Agenda

To successfully drive innovation, governments need to foster collaboration between the public and private sectors, prioritize cybersecurity, and ensure that emerging technologies are implemented ethically and with a focus on inclusivity.

In this session, we'll discuss the foremost government initiatives globally achieved through the strategic implementation of cutting-edge technologies that drive innovation, improve public services, and address societal challenges.
 

Generative AI has revolutionized public sector service delivery by automating tasks, improving efficiency, and enhancing citizen engagement. However, like any transformative technology, the adoption of generative AI in the public sector comes with its share of challenges.

In this session, we'll explore how generative AI has impacted and revolutionized public sector service delivery, along with some of the challenges leaders face and strategies to overcome them.

This is a demo of an assistant for investigating Suspicious Transaction Reports leveraging an offline large language model and SAS' industry-leading investigation management solution. See how SAS uses prompt engineering

In this session, we'll discuss the developments and challenges of the regulatory landscape around privacy and AI in Singapore, ASEAN, and the wider Asia-Pacific region. The session will set the scene and will provide background as well as questions for the panel discussion that will follow.

Kalliopi Spyridaki, Chief privacy strategist, EMEA & Asia Pacific, SAS

Navigating the regulatory landscape for AI policy and privacy compliance in the Asia-Pacific (APAC) region involves understanding the diverse regulatory frameworks that countries within the region have established. While there is no one-size-fits-all approach, several common themes and trends can be identified.

In this session, we'll explore diverse approaches, emerging trends, and essential best practices for navigating complex compliance requirements in the dynamic regulatory landscape of the APAC region.

Kalliopi Spyridaki, Chief privacy strategist, EMEA & Asia Pacific, SAS

As AI continues to shape our societies and economies, building trust and ensuring transparency are critical imperatives.

This keynote will explore AI's future trajectory, emphasizing the pivotal role of trust and transparency in its evolution. By examining emerging trends, ethical considerations, and regulatory frameworks, we'll chart a path forward that fosters responsible AI development and engenders confidence among stakeholders.

Creating a climate risk scenario simulation framework involves systematically assessing and modeling the potential impacts of climate-related events on various aspects of an organization's operations. In this session, we'll discuss the structured way to determine the impact of climate risk on the business. Key discussion points include:-

• How does climate risk impact your business?
• How do you convert climate risk factors into well-known risk factors?
• How to develop scenarios?

Integrated Balance Sheet Management (IBSM) is a crucial component for financial institutions, providing a comprehensive approach to managing liquidity and interest risks together and optimizing the balance sheet. In this session, we'll explore why IBSM is so essential and the key challenges and benefits. Key conversation highlights include:

• How do banks incorporate Integrated Balance Sheet Management (IBSM) analytics in business decision-making?
• What are the main challenges encountered by banks in implementing IBSM analytics?
• Evolution of IBSM analytics and the importance of forward-looking scenario analysis with conditional balance sheet dynamics

Wilson Yap, Director & head of risk banking solutions, Asia, risk research and quantitative solutions, risk & finance advisory, SAS

AI in insurance risk management empowers insurers to make data-driven decisions, enhance operational efficiency in underwriting, pricing, and claims processing, and respond more effectively to emerging risks.

In this session, we'll explore how AI/ML plays a transformative role in insurance business process and risk management, revolutionizing how insurers assess, mitigate, and manage risks.
 

AI is now more used in the banking business, although many restrictions prevent AI from being used in the risk management area. While AI can bring significant benefits, it's essential to understand the practical applications and considerations when using it in risk management. Key discussion highlights include:-

• Where and how is AI used in risk management today?
• How does AI help to enhance the current risk management?
• What are the challenges encountered using AI?

Dr Terisa Roberts, Global solution lead – risk modeling and decisioning, SAS

In an era where digital transformation is paramount, financial institutions are challenged not only with enhancing credit risk assessment and fraud prevention but also with gaining deeper customer insights. This session delves into the integration of artificial intelligence (AI), machine learning (ML), large language models (LLM), and alternative data sources, including open banking, to forge a comprehensive enterprise decisioning framework. Key discussion highlights include:-

• How these technologies can revolutionize risk management
• How this technology detects fraud more effectively
• How these technologies can drive competitive advantage in digitalized banking

Dr Terisa Roberts, Global solution lead – risk modeling and decisioning, SAS

There's a buzz around AI and GenAI – but there are also many benefits to be gained. Both have applications that can be applied in Fraud and Financial crime. We’ll discuss the benefits realized with AI and the advances of GenAI. But it isn’t all about machines; it's also about how collective intelligence brings AI, systems, humans, and data intelligence together as complementary factors to combat financial crime.

