For far too long, anti-money laundering and terrorist financing solutions have forced analysts to wade through oceans of transactions and alerted work items (alerts). Alert-centered analysis is both ineffective and costly. The goal of an anti-money laundering program is to reduce risk for your financial institution, and to do this most effectively, you must start with analysis at the customer level, rather than simply troll through volumes of alerts and transactions. In this session, discover how a customer-centric approach leads to increased analyst efficiency and streamlined investigations. Rather than starting with alerts and transactions, starting with a customer-centric view allows your analysts to rapidly triage suspicious activities, prioritize work, and quickly move into investigating the highest risk customer activities.

Does the rapidly changing fraud and compliance landscape make it difficult to adapt your applications to meet your current needs? Fraudsters are constantly evolving and your applications need to be able to keep up. No two businesses are ever the same. They all have different business drivers, customer needs, market demands, and strategic objectives. Using SAS^® Visual Investigator, business units can quickly adapt to their ever-changing needs and deliver what end users and customers need to be effective investigators. Using the administrative tools provided, users can quickly and easily adapt the pages and data structures that underpin applications to fit their needs. This presentation walks through the process of updating an insurance fraud detection system using SAS Visual Investigator, including changing the way alerts are routed to users, pulling in additional information, and building out application pages. It includes an example of how an end user can customize a solution due to changing fraud threats.

Gone are the days when the only method of receiving a loan was by visiting your local branch and working with a loan officer. In today's economy, financial institutions increasingly rely on online channels to interact with their customers. The anonymity that is inherent in this channel makes it a prime target for fraudsters. The solution is to profile the behavior of internet banking in real time and assess each transaction for risk as it is processed in order to prevent financial loss before it occurs. SAS^® Visual Scenario Designer enables you to create rules, scenarios, and models, test their impact, and inject them into real-time transaction processing using SAS^® Event Stream Processing.

Every day, businesses have to remain vigilant of fraudulent activity, which threatens customers, partners, employees, and financials. Normally, networks of people or groups perpetrate deviant activity. Finding these connections is now made easier for analysts with SAS^® Visual Investigator, an upcoming SAS^® solution that ultimately minimizes the loss of money and preserves mutual trust among its shareholders. SAS Visual Investigator takes advantage of the capabilities of the new SAS^® In-Memory Server. Investigators can efficiently investigate suspicious cases across business lines, which has traditionally been difficult. However, the time required to collect, process and identify emerging fraud and compliance issues has been costly. Making proactive analysis accessible to analysts is now more important than ever. SAS Visual Investigator was designed with this goal in mind and a key component is the visual social network view. This paper discusses how the network analysis view of SAS Visual Investigator, with all its dynamic visual capabilities, can make the investigative process more informative and efficient.

Wouldn't it be fantastic to develop and tune scenarios in SAS^® Visual Scenario Designer and then smoothly incorporate them into your SAS^® Anti-Money Laundering solution with just a few clicks of your mouse? Well, now there is a way. SAS Visual Scenario Designer is the first data-driven solution for interactive rule and scenario authoring, testing, and validation. It facilitates exploration, visualization, detection, rule writing, auditing, and parameter tuning to reduce false positives; and all of these tasks are performed using point and click. No SAS^® coding skills required! Using the approach detailed in this paper, we demonstrate how you can seamlessly port these SAS Visual Scenario Designer scenarios into your SAS Anti-Money Laundering solution. Rewriting the SAS Visual Scenario Designer scenarios in Base SAS^® is no longer required! Furthermore, the SAS Visual Scenario Designer scenarios are executed on the lightning-speed SAS^® LASR™ Analytic Server, reducing the time of the SAS Anti-Money Laundering scenario nightly batch run. The results of both the traditional SAS Anti-Money Laundering alerts and SAS Visual Scenario Designer alerts are combined and available for display on the SAS^® Enterprise Case Management interface. This paper describes the different ways that the data can be explored to detect anomalous patterns and the three mechanisms for translating these patterns into rules. It also documents how to create the scenarios in SAS Visual Scenario Designer; how to test and tune the scenarios and parameters; and how alerts are ported seamlessly into the SAS Anti-Money Laundering alert generation process and the SAS Enterprise Case Management system.

Today's financial institutions employ tens of thousands of employees globally in the execution of manually intensive processes, from transaction processing to fraud investigation. While heuristics-based solutions have widely penetrated the industry, these solutions often work in the realm of broad generalities, lacking the nuance and experience of a human decision-maker. In today's regulatory environment, that translates to operational inefficiency and overhead as employees labor to rationalize human decisions that run counter to computed predictions. This session explores options that financial services institutions have to augment and automate day-to-day decision-making, leading to improvements in consistency, accuracy, and business efficiency. The session focuses on financial services case studies, including anti-money laundering, fraud, and transaction processing, to demonstrate real-world examples of how organizations can make the transition from predictions to decisions.

The recent controversy regarding former Secretary Hillary Clinton's use of a non-government, privately maintained email server provides a great opportunity to analyze real-world data using a variety of analytic techniques. This email corpus is interesting because of the challenges in acquiring and preparing the data for analysis as well as the variety of analyses that can be performed, including techniques for searching, entity extraction and resolution, natural language processing for topic generation, and social network analysis. Given the potential for politically charged discussion, rest assured there will be no discussion of politics--just fact-based analysis.