P&C and life insurers during the past five years, and Gartner continues to observe many companies still assessing ways in which they can launch new products to meet shifting consumer demands. The Nexus of Forces is creating new product opportunities as a result of new device usage that can provide real-time information to the insurer to support pricing, risk modeling and product needs, as well as using social networking platforms as a medium for product intelligence, and sales and cloud computing models to support data procedures. Examples of how insurers can leverage these devices and platforms include: Leveraging telematics technology (including black-box and in-car technology) to offer usage-based insurance for auto/ motor insurance. Data is sent from the device to the insurer in real-time, which then can be analyzed to determine cost of premium, based upon driving behavior ("pay as you drive"). In the future, insurers will collect more data from these devices to offer "pay how you drive." This will analyze driving patterns such as speed, location and other driving risk, compared to only mileage data, which is used today. Telematics data can also be utilized in actuarial departments to help with improved risk modeling and pricing. Some U.S. insurers, for example, launched teen driving programs during the last few years, which install a box into the car to provide driving data to the insurer and provide parents with valuable information, such as driving behavior and tracking (e.g., location of car can be seen on the Internet, leveraging the GPS in the box). New wireless technology can be used to help understand property risks, especially in regions with large-scale natural disasters. Wireless boxes can send information to insurers about movement of buildings or structural damage, which would impact insurability and property risks. Smart home technology can be leveraged to help understand the risks of a physical dwelling and help homeowners control costs of insurance in providing this information to their insurer. Identifying product opportunity due to real-time data derived from the device, such as the consumer moved into a location, or exhibits a behavior which signals a new product opportunity or that is not currently covered within their existing product. Collect and analyze data from social media platforms to identify individual product needs (e.g., individual customers, based upon statements or behavior on the platform) and product trends (e.g., pattern analysis of repeatable issues or needs of social media users for products related to unique behaviors or life stages). Use crowdsourcing for direct feedback from customers to create and vote on new product ideas. This strategy has already been used, for example, by small business insurers wanting customers/prospects to identify the needs of this consumer group that were not met with traditional products, so that they could create a new product to fill these gaps. Enable product innovation through cloud computing. To fulfill this strategy, many insurers will be increasingly turning to the cloud as the mechanism to support data acquisition and even data analysis. Cloud computing will

5 help companies build out the wireless data platform, can be an option for hosting the data analysis solution or, possibly, be the platform for which business process as a service (BPaaS) providers run their network. This will provide smallto-midsize insurers the opportunity to enter new product markets, without the substantial upfront investments needed to support these products (e.g., the policy management and billing systems), or the data infrastructure to support the volume required for real-time wireless and M2M processing. Support more granular pricing analysis by actuaries through augmenting traditional information with new data sources to aid in precision. Many companies are leveraging cloud computing to assist with processing power, and avoiding runtime issues when data sources grow larger than what traditional actuarial systems can handle. Deploy New Data, Improved Models and Modern Fraud Technologies to Strengthen Fraud Management P&C and life insurers should embrace new forms and techniques for data management in areas of fraud and risk management. Innovative insurers are building out new strategies targeted at reducing fraud and losses through a combination of enhanced data, new fraud detection technologies and improved process management (including case management capabilities to support fraud investigation; for more information on fraud, see "Insurers Must Become More Aggressive at Addressing Underwriting and Claims Fraud"). This can be applied to underwriting and claims fraud. Unstructured data analysis to include adjuster and customer service representative (CSR) notes, images and social data in the model and investigation process. GPS-empowered data checks against entered data, or to supplement user input. For example, using GPS to determine where the user is filling out a first notice of loss (FNOL) application on a mobile device to compare against the accident report. Pattern detection to identify new patterns such as abnormalities in the data to represent new behavior of fraudsters to help with model improvement. Leveraging social media data for fraud investigation in product lines such as workers compensation, bodily injury, or disability. Using this as an information source to help investigate potentially fraudulent cases and provide input for litigation. Performing social network analysis to identify fraud rings by analyzing location, address or individual through assessing connections, which are not obvious in the data through traditional BI practices. Using industry data aggregation services to supplement internal data to help identify fraud risks and patterns through the collective power of combined data assets across multiple insurers in a pooled data service. Often, this is offered in the cloud by data providers, reducing the lapse time and cost of using such services (including pay-by-the-use models). Key ways innovative insurers are leveraging information for reduced fraud include: Improving the accuracy of fraud detection through improved analytical capabilities, often through the use of modern fraud detection solutions. These solutions support analysis of structured and unstructured data, provide advanced analytics procedures (including predictive modeling and anomaly detection) and help to identify fraud rings through the analysis of repeatable trends via social network analysis. Real-time data analysis at point of data entry through the use of predictive modeling and modern fraud detection solutions that operate in real-time versus batch. For underwriting fraud, this would be combined with e-applications, with intelligence built in to validate the data being entered and flowing through the application (e.g., back/forward movement and data field changes). Using modern fraud management applications, which leverage social network analysis, predictive modeling, business rule engines and unstructured data analysis, insurers can help reduce risks in claims and underwriting therefore driving up profitability and reducing losses. Provide Real-Time Information and Systems to Key Decision Makers Throughout the Company Having real-time insight into performance and notifications about changes in the data is valuable, but without a way to respond including changing a business process the value is diminished. This issue is growing, with the advent of wireless devices, social platforms and other mechanisms that provide more data in real-time to the insurance business user. Furthermore, much of insurance is still based upon critical decisions that key decision makers will continue to make throughout the organization. These individuals consist of heads Bust out fraud: New Strategies for Fraud Prevention l 5

