Unlock the power of analytics in finance
Sharpen decisions.
Strengthen compliance.
Future-proof your workforce.
Strengthen financial strategy with analytics expertise.
SAS Finance Case Studies bring analytics to life in the banking and finance sector, helping your analysts, data scientists, and risk teams apply SAS tools directly to real-world challenges in risk, compliance, credit, and customer analytics.
Why finance teams trust SAS
Gain practical, measurable impact
Every module connects directly to your organization’s business goals:
- Banking & finance: Fraud detection, real-time trading analysis, compliance monitoring.
- Accelerate reporting and decision cycles
- Reduce manual risk and compliance tasks
- Enhance accuracy through data automation
- Strengthen governance with data-driven audit trails
Training designed for finance professionals
Who should attend:
- Business Analysts & Data Scientists – Apply analytics to real banking cases
- Risk, Compliance & Credit Teams – Automate and improve risk models
- IT & Data Engineers – Master data preparation for analytics and reporting
Develop future-proof teams
Equip your organization to adapt to change with analytics skills that drive agility and resilience, from automating credit processes to building predictive dashboards that support regulatory compliance and risk mitigation.
Empowering your teams to excel
Tailored for the Financial Sector. Built for professionals with existing analytics skills. Participants use their knowledge of SAS Programming, Visual Analytics, Macro Language, and SQL to work with authentic financial data and solve practical banking and risk scenarios they recognise from their daily work.
Real-world relevance
Authentic banking datasets ensure direct application to your challenges
Regulatory readiness
Build strong data foundations that support compliance and audits
Actionable insights
Create dashboards that drive smarter business decisions
Elevated risk practices
Apply analytics for credit risk, churn, and bias detection
Certification alignment
Supports SAS certification for individual and team growth
Future-proof skills
Stay ahead of market and regulatory changes
Designed for modern finance challenges
The financial sector is evolving rapidly, from new compliance standards to digital transformation pressures. Upskill your teams today to stay competitive, reduce operational risks, and accelerate data-driven innovation.
Explore SAS experiences tailor-made for you
SAS® Visual Analytics 1: Finance case study
This case study introduces learners to SAS Visual Analytics by guiding them through the exploration and analysis of customer data from Orion Star Bank. The focus is on building foundational skills in data visualization, report creation, and dashboard design to support business understanding and decision-making.
Learn How To:
- Explore and visualize customer demographics and business performance.
- Analyze social media influence and product usage patterns.
- Identify and address data quality issues.
- Build comprehensive reports and dashboards.
- Use interactive filters and custom categories for deeper analysis.
Who Should Attend:
- Beginners and new users of SAS Visual Analytics.
- Business analysts and professionals seeking to create basic reports and dashboards.
- Anyone interested in data-driven insights for financial services.
Study Description:
- Analyze customer demographics, income, education, and social media influence.
- Evaluate business performance and customer trends over time.
- Identify and visualize data quality issues.
- Build dashboards summarizing key findings and actionable insights.
- Create interactive reports with filters, prompts, and drill-down capabilities.
Prerequisites:
- Course SAS Visual Analytics 1 for SAS® Viya: Basics or equivalent foundational knowledge.
Visual Analytics 2: Finance case study
This case study enables learners to apply advanced SAS Visual Analytics skills to real-world financial data from Orion Star Bank. Participants explore, prepare, and analyze customer and transaction data, focusing on uncovering business trends, identifying data quality issues, and building dashboards to support strategic decision-making.
Learn How To:
- Explore and prepare large, complex financial datasets for analysis.
- Identify and visualize business trends and revenue changes.
- Detect and report on data quality issues.
- Build interactive dashboards for management and operational use.
- Integrate external data (e.g., state population) for deeper insights.
- Apply advanced filtering, aggregation, and visualization techniques.
Who Should Attend:
- Users who have completed SAS Visual Analytics 1 and want to deepen their skills.
- Analysts and business professionals seeking to create impactful dashboards and reports.
- Anyone interested in advanced data visualization and business intelligence in finance.
Study Description:
- Investigate and prepare transaction data for analysis.
- Explore and analyze operational history, revenue trends, and geographical patterns.
- Build dashboards to highlight business performance, customer segments, and product opportunities.
- Create data quality dashboards to monitor and flag issues.
- Integrate external datasets and perform advanced data joins.
- Design dynamic, filterable reports for management and marketing.
- Develop interactive dashboards with multiple pages and pop-ups for detailed insights.
Prerequisites:
- Course SAS® Visual Analytics 2 for SAS® Viya®: Advanced or equivalent foundational knowledge.
