fraud detection

12月 022021

It’s a hard time to be a decision maker. Unexpected externalities like global pandemics, natural disasters and climate change make it harder to predict – and react to – everyday events. And that’s not just true for the world around us. The organizations we work within are more complex than ever, too.

The volume of communications and channels where we must meet customers and employees has grown exponentially – demanding our attention and reducing our focus. Not to mention added organizational complexity blurring the lines of roles and responsibilities according to geography, product and function.

Gaining control of such complexity requires rapid, streamlined and agile decision making. Technology that enables decision making needs to identify problems and take corrective action in real time to move quickly from questions to decisions.

SAS and Microsoft empower you to make better, faster decisions with unique enterprise decision management with SAS Intelligent Decisioning and Microsoft Power Automate using the SAS Decisioning connector – giving you the ability to design, deploy and manage automated decisions to improve the customer, employee and partner experience.

Enterprise decision management from SAS and Microsoft allows you to automate with a deliberate focus on decisions. You can combine business rules management with digital process automation and ModelOps, including model management and analytics, to accelerate the decision making process.

Together, Intelligent Decisioning and Power Automate unlock a breadth of use cases across the enterprise, including:

  • Insurance: Claims processing. Improve customer satisfaction and process claims faster. Receive insurance claims via Microsoft Power Apps and use Microsoft Power Automate to seamlessly ingest the claim into SAS Intelligent Decisioning. Using neural network models, SAS Intelligent Decisioning can analyze images of damage and compare with policies. If more information is required, Power Automate can trigger a flow to connect with a representative in Dynamics 365 Omnichannel for Customer Service. Once the decision is rendered, Power Automate can trigger process flows to notify the customer and deposit money into the bank account on file.
  • Banking: Credit decisioning. Reduce lender risk, improve decisioning response times and increase your bottom line. Build risk profiles in SAS Intelligent Decisioning by creating score cards and decision tables based off external data points, such as credit score, that assign each customer a risk rating. Use risk ratings to render decisions like home equity and line of credit approvals, and determine the loan amount. Once a decision has been made Power Automate flows can be used to communicate the loan amount to the customer and help them complete the loan agreement.
  • Retail/Banking: Fraud detection. Enable more secure transactions, reduce losses due to fraud and improve customer trust in your organization. SAS Intelligent Decisioning can identify fraudulent purchases and determine an appropriate course of action based on the level of confidence that a purchase is fraudulent. Power Automate can trigger automated reactions like alerting associated parties, denying a purchase at the point of sale, alerting the vendor, or sending notifications to the card holder.
  • Retail: Contextual Marketing. Increase marketing influence and become more customer centric by curating relevant and timely offers based on individual preferences. Use SAS Intelligent Decisioning to build a profile of tastes and preferences via geolocation, recommendation engines and market basket analysis. Use this profile to trigger Power Automate flows to send specific offers that align with important events, like birthdays or anniversaries, and send emails or push notifications to customers with unique, context-specific offers.

To learn more about what SAS Intelligent Decisioning and Microsoft Power Automate can help you achieve, visit

4 ways to make better, faster decisions with enterprise decision management from SAS Viya on Azure was published on SAS Users.

8月 262020

Fraud, waste and abuse (FWA) ravages the US health care system. Estimates from the National Health Care Anti-Fraud Association show fraud costs health care organizations $70 billion to $230 billion each year. The precise figure is unknowable because only 3 to 10% of this fraud is ever detected. With more [...]

Catch a fraudster: Finding the needle in the haystack with AI was published on SAS Voices by Alyssa Farrell

4月 122018

The financial services industry has witnessed considerable hype around artificial intelligence (AI) in recent months. We’re all seeing a slew of articles in the media, at conference keynote presentations and think-tanks tasked with leading the revolution. AI indeed appears to be the new gold rush for large organisations and FinTech [...]

AI for fraud detection: beyond the hype was published on SAS Voices by Sundeep Tengur

3月 152018

fraud detectionIn the medical field, an autopsy is valuable because it helps you understand the cause of death. But, what’s more valuable is identifying the leading indicators of an illness so that you can address it before the Grim Reaper comes knocking. Best in class organizations are taking a similar approach to their fraud detection, shifting from a purely hindsight view to insights and even foresight – getting out in front of the fraud before it happens, revenue is lost, reputation damaged and regulators apply even more pressures.