6 of underwriting, marketing, claims, customer service, sales and the CFO, for instance. These employees need real-time insight, but also real-time systems (e.g., those which operate in realtime, are business rules and BPM-based, therefore allowing the business user to make rule/process changes without IT's involvement, and those that execute process changes in real time), which they can quickly and easily go into to change a workflow, business rule or process all together. For ultimate success, insurers are combining real-time insight with real-time systems to allow decision makers the ability to act. Use New Data and Improved Modeling to Support Business Process Re-engineering In addition to assisting in decisioning, real-time information is being analyzed and applied to automate next action or outcomes therefore supporting process improvements and automation. In these cases, information will allow an insurer to radically change the business processes and reduce manual steps (and those that were typically considered fundamental). The end result is a more consistent, faster, accurate and lowercost process. 6 l Bust out fraud: New Strategies for Fraud Prevention Examples of how insurers are combining real-time data and systems for decision workers include: Collecting information on upcoming changes in weather patterns (e.g., a hurricane forming off the coast of Florida) to determine impact on underwriting, and (if needed) changing underwriting rules in the underwriting/policy system in real-time to stop all policies being quoted and issued within a certain region. Rules changes are instantaneous and immediately implemented, resulting in no new policies being issued until the rule is overridden (e.g., the storm is over and the head underwriter releases the hold in the system). Identifying pending risks instantaneously and automating outbound notifications to customers on how to prevent losses and prepare for this event. This will help reduce losses, and provide customers with valuable information to prepare for pending catastrophes or other events, including natural disasters or health risks. Real-time feeds from social media platforms that can be routed to customer service and claims, including notification of complaint, incident (e.g., wreck or loss) or service inquiry. Real-time visibility into issues that are growing on the social media channel that CMOs and corporate executives need to respond to. This would include backlash of a recently launched media campaign or some negative response to the corporate image or brand. Immediate insight into the rising issue will allow companies to respond, as well as show how to face the issue (e.g., cancelling the campaign). Analyzing social media for repeatable service issues, including claims problems, process bottlenecks and call center performance. Many insurers are using this feedback, for example, to assess the effectiveness of the call center and provide input into training. Examples of how this could be done include: Enabling the underwriting of life insurance policies, without a medical exam. Life insurers are slowly adopting predictive underwriting technologies and new sources of data (including pharma) to assess risk, using new models and data sources. This results in quicker underwriting and elimination of the step of human medical examination. Increasing auto adjudication of claims in P&C insurance. This is already commonplace for simple claims, such as glass repair or low-cost risks in personal lines. P&C insurers are increasingly assessing how this can be applied to higher cost and more complex claims, when risk is low and cost of claims processing is high. Real-time product offers on the website, based upon either website analytics (i.e., movement on the site as a user visits pages on life events and clickstream analysis) or through the use of gamification technologies, where customers go through a series of exercises to determine best product fit. Products or product bundles can be combined on demand, real-time marketing messages displayed on the user's screen or outbound s generated can be tailored to that individual's unique needs and personalized, based upon any customer information you have on that individual. Using personality profiling to match call center CSRs, with prospects/customers in order to promote improved sales rates and customer-service quality.

