SAS VIYA 4  |  FINANCIAL CRIMES SAS Viya Copilot Prompt Library for Financial Crimes Reusable prompts for finding suspicious patterns, investigating connected activity and operationalizing fraud decisions with SAS Viya Copilot. Jump to a section Data Governance Data & AI Studio Model Studio Model Manager Visual Analytics Visual Investigator Fraud Decisioning BEFORE YOU START Use these prompts as starting points. Replace example table names, variables, thresholds, projects, investigative objects, organizations and rule assets with values from your SAS environment. Review before operational use. Review generated code, analytical recommendations, investigative summaries and fraud rules before relying on the output. GOOD TO KNOW Adapt to your environment. Available capabilities, data, variables, permissions and outputs depend on your SAS environment and application context. Copilot-generated analytical recommendations, code and investigative summaries should be reviewed and validated by qualified users before operational use.   SAS Viya Copilot in SAS Data Governance   Create a trusted financial-crime data foundation   Back to top ↑ EXAMPLE ACTIVITY Identify governed customer, account, transaction, counterparty and risk-indicator data for a financial-crime analysis. GOVERNED DATA FOUNDATION USE CASE PROMPT EXPECTED OUTPUT Find customer and account data “Find governed data assets containing customer and account information for a financial-crime analysis.” A list of potentially relevant governed data assets. Find transaction data “Find data assets that contain transaction amount, date and time, channel and counterparty information.” A list of potentially relevant governed data assets. Find geography and risk data “Find data assets that include geography, country and customer risk-indicator information.” A list of potentially relevant governed data assets. Find counterparty and payment data “Find data assets related to counterparties, beneficiaries and payment channels.” A list of potentially relevant governed data assets. Find data for a specific analysis “Find data assets I can use to detect unusual transaction behavior across accounts.” A list of potentially relevant governed data assets.   SAS Viya Copilot in SAS Data and AI Studio   Prepare and explore the data   Back to top ↑ EXAMPLE ACTIVITY Generate and explain code to profile, join and prepare customer, account and transaction data. Use SAS Data Governance first to find the relevant tables. DATA PREPARATION & CODE ASSISTANCE USE CASE PROMPT EXPECTED OUTPUT Get product help “Explain how to remove duplicate rows from a table in SAS Data and AI Studio.” Provides a step-by-step explanation based on SAS documentation. Profile data with code “Generate Python code to identify missing and duplicate records in a dataset.” Generates Python code to run and assess. Join tables “Generate SAS code to join tables [table X], [table Y] and [table Z] and keep the amount, date and time, channel, geography and counterparty variables.” Generates SAS code to review, run and adapt. Engineer features “Generate SAS code to calculate transaction count and average transaction amount per account for each 30-day period.” Generates SAS code for behavioral features. Understand code or flows “Explain what this code or flow does.” Explains the code or flow in plain language.   SAS Viya Copilot in SAS Model Studio   Detect unusual behavior   Back to top ↑ EXAMPLE ACTIVITY Develop a model that identifies customers or accounts with unusual combinations of transaction frequency, amounts, counterparties or behavioral changes. MODEL DEVELOPMENT USE CASE PROMPT EXPECTED OUTPUT Understand the project “Summarize this financial-crime detection project, including models, versions, champion model, available performance information and publishing status.” Summarizes the project and its registered models. Compare candidates “Compare the models in this project and explain the differences between them.” Compares registered model candidates. Manage the champion “Set [model name] as the champion model for [detection project].” Sets the requested champion designation subject to supported confirmation. Monitor performance “Summarize the latest available performance-monitoring results. Highlight material changes in performance or input data that require review.” Highlights available performance or data changes. Publish approved model “Publish the approved champion model to [publishing destination] and report the resulting status.” Publishes the supported model and reports its status.   SAS Viya Copilot in SAS Model Manager   Govern and operationalize models   Back to top ↑ EXAMPLE ACTIVITY Register and manage a detection model so its versions, champion status, monitoring information and publishing status can be governed. MODEL GOVERNANCE & OPERATIONALIZATION USE CASE PROMPT EXPECTED OUTPUT Explore suspicious activity “Analyze the detection results and identify notable patterns by transaction type, customer segment, geography, channel and time.” Summarizes notable patterns and suggested areas for analysis. Create a hotspot report “Create a report showing where anomalous activity is concentrated by geography, transaction type and customer segment. Include filters for date, channel and risk level.” Creates a proposed report containing relevant visualizations and controls. Examine trends “Show how the volume and value of anomalous transactions change over time. Break results down by channel and transaction type.” Shows time-series visualizations and summarizes relevant changes. Compare segments “Compare anomalous activity across customer segments using flagged transactions, total value and available risk measures.” Shows comparative visualizations and explains differences. Explain a report “Explain the key insights in this report, including concentrations of anomalous behavior and patterns warranting further investigation.” Explains the report’s principal findings.   