The real deal in fraud and financial crimes

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Financial institutions evaluating fraud management solutions face a crowded vendor landscape. Dozens of vendors claim to offer various pieces of the puzzle. With so many choices available, how will you sort through the marketing rhetoric to find the best fit for your organization?

You could assemble a team of analysts and advisors from the risk management and financial services industries to serve as independent advisors. Give them several months to gather and review vendor submission forms, administer user surveys, interview customers and users of each solution, conduct briefings with vendors, attend conferences, host roundtable discussions, collaborate with industry consultants, and review academic and regulatory studies.

You could, or you could be thankful that research firms have already done it.

Checking under the hood

Industry analyst firms each have their own method of evaluating vendor technologies. SAS recently had the pleasure of participating in evaluations from two notable firms, and I’m proud to report that we not only met the strict criteria for inclusion but also were named as a leader in both reports.

Forrester Research conducts intensive hands-on laboratory evaluations of fraud management solutions from vendors that meet its selection criteria, then evaluates and scores those vendors on 15 additional factors. Forrester’s January 2016 report, The Forrester Wave™: Enterprise Fraud Management, Q1 2016, put SAS in the #1 position as Leader for current offerings, while also awarding SAS the highest scores among all vendors in the strategy and market presence categories.

Chartis uses the RiskTech Quadrants® approach it developed specifically for the risk technology marketplace, based on extensive independent research and coding the findings into a clear scoring system. Selected vendors – 31 in the latest study – are then ranked based on completeness of offering and market presence and potential. SAS scored the #1 position as category leader in the April 2016 report, Chartis RiskTech Quadrant for Enterprise Fraud Technology Solutions 2016. SAS is also positioned as a leader in the RiskTech Quadrant for anti-money laundering (AML) and transaction monitoring solutions, know your customer (KYC) and client on-boarding solutions, and watch list monitoring solutions.

Forrester Wave™: Enterprise Fraud Management, Q1 ’16

Forrester Wave™: Enterprise Fraud Management, Q1 2016. Image source: http://www.forrester.com/pimages/rws/reprints/document/113082/oid/1-SFN56X © 2016 Forrester Research, Inc.

 

What makes a category leader?

It’s gratifying when independent research firms validate our development directions and performance, but what should really matter to you is that these reports clarify what to look for. What makes a leader? What will you get from a category leader that you won’t get elsewhere, and how does it affect your ability to protect your data, customers and reputation while preserving the digital experience? Three components seem to stand out the most: completeness of offering, an enterprise approach and machine learning.

A complete offering

Forrester evaluated vendors against 15 criteria grouped into three high-level buckets: current offering, strategy and market presence. SAS was cited as leading the pack with the following capabilities:

  • Great coverage for data integration, queue management, and authoring of rules and models with out-of-the-box support for all major transaction types
  • Product development strategy that includes: 1) improving in-memory visualization of performance indicator dashboards; 2) extending design and simulation against big data; and 3) improving analytics by integrating device and behavior data.
  • Innovation in mobile payment fraud detection, machine and deep learning, and a wide support network of developers, professional services, sales and technical support personnel worldwide.

On the Chartis shopping list for a category leader are capabilities for:

  • Entity triage and prioritization
  • Data quality and aggregation to create common customer views
  • Text mining and sentiment analysis for analyzing unstructured data
  • Real-time decisioning, authoring, and simulation
  • Consortium and custom model services for payments fraud
  • Transaction monitoring optimization supported by in-memory architectures
  • Proactive search and discovery
  • Easy sharing of data and investigations through a common technology foundation

Stated differentiators for SAS included “the computational power of the core system, the ability to analyze large amounts of complex data in a timely manner (where relevant in real-time), and the ability to improve analytical performance.” Particular attention is given to risk analytics, which requires such capabilities as non-linear calculations, predictive modeling, simulations and scenario analysis. Using multiple analytic techniques to calculate a composite fraud score identifies fraud that would otherwise go detected and reduces false positives.