7 Source: FICO Uncovering More Fraudulent Health Care Providers with FICO Identity Resolution Engine Many insurance payers realize how valuable Identity Resolution and Link Analysis technology can be in supporting detection of organized crime, as well as opportunistic fraudulent providers. But they also know how difficult it is to implement on proprietary platforms. Now, with FICO Identity Resolution Engine as a component of FICO Insurance Fraud Manager, health care insurers can immediately access the industry s most innovative entity data matching technology to reduce losses with a more holistic view into criminal activity and networks. Every insurer is painfully aware of the double-edged dilemma caused by claims fraud today. Fueled by the growing sophistication of criminal rings taking advantage of transaction volume and multiple communications channels as well as sophisticated identity deception the industry is experiencing big losses. First, there are the losses caused directly by fraud. Many insurers estimate that between 10 and 20 percent of claims are fraudulent, and that they detect or deny less than 20 percent of those fraudulent claims. Then there are the losses caused indirectly by fraud. The mere threat of today s fraud problem challenges the speed and efficiency of many firms claims handling. In today s competitive marketplace, slow claims payments or mistakenly denied claims will quickly drive customers away, not to mention generate fast and widespread reputational damage via social media. So how best to strike a balance between today s fraud detection and claims handling demands? And how to do so within today s reality of cost and resource constraints? The answer is with a more comprehensive, and more streamlined, view into today s fraud perpetrations, and in particular with an analysis of the perpetrators, as well as the claims themselves As part of its FICO Claims Fraud Solution, FICO is helping insurers worldwide efficiently detect more fraud with FICO Identity Resolution Engine, combining federated data search capabilities, identity resolution algorithms, link analysis technology, and visualization tools. Now, in addition to determining whether a claim appears to be fraudulent using analytic models and rules technology, insurers can determine whether a claimant s personal or transactional data appears to be suspicious, and whether that person is linked with additional people who may also be suspected of involvement in a fraud ring or fraud activity. Applicable in reactive investigations to incoming claims, or in proactive mode to predetermine likely perpetrators, payers can use the solution s identity resolution and linking technology to search across a variety of attributes such as locations, service providers, telephone numbers, names and identifiers (License, NPI, DEA Numbers) to uncover hidden relationships behind criminal fraud rings. FICO Identity Resolution Engine differentiates itself from other data matching systems with: A federated, cross-database approach to accessing a variety of internal or external data sources, eliminating the need to build a data warehouse and move data into a separate repository. Advanced and proven technology to automate the matching and relationship identity process with extremely high precision and speed.» Intelligent Data Access FICO Identity Resolution Engine gives insurer s investigators the fastest and most comprehensive technology to determine who s who and who knows whom across disparate and potentially remote data sources. Unlike other vendor solutions, there s no need to develop a separate data warehouse, move data into a common repository, and cleanse and normalize the data. Instead, with FICO Identity Resolution Engine, investigators look at data in the original location and source format using a seamless approach to understanding matches, relationships and degrees of separation. It s easy to leverage the value of any internal or external data sources, without the exorbitant costs, time delays and resource drain required by other solutions. Bust out fraud: New Strategies for Fraud Prevention l 7

8 Source: FICO 8 l Bust out fraud: New Strategies for Fraud Prevention FICO Identity Resolution Engine gives investigators access to multiple data sources at once. Rather than logging on and off of each data source in succession for example, individually searching separate data sources on customers, agents/ employees, claims, negative data watch lists or external thirdparty databases FICO Identity Resolution Engine accesses all data sources simultaneously. This enables investigators to triage cases in minutes, or seconds, rather than days or weeks, using FICO s case manager. In addition to cost, time and resource savings, insurers realize other benefits from FICO s federated data access approach: Avoid privacy issues. By not moving data from various sources into a central repository, insurers avoid the possibility of commingling sensitive data. They also eliminate the risk of being responsible for making sensitive data public via database attacks or unintentional distribution of data. The forensic value of data is not jeopardized. Many data matching systems discard valuable forensic data as part of the data cleansing process. For example, if an insurer determines that a John Doe is an alias and the correct name is Jon Doe, many systems will automatically discard all John Doe references after the determination is made, thereby diminishing the forensic value of data searches. Unlike other data matching options, however, FICO Identity Resolution Engine retains all of the correct information so there s no rework when the case gets turned over to litigation.» How It Works: Four Core Functions FICO Identity Resolution Engine provides four core functions for insurers: Cross Database Identity Resolution, Link Analysis, Real Time Visualization and Red Flag Alerts. In just minutes or seconds, the technology helps investigators: Determine that an individual is using multiple, various versions of personal attribute information an indication of a fraud perpetrator.