SAS Viya Copilot in SAS Visual Analytics   Understand patterns and hotspots   Back to top ↑ EXAMPLE ACTIVITY Create visualizations showing concentrations of anomalous behavior by transaction type, customer segment, geography and time. PATTERNS & HOTSPOTS USE CASE PROMPT EXPECTED OUTPUT Summarize findings “Summarize the key entities, transactions and relationships identified in this investigation. Separate observed facts from indicators requiring validation.” Separates observed facts from indicators. Retrieve object details “Show [customer name]’s date of birth from the object record.” Returns the requested authorized object-record value. Explore networks “Show the customers, accounts, counterparties and transactions connected to this account.” Shows connected entities and relationships. Navigate records ▸ Switch to [customer name]. Switches the active view to the selected object or tab. Search parties “Show me any people with the surname [surname].” Lists objects matching the search criteria. Locate a party “Do we have any information on [customer name] from [location]?” Returns matching records or reports no match. Find linked claims “Show any open claims associated with this object or its linked objects.” Summarizes related open claims from available data. Get product help “Explain how to create a relationship between objects in SAS Visual Investigator.” Provides a step-by-step explanation based on available product documentation.   SAS Viya Copilot in SAS Visual Investigator   Investigate connected activity   Back to top ↑ EXAMPLE ACTIVITY Start with an anomalous account, expand its network and determine whether the activity appears isolated or connected to a broader network. CONNECTED ACTIVITY INVESTIGATION USE CASE PROMPT EXPECTED OUTPUT Explore the network “Show the customers, accounts, counterparties and transactions connected to this account. Highlight shared attributes and repeated relationships.” Shows connected entities and their relationships. Identify important connections “Which connections in this network warrant closer review based on transaction frequency, value, timing, shared attributes or proximity to other alerted entities?” Prioritizes connections using information available in the investigation. Develop investigative summary “Summarize the key entities, transactions and relationships identified in this investigation. Distinguish observed facts from analytical indicators that require validation.” Separates established evidence from indicators requiring review. Identify next investigative steps “Based on the information currently available, what entities, relationships or transactions should an investigator review next, and why?” Suggests follow-up areas tied to available evidence and network relationships.   SAS Viya Copilot in SAS Fraud Decisioning   Uncovering Fraud   Back to top ↑ EXAMPLE ACTIVITY SAS Viya Copilot for Detection Architecture DETECTION ARCHITECTURE USE CASE PROMPT EXPECTED OUTPUT Understand available data “What is the current message schema for this rule?” Shows the available message schema and profile variables. Understand relevant variable “What is ‘minutes since last mobile event,’ and how can I use it in a fraud rule?” Explains the profile variable and how it may be used in rule logic. Generate a fraud rule “Can you help me write a rule? If the message is an ATM withdrawal that is not being made in the cardholder’s home country and the amount >400 then decline the message and generate an alert.” Generates DS2 rule code using available variables. Understand a fraud rule “Explain what this code means.” Explains the rule’s conditions and resulting action. These prompts are starting points. Adapt table names, variable names, thresholds, project names and business terminology to match your data and SAS environment. Review and validate Copilot-generated analytical recommendations, code and investigative summaries before operational use. ... View more

I open SAS.   I submit a macro (just submit it, so nothing happens except it puts the macro into memory).  A line in the macro points to a formats library.   I call the macro, so the guts of the macro runs.   When the macro runs it creates a dataset.  After running the macro I do a PROC FREQ on that dataset.  All the formats are applied correctly.   Then I call the macro again.  I do not submit the macro itself again, rather I just call (run) it.  I change nothing and I do nothing else.  All I do is call the macro a second time.   Then I do that same PROC FREQ mentioned above and this time some...not all, but some...of the formats are not applied.   So the 1st time I run the PROC FREQ I see all words (the formatted values) instead of their underlying numbers.   And the 2nd time I run the PROC FREQ I still see mostly words (the formatted values), but for some of them I see their underlying numbers instead.   And every subsequent time I run it I see the mostly words but some underlying numbers instead.   IOW, it works properly after I open a new SAS session and run it for the first time.   And it doesn't work properly every subsequent time I run it.   Any idea? ... View more

You know what's better than hosting a TASUG meeting and bringing SAS users together to learn and inspire? Watching people who were there share insights afterward. ... View more