Enterprise approach

A number of vendors say they have an enterprise approach, but by what definition? Some vendors have tacked on data management and business intelligence (BI) capabilities to their fraud tool. Others were data management or analytics vendors who somehow added or acquired a method to address fraud. According to Chartis, a true enterprise approach is about much more than checking off those functional boxes in the portfolio:

“Enterprise solution providers have a clear strategy and vision for providing risk management technology platforms. They are characterized by the depth and breadth of their technology capabilities, combining functionally rich risk applications with comprehensive data management, risk analytics, and business intelligence technologies. A key differentiator is the openness and flexibility of their technology architecture and their ‘tool-kit’ approach to risk analytics and reporting.”

The completeness of the SAS offering, coupled with deep domain expertise, led Chartis to name SAS as its category leader.

Of course, data management is the essential foundation for an enterprise approach. “A unified data platform that enables analysis of reliable and consistent information from across the organization will form the lynchpin of [financial crime risk management]FCRM in the future,” said Peyman Mestchian, Managing Partner at Chartis Research.

Chartis points to the importance of risk management systems being able to interact with other systems and handle large volumes of data. “Particular attention is given to the use of modern data management technologies, architectures, and delivery methods relevant to risk management (e.g. in-memory databases, complex event processing, component-based architectures, cloud technology, software-as-a-service),” all areas that are SAS hallmarks.

In fact, Forrester granted SAS the highest possible ranking in data integration – no surprise, given that SAS has been providing data management capabilities to financial institutions for nearly 40 years.

Truly integrating data management with advanced analytics and domain expertise is fundamental to support a holistic view of financial crimes risk.

Machine learning

According to Forrester, machine learning is one of the key factors that “now dictate which providers lead the pack.” Unlike rules-based systems, which are fairly easy to test and circumvent, machine learning adapts to changing behaviors in a population through automated model building. With every iteration, the algorithms get smarter and deliver more accurate results. It’s easy to see the value of machine learning to keep pace with evolving fraud tactics.

This is nothing new to SAS. Machine learning capabilities were built into SAS® fraud and compliance solutions from the beginning. SAS captures behavioral data from multiple entities and analyzes patterns every time a transaction is scored, helping firms isolate suspicious behavior and improve the customer experience for legitimate transactions. When the analytics can adapt to the changing behaviors seen in the data, the system is continuously improving and produces fewer and fewer false positives over time.

Although machine learning has been a popular buzzword in the past year, SAS has been incorporating machine learning techniques for decades, including in our fraud solutions.

Don’t take our word for it

To address the growing threat of fraud, many firms have created intelligence units that proactively identify complex risks using data visualization and entity link analysis built on big data architectures. The investments are substantial. So are the risks.

Choose carefully as you move forward to modernize your fraud and financial crimes strategy. The wrong solution could leave you mired in integration hassles and inconsistencies. It could annoy your customers with unnecessary inquiries about legitimate transactions. The right solution will enable you to prevent fraud sooner, rate client risk more accurately, and triage investigations more effectively.

For an impartial view of the options – and what you should expect from a leading vendor – check out The Forrester Wave™: Enterprise Fraud Management, Q1 2016, the Chartis Risk Tech Quadrant for Enterprise Fraud Technology Solutions 2016 – or other analyst reports listed in Analyst Viewpoints.

Learn more about SAS fraud and compliance offerings.

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About Author

James Ruotolo

Principal for Insurance Fraud Solutions

James Ruotolo is the Principal for Insurance Fraud Solutions in the Global Fraud & Financial Crimes Practice at SAS®. He is responsible for fraud detection and investigation management solutions for the property, casualty, life and disability insurance markets worldwide.

2 Comments

  1. Osman Meneses, Tarek on

    Could we see this for 2019, the graphic from Forrester Wave™: Enterprise Fraud Management, Q1 2016. really describes it!!

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