Keith Swanson, director, Asia Pacific/Japan, global fraud, financial crime & security intelligence practice, SAS

Digital and remote channel activities are everything today. Neo or digital banks and other entrants are growing. But for all financial institutions, the attacks, compromise of customer data, and the resulting scourge of remote fraud are apparent.

In this session, we'll talk about the impacts and implications of scams from the perspectives of customers, financial institutions, and solution providers.

Ian Holmes, Global lead for enterprise fraud solutions, director, SAS

How do organizations move to real-time onboarding and originations? It starts with bringing data and decisions together within the customer lifecycle. In this session, we'll discuss and show how technology is helping financial institutions make better and faster decisions and how customers demand the promise of digital immediacy.

A pragmatic view on the new technology supporting better detection. We'll explore the main challenges and trends while sharing practical insights on how new technologies revolutionize detection.

Ahmed Drissi, APAC AML lead, SAS

Building on the earlier impacts and implications, this session will talk more about examples of specific scam issues and how SAS has worked with clients to address those challenges. We'll take a use case/case study view on how analytics/AI/ML, reference accounts, and social network analysis to identify mule accounts (both an AML and Fraud concern) can help the industry combat scams.

Ian Holmes, Global lead for enterprise fraud solutions, director, SAS

Building on the earlier session about advances in GenAI and general means of applying it, this session will highlight practical examples through a case study of how to apply this technology.

Keith Swanson, Director, Asia Pacific/Japan, global fraud, financial crime & security intelligence practice, SAS

Jason Loh, Head of technology futures, global technology practice AP, SAS

The future of AI and analytics powered by cloud technologies is expected to be dynamic and revolutionary, shaped by continuous progress in artificial intelligence (AI) and cloud computing.

In this session, business and technology leaders will discuss the increasing incorporation of AI into cloud platforms, its effects on IT strategies, operational hurdles, and what the future holds for AI-powered solutions.

Jason Loh, Head of technology futures, global technology practice AP, SAS
Michael Araneta, Lead for AWS banking GTM in Southeast Asia (ASEAN), Amazon Web Services

Our journey then ascends to the cloud, where the strategic integration between SAS and Red Hat OpenShift exemplifies the perfect marriage of analytics and cloud innovation. This partnership introduces a paradigm of 'build once, deploy anywhere,' fostering a seamless collaboration between data science and IT. It's a pivotal moment in our narrative, highlighting a shift towards accelerated deployment and the freedom to innovate across any environment.

Learn about SAS's strategic vision for Generative AI, which emphasizes ethical practices, human-centric innovation, and security. Focusing on three areas - Synthetic Data Generation, Digital Twins, and Large Language Models, SAS Viya unlocks transformative potential across industries, enhancing productivity and unlocking value in organizational data. Join us to explore how SAS, in partnership with Microsoft, is paving the way for a new era of trusted generative AI solutions.

Jason Loh, Head of Technology Futures, Global Technology Practice AP, SAS

Our exploration begins with the SAS Viya Workbench, a pioneering platform that propels data scientists beyond the boundaries of traditional analytics and machine learning development. By harmonizing SAS, Python, and R within beloved interfaces like Visual Studio Code and Jupyter Notebook, the Workbench catalyzes rapid, collaborative development, setting the stage for the next wave of AI & Analytics modeling.

Next, we immerse ourselves in a dynamic showcase of SAS Viya's generative AI capabilities, highlighting the role of Synthetic Data Generation and Copilots in democratizing AI. This segment illustrates how SAS Viya is dismantling traditional barriers to AI usage and access, offering a glimpse into a future where generative AI is an integral part of every analytics strategy, facilitating a seamless transition into advanced, data-driven operations.

At the summit, SAS Viya stands as a powerful aggregation of analytics, AI, and machine learning capabilities. Through the prism of software interfaces and practical applications, we explore the essence of modern solutions and Enterprise Customer Decisioning in action. SAS Viya is depicted not just as a tool but as a transformative force, enabling more profound insights and fostering quicker, more informed decision-making processes.