What if your first major career experience let you build technology, lead student programs and collaborate across countries, all at the same time?   It began with a LinkedIn scroll. I spotted an opportunity with the SAS CareerStart Program and immediately recognised the kind of work I already loved: connecting with students, running events and hackathons, building communities and making technology easier to understand. As a Computer Science student, I expected the technical work to challenge me. What I did not expect was how much I would also learn about people, communication and turning ideas into experiences that genuinely help others. Why the CareerStart@SAS Program stood out The opportunity felt bigger than a traditional early-career placement. It offered the chance to work with colleagues and education partners across countries, learn through mentoring and one-to-one development, and contribute to projects with visible outcomes for students and educators.  The role also matched the experiences I had built at university through student organizations, technical webinars and cross-campus activities. I knew I could bring those skills with me, while stretching well beyond my comfort zone.        Turning ideas to APAC-wide impact When I joined SAS, I quickly became involved in a variety of projects across the Asia-Pacific region. In practice, this meant working on several initiatives at once: Presenting live enterprise analytics demos at four APAC events to more than 370 students and faculty Running an APAC-wide hackathon that attracted more than 500 registrations and was built around SAS Viya for Learners Developing joint capstone projects with RMIT, the University of Canberra, and UNSW Designing a course recommendation engine that personalizes learning pathways for students Testing how SAS Viya for Learners works with the SAS Extension for VS Code, REST APIs, and the Model Context Protocol (MCP), while documenting the first viable workflows for these integrations Volunteering with Girls in Tech in Sydney and Melbourne to support girls and young women pursuing careers in technology Supporting academic opportunities and partnerships in the Philippines  The biggest lesson: technical skills help you build a solution, but curiosity about the person using it is what makes the solution useful. Learning to build without a perfect playbook Two projects especially shaped my experience. My cohort helped bring the SAS Viya for Learners Challenge to APAC. We had a useful foundation from the Australia and New Zealand event, but a regional rollout introduced new questions that we had to solve on our own during the event. We captured our learnings so future cohorts can build on them and scale the program further. The Model Context Protocol integration work to SAS Viya for Learners free software was similarly exploratory. There was no step-by-step answer waiting for me. I tested different approaches, identified viable workflows and documented the process for the people who would continue the work. That experience taught me that progress often begins with a willingness to experiment. More than technical experience At first glance, this might not seem like a typical Computer Science role. But I discovered that my degree was just as valuable when translating complex technology into something relevant and accessible for students as it was when working directly with code and tools. The goal was not only to explain how the technology worked, but also to show students how it could help them complete university projects, develop practical skills, and improve their employability. That mindset inspired the course recommendation engine. Instead of asking only, “Can I build this?”, I asked, “What would encourage a student to discover a useful course they might otherwise miss?” The technical build mattered, but understanding the learner made it meaningful. At the same time, the internship accelerated my own technical growth. Although I only began learning SAS Viya and Base SAS when I joined SAS, the experience gave me the confidence to pursue certifications and continue expanding my skills. In many ways, I was learning alongside the students I hoped to support. 3 Lessons I will take forward Looking back, three lessons stand out from my internship experience. 1. Stay Curious About Your Audience Students often know more than we assume. The strongest programs begin by understanding what people already know, what they need next and how to build from there. 2. Focus on Authentic and Accountable Applications In industry, the important question is not only how a technology works. It is how it can solve a real problem. That requires testing, understanding limitations and communicating value honestly. 3. Bring Your Passion to a Wider Stage Working with colleagues across countries exposed me to new perspectives, cultures and ways of collaborating. Diverse teams do more than broaden your network. They strengthen ideas.       My advice to students Be open to learning beyond your technical specialty. The moments that stretch you often become the ones that shape you most. Volunteer for the presentation. Ask the extra question. Test the uncertain idea. Work with people whose experiences are different from yours. Most importantly, focus on creating value for others. The SAS CareerStart Program showed me that technical skills and human understanding are not competing strengths. Together, they are what turn knowledge into impact. Ready to explore what your own CareerStart journey could look like? Learn more about the internship program: https://www.sas.com/en_ph/careers/students-and-graduates/internships-and-fellowships.html Join the SAS student community: https://communities.sas.com/t5/SAS-Communities-Library/FAQ-for-students-and-independent-learners/ta-p/728270   ... View more

A new update is available for Base SAS , version 9.4_M8 : Hot Fix: M4B023 - Published 10NOV2026 , Download link for M4B023 Component name: Base SAS Related SAS release: SAS 9.4   Issues addressed in M4B023 SAS Note 70504 Support for the IBM "System SSL" for z64 KB0060696 The HTTP procedure fails with "ERROR: Unable to read data from Web server. Retry is not available. This list of notes might be incomplete. For a complete list of issues addressed by this hot fix, visit the hot fix page for M4B023   Note: A comprehensive list of all SAS hot fixes is available from support.sas.com. You can use the SAS Hot Fix Analysis, Download, and Deployment (SASHFADD) tool to manage your SAS hot fixes. ... View more