SAS Programming 1: Finance case study
This case study guides learners in applying SAS programming skills to realistic financial data scenarios. Participants work with data from a simulated bank, focusing on the importance of data-driven analysis for business decisions, risk management, and stakeholder reporting. The course highlights why SAS programming is essential for supporting organizational goals in the financial sector.
Learn How To:
- Analyze customer, product, and financial data to solve business problems.
- Explore, validate, and prepare data for meaningful insights.
- Report findings to stakeholders with varying technical backgrounds.
- Assess risk and profitability using real-world datasets.
- Export results for non-technical audiences.
- Use SQL in SAS to combine and query data from multiple sources.
Who Should Attend:
- SAS programmers who have completed SAS® Programming 1: Essentials.
- Analysts seeking practical experience with business-focused financial data.
- Anyone interested in understanding the impact of data analysis in banking.
Study Description:
- Import, examine, and report on customer and product data.
- Analyze customer demographics, calculate statistics, and create dynamic reports.
- Clean and transform data, calculate profit, assess risk scores, and prepare marketing lists.
- Identify low-profit products, report on top customers, and use macro variables for dynamic reporting.
- Export selected data to Excel for stakeholders.
- Join tables and create reports using SQL.
Prerequisites:
- Course SAS® Programming 1: Essentials or equivalent foundational knowledge.
SAS Programming 2: Finance case study
This case study challenges learners to apply SAS Programming 2 data manipulation techniques to real-world banking data. Participants prepare, clean, and analyze data to generate reports for management and marketing, focusing on practical business questions and data quality.
Learn How To:
- Explore and validate large financial datasets.
- Prepare and clean data for reporting and analysis.
- Merge, filter, and transform data using advanced SAS programming.
- Generate business reports and answer operational questions.
- Analyze social media influence and product usage.
- Export results and automate reporting tasks.
Who Should Attend:
- SAS programmers who have completed SAS Programming 1 and want to advance their data manipulation skills.
- Data analysts and reporting professionals in finance.
- Anyone interested in practical SAS programming for business applications.
Study Description:
- Explore product, contract, and customer data for quality and consistency.
- Prepare and split datasets into valid and invalid records.
- Identify social media influencers and high-risk customers.
- Analyze household structures and prepare targeted marketing lists.
- Generate Excel reports on product usage and profitability.
- Analyze revenue and cost by product and product group.
- Create dynamic reports using macro variables and advanced data steps.
Prerequisites:
- Course SAS® Programming 1: Essentials and
SAS® Programming 2: Data Manipulation Techniques
or equivalent foundational knowledge.
Macro Language 1: Finance case study
This case study places learners in the Analytics and Reporting department of a bank, where they use SAS Macro Language to automate and streamline key business processes. The focus is on improving efficiency in generating personalized customer communications and reports for financial products, such as identifying customers at risk of churn and supporting targeted marketing efforts.
Learn how to:
- Automate repetitive reporting and communication tasks in a banking environment.
- Build macros to generate customer emails and assemble client information for financial product offers.
- Validate and standardize macro parameters for robust automation.
- Integrate macro solutions into real-world financial data workflows.
Who Should Attend:
- SAS programmers seeking to automate business processes in finance.
- Analysts supporting customer engagement and retention initiatives.
- Anyone interested in scalable automation for financial reporting and communication.
Study Description:
- Automate customer email generation for financial product offers.
- Create macros for assembling customer information.
- Validate macro parameters and handle errors in business processes.
- Integrate macros with data-driven financial reporting.
- Test and debug macro programs in real-world banking scenarios.
Prerequisites:
- Course SAS® Macro Language 1: Essentials or similar knowledge
SQL 1: Finance case study
This case study immerses learners in the Credit Risk department of a bank, using SAS SQL to prepare, clean, and analyze financial data for credit risk modeling and business reporting. The focus is on supporting fair and effective credit decisions by ensuring high-quality data and uncovering insights into customer behavior and risk.
Learn How To:
- Access, explore, and validate customer and risk data for credit analysis.
- Integrate and clean financial datasets to support credit modeling.
- Detect and address data quality issues relevant to credit risk.
- Calculate financial and risk metrics to inform business decisions.
- Build and score predictive models for credit default.
Who Should Attend:
- SAS programmers and analysts working in credit risk or financial analytics.
- Professionals supporting data-driven decision-making in banking.
- Anyone seeking practical experience with SQL for financial data preparation and analysis.
Study Description:
- Access and explore customer demographics and risk scores.
- Validate and clean data for credit risk analysis.
- Integrate multiple financial datasets for modeling.
- Analyze bias, risk, and financial indicators in credit decisions.
- Build and score logistic regression models for credit default prediction.
Prerequisites:
- Course SAS® SQL 1: Essentials or similar knowledge
Register Your Interest
Learn how SAS Finance Case Studies can be tailored to your organisation’s goals.
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