Proactively detecting fraud isn’t easy though. There is the nature of the challenge itself: Fraud is a behavioral problem and one that is dynamic, complex and often sophisticated. Then, there is the data challenge – lots of it and in many different formats, including structured and unstructured. Next is the analytics. There are many techniques available, and some might be good, and others not. Finally, the technology. There is no shortage of solutions, but they can be expensive and organizations need to beware of ending up with a collection of siloed, single-point solutions that don’t tell the full story.

That said, unless you’re willing to close your business, which is the only surefire way to get to 0% fraud, you’ve got to tackle it.

How to tackle fraud?

For starters, I advise leaders to define their risk appetite and tolerance. What is the level of risk that you – and the organization – can live with? If you can live with 5%, let’s say, then that’s your true North and benchmark to measure against. Once the risk appetite is set, next comes the balancing act of strategic long-term view and tactical short-term needs plus balancing fraud prevention against the customer experience, and more. Then, make sure you have the data, technology, people, processes, governance and analytics in place to continuously measure and refine.

What we are seeing today is that analytics is a key component of moving fraud detection from hindsight to foresight. It starts with dividing risk into three classes. The first is what you know. I have fraud, it’s happening, and I can put business rules in place to detect it. It’s a repeatable pattern that usually responds well to the “if x, then y” formula. The second class is what you do not know.  This is about anomaly detections and can often be found by highlighting things that don’t happen often, but stand out when they do. The third, and most challenging class, is when you don’t even know what you’re looking for. Is it a needle in a haystack? Maybe a rusty nail? This is where AI and ML come in play.

Applying best-in-class tools allows organizations to ingest enormous sets of data, including text, voice, social, structured and unstructured data. Adding best-in-class analytics helps to sort the noise from signals, and advanced analytics including Artificial Intelligence, Machine Learning and Natural Language Processing enable organizations to move faster, by processing in real time, and benefit from iterative learning, where humans help models become smarter and smarter until they can improve themselves every single time. And, of course, the best solutions provide an end-to-end analytics lifecycle from data to analytics to insights.

There’s no question that fraud is complex and challenging, but unless you’re willing to send your business to the morgue – and close your doors forever – you’ve got to tackle it. And, thanks to advances in analytics, we can help stop fraud before it starts.

Find out more at the SAS Global User Forum 2018

Join Constantine Boyadjiev for his “Suspect Behavior Identification through Sentiment Analysis and Communication Surveillance” Breakout Session at SAS Global Forum 2018 April 10 at 3 p.m. in Mile High Ballroom Theater C.





Move fraud detection from hindsight to insight to foresight was published on SAS Users.

6月 072016

To some people, electricity is like air: There for the taking. For others, circumventing paying a utility bill is a just cause, sticking it to “Big Energy” for their perceived transgressions against their customers. In either case, not paying for energy is considered fraud and a crime. In some states […]

Fraud detection is like crime fighting, only geekier was published on SAS Voices.

4月 142016

Across the globe, governments are losing billions in revenues to organised VAT fraud. The most recent VAT Gap study published by the European Commission estimates that EU countries lost an estimated €168 billion in VAT revenues in 2013. That's equivalent to 15.2% of the total expected VAT revenue from the […]

Attention VAT fraudsters: You’re no match for analytics! was published on SAS Voices.

8月 112015

As technology and analytics continue to evolve, we're seeing new opportunities not only in the way that we analyze data, but also in deployment options. More specifically, real-time deployment of analytical algorithms that enable organizations to detect and respond to security threats, offer timely incentives to customers, and mitigate risk by detecting compliance […]

The post Streaming Text Analytics: Finding value in real-time events appeared first on The Text Frontier.

11月 212014
Every day there are news stories of fraud perpetrated against federal government programs. Topping the list are Medicaid and Medicare schemes which costs taxpayers an estimated $100 billion a year. Fraud also is rampant in other important federal programs, including unemployment and disability benefits,  health care, food stamps, tax collection, […]
3月 182014
New versions of JMP Clinical and Genomics are available starting today, so I wanted to take the opportunity to give a brief overview of some of the new features you’ll come to enjoy with the new release of JMP Clinical 5.0. Below are seven things to love! 1. Risk-Based Monitoring [...]