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Absa Bank Modernizes Credit Risk Management Reporting with SAS - AI-driven automation with SAS Viya on AWS accelerates reporting while enhancing compliance and model governance - Absa.africa / SAS.com
Absa Bank Modernizes Credit Risk Management Reporting with SAS

 

PRZOOM - /newswire/ - Cary, NC, United States, 2026/08/05 - AI-driven automation with SAS Viya on AWS accelerates reporting while enhancing compliance and model governance - Absa.africa / SAS.com.

   
 
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Absa Bank, one of Africa's largest financial institutions, understands that each credit decision represents someone's next chapter. Amid rising customer expectations and regulatory demands, the bank teamed with SAS, a global leader in data and AI, to modernize its credit risk management infrastructure. The result: faster, more transparent and reliable lending and better outcomes for the people Absa serves.

The credit risk management system built on SAS® Viya®, the company’s data and AI platform, and running on Amazon Web Services (AWS) has reduced reporting cycles by 80% to 90% from weeks to hours. It also helps the bank roll out new models 50% faster than before.

“Absa’s adoption of SAS Viya on AWS has transformed model risk management from a back-office function into a forward-looking strategic advantage,” said Stu Bradley, Senior Vice President of Risk, Fraud and Compliance Solutions at SAS. “The focus on governance is helping streamline AI innovation, and this evolution enables faster, more reliable credit decisions, improves loss predictability and strengthens regulatory compliance for Absa.”
Next-gen model governance drives precision and performance

With more than 500 credit risk models supporting its retail portfolio, Absa recognized that delays in model monitoring and updates could adversely impact capital reserves, loss forecasts and regulatory compliance. The bank’s legacy system reliant on manual scripts and siloed processes was unsustainable.

“Model monitoring is a vital part of our model governance,” said Dewald Fourie, Modeling Data Scientist at Absa. “Previously, analysts spent up to four weeks generating a single report. Now, with SAS Viya on AWS, we’ve automated the process and shifted our focus to strategic analysis and innovation.”

The benefits of Absa’s new SAS-powered capabilities on AWS extend far beyond efficiency:

• 80% to 90% reduction in reporting time: Model monitoring reports are now generated automatically.
• 50% faster onboarding of new models: New frameworks (including all associated approvals) now go live in less than six months.
• Strategic reallocation of talent: Analysts once bogged down in manual work are now focused on higher-value projects.
• Elastic cloud usage: Instead of idle server capacity, resources now scale dynamically to meet demand paying only for what’s used.
• Built-in AI guidance: The automated “Insights” feature of SAS Viya surfaces recommendations for further optimization.

To lead the transformation, Absa established a Center of Excellence and partnered with SAS to rebuild its monitoring framework. The new system delivers:

• Standardized reports and dashboards across all models.
• Automated execution to reduce human error and manual effort.
• Real-time insights for business and regulatory stakeholders.

“With SAS Viya on AWS, we turned a once dull-but-necessary manual function into an automated strategic capability,” said Fourie. “We now deliver faster, more reliable credit decisions while improving loss predictability and ensuring regulatory compliance.”

Absa’s success has sparked broader innovation across the bank, with plans to apply the same data and AI-driven approach to other areas of operations.
Credit risk management: The foundation of financial resilience

Effective credit risk management is essential for banks and financial services firms because it directly influences both profitability and reputation. By striking the balance between prudent lending and responsible risk-taking, institutions can sustain growth while minimizing exposure to losses from defaults or poor credit decisions.

Absa’s modernization illustrates this balance in action, supported by SAS’ proven leadership in credit risk solutions. Backed by SAS’ Category Leader distinction across seven quadrants in Chartis Research’s recent Credit Risk Management Solutions, 2025: Quadrant Update, Absa exemplifies how a data-driven governance framework can help firms strengthen performance, resilience and customer confidence, while laying the foundation for continued innovation across the enterprise.

About Absa Bank
Absa Group Limited (‘Absa Group’) is listed on the Johannesburg Stock Exchange and is one of Africa’s largest diversified financial services groups. Absa Group offers an integrated set of products and services across personal and business banking, corporate and investment banking, wealth and investment management and insurance.

Absa Group (absa.africa) owns majority stakes in banks in Botswana, Ghana, Kenya, Mauritius, Mozambique, Seychelles, South Africa, Tanzania (Absa Bank Tanzania and National Bank of Commerce), Uganda and Zambia and has insurance operations in Kenya and South Africa. Absa also has representative offices in the People’s Republic of China, Namibia, Nigeria and the United States, as well as securities entities in the United Kingdom and the United States, along with technology support colleagues in the Czech Republic.

About SAS
SAS (sas.com) is a global leader in data and AI, helping organizations make confident decisions with AI they can trust. For decades, SAS has set the standard for delivering software that drives meaningful impact, incorporating deep industry expertise, transparency and governance. SAS gives you THE POWER TO KNOW®.

SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. ® indicates USA registration. Other brand and product names are trademarks of their respective companies. Copyright © 2026 SAS Institute Inc. All rights reserved.

 
 
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Absa Bank Modernizes Credit Risk Management Reporting with SAS

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