9 Uncover links between disparate individuals sharing the same personal attribute information an indication of a possible fraud ring. Visually analyze matches and relationships on-screen with the FICO case manager or other third party software. Receive red flag alerts of data matches when transactions occur. Cross Database Identity Resolution gives insurers a method to develop identity similarities with the system s federated, single search functionality. The identity resolution functionality intelligently searches across disparate databases for variations in spelling, addresses and formats, and determines matches using more than 50 algorithms. When a claim is fi led, or when used in a proactive search, the technology s identity resolution engine will compare attributes of the policyholder with other databases such as an internal Special Investigation Unit (SIU) blacklist, other internal databases and external databases. The technology analyzes personal attributes such as name, street address, city/state/zip, social security number, date of birth, telephone contact or employer across databases to identify likely matches. Unlike other data matching technology, the FICO system also scores the match in terms of its likelihood of representing the same person. Social Link Discovery produces connections between suspicious claimants and other individuals. Once a claimant has been deemed suspicious, investigators can then fi nd relationships between that individual and others claimants, but also third-party individuals such as the insurer s employees or Source: FICO Bust out fraud: New Strategies for Fraud Prevention l 9

10 business professionals that might stand to gain from a paid claim. The technology enables investigators to uncover non-obvious relationships by exploring attributes in additional databases. For example, attributes, such as a phone number, from the suspicious claimant may be found to match attributes of an individual in the insurer s agent/employee database, suggesting collusion. Investigators can then determine if that employee s attributes match attributes of individuals in other databases, suggesting a ring. FICO Identity Resolution Engine also opens the door to the potential of data within social networks such as Facebook and Twitter, if the insurer has access to that data. Real Time Visualization gives investigators an on-screen graphic display of the matches that it has determined as suspicious. Its icons identify the degrees of separation between the claimant, the similar claimant identities found in various databases, and other individuals that the claimant is connected to by way of shared attributes. Red Flag Alerts automatically display suspicious activity directly to the investigator as transactions occur such as at First Notice of Loss. In some cases, where a relationship match is displayed in another business area for example, an auto claims investigator sees that a match has been uncovered in a homeowner policy database the investigator can alert the company s other line of business area.» For Reactive Investigations and Proactive Fraud Detection Insurers can apply FICO Identity Resolution Engine in reactive investigations as a regular part of their claims review process, or in a proactive approach to identifying networks. In reactive investigations, the technology is applied following a FICO claims fraud score identifying an incoming claim as suspicious of fraud. As shown in Figure 3, the suspicious claim s policyholder is now a suspect. To determine if the policyholder should be suspected of criminal involvement, investigators use FICO Identity Resolution Engine to perform targeted searches across various internal or external databases looking for shared personal attribute information with other suspects or known criminals. Figure 3 also shows how the technology can be used in proactive investigations, searching for suspects that could trigger alerts to 10 l Bust out fraud: New Strategies for Fraud Prevention Source: FICO

11 future incoming claims. Investigators can perform broad based searches of various individuals to find suspicious connections based on shared personal attributes. FICO analytics can then determine and prioritize the strength of the connections to identify new suspects.» A Critical Component of an Integrated Solution FICO Identity Resolution Engine is a critical component of the comprehensive FICO Claims Fraud Solution, integrating industry-leading technologies including: sophisticated analytics to detect potential fraud and provide a logical starting point for an Identity Resolution Engine search; flexible business rules management to manage defined actions based on corporate parameters; case management capabilities to support workflow; and professional services to tie it all together. Find Out More Learn how your company can benefit from FICO s advanced solutions to fight insurance claims fraud. Contact us at info@fico.com. Bust out fraud: New Strategies for Fraud Prevention l 11

12 About FICO FICO (NYSE:FICO) delivers superior predictive analytics solutions that drive smarter decisions. The company s groundbreaking use of mathematics to predict consumer behavior has transformed entire industries and revolutionized the way risk is managed and products are marketed. FICO s innovative solutions include the FICO Score the standard measure of consumer credit risk in the United States along with industryleading solutions for managing credit accounts, identifying and minimizing the impact of fraud, and customizing consumer offers with pinpoint accuracy. Most of the world s top banks, as well as leading insurers, retailers, pharmaceutical companies and government agencies rely on FICO solutions to accelerate growth, control risk, boost profits and meet regulatory and competitive demands. Building a world class experience is an evolution, not a revolution, and FICO analytic tools and applications deliver ROI at every stage of maturity. Learn more at FICO: Make every decision count. Big Data analytics will revolutionize how products are developed and distributed to how organizations communicate with customers. Advances in technology have created challenges, but also opportunities to increase sales and profit. FICO is helping the world s largest marketing organizations succeed by finding actionable customer insights within massive amounts of data and making high-volume decisions more accurate, predictable and profitable at every turn. 12 l Bust out fraud: New Strategies for Fraud Prevention