Name: Automation and optimization of Retail Credit risk policies/processes with advanced risk analytics
Start: 2024-10-09T07:09:00Z
End: 2024-10-09T07:09:24.000Z
Location: BrightTALK
Rating: 0

SAS is a global leader in AI and analytics software, including industry-specific solutions. SAS helps organizations transform data into trusted decisions faster by providing knowledge in the moments that matter. SAS helps clients across industries address their most critical and complex analytical challenges through SAS Viya, our cloud-native AI, analytic and data management platform.

From helping our customers fight fraud and mitigate risks through our fraud, anti-money laundering, security intelligence and risk management solutions, as well as helping drive engagement through our customer intelligence solutions, SAS delivers innovative solutions to enable our customers achieve greater productivity, performance and trustworthiness.  

EDB has embarked on a journey to deploy SAS Viya 4 with Multitenancy to service Government agencies across Singapore as part of our national Innovative digital transformation strategy, addressing the challenges of optimizing data management within the GCC framework.

This session showcases the strategic adoption of SAS within GCC infrastructure to facilitate efficient and collaborative governance in the digital age.

SAS Viya 4 Experience in GCC. Deploying SAS Viya with Multitenancy for Cross-Government Usage

The qualities of productivity and performance delivers incredible power, and to effectively leverage this power it must be trustworthy. Hear how SAS is delivering the most trustworthy AI platform on the planet.

Delivering Trustworthy AI

We'll use a case study to illustrate how data and decisioning are simplifying onboarding and origination activities like customer screening, application fraud, credit risk decisioning, and customer risk assessment. We'll dive into the customer experience, technology execution, and operational impact in driving immediate results for customers. What does this mean for organizations today, and where could they be?

[Problem & Answer] Making Customer Engagement simpler, immediate and efficient

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.

How to Address the Complexity of Sanctions in 2024

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.

Simplifying Onboarding and Originations across Fraud, AML, and Risk

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.

This session will explore how AI/ML plays a transformative role in insurance business processes and risk management, revolutionizing how insurers assess, mitigate, and manage risks.

[Panel Discussion] Future of Insurance Risk: Transforming Insurance Risk Capability to Truly Embed Risk Culture

SAS is helping developers "get more done", deliver more value, and work more efficiently. See how SAS is delivering unique capabilities to boost productivity and provide developers with the choices they require.

Experience a true Pythonic environment optimized for performance, complete with streamlined packages. Discover how we solve missing data with Synthetic Data Generation, publish your models into the SAS Viya Enterprise ecosystem, blending the best of open source and SAS's robust capabilities.

Unveil SAS CodeGen to rapidly produce and document SAS code, provide explanations, and achieve higher productivity through a streamlined programming experience.

The SAS Developer Experience

This session will talk 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.

[Problem & Answer] Practical Strategies and Techniques for Combatting Scams

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

[Panel Discussion] Navigating the Future: The Critical Role of Integrated Balance Sheet Management

Optimize AI model lifecycles and transform data into strategic decisions using SAS Viya. Learn to enhance teamwork, streamline workflows, and deploy models into real-time production environments with SAS ModelOps.

Discover the power of integrating with Large Language Models through SAS Information Catalogue and SAS Studio Flow, enriching data and improving the analytics lifecycle, while protecting PII with SAS Data Maker. Additionally, manage real-time campaigns effectively with SAS Intelligent Decisioning, utilizing advanced business rules and models for dynamic offers.

SAS solutions facilitate seamless model updates and scalability, supported by deep insights into customer behavior and campaign performance from SAS Visual Analytics.

Enhancing AI Productivity and Decision-Making with SAS Viya

Navigating the regulatory landscape for AI and data privacy in the Asia-Pacific (APAC) region involves understanding the ever-evolving 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 requirements in the dynamic regulatory landscape of the APAC region.

[Panel Discussion] Navigating the Regulatory Landscape: AI Policy and Privacy Compliance in the APAC Region

You can't be more productive if your AI is running slow or can't scale. See how SAS is delivering the most performant data and AI platform to not only support productivity, but drive down computing costs.

Why Speed and Performance Matters

Scams are a persistent issue globally.  Although, fraud has always been in focus, the losses from scams are out of control.  The industry is in a tailspin.  The media coverage has deepened.  The regulators are increasing their scrutiny to a heightened level. 

Scammers are constantly evolving their tactics, taking advantage of new technologies, and exploiting vulnerabilities. For those solving the problem of scams, the success, the predominant types and impact can vary by region, customer demographic, and channel.  In this session, we'll discuss the impacts and implications of scams from a customer, financial institution, and Solution provider perspective.

[Fireside Chat] Closing the Floodgates - Combatting Fraud - Impacts and Implications

Today, modern risk management operates in a dynamic world. We observe heightened risks, accelerated digital decisioning and new technologies developing at ground-breaking speed. While generative AI is seen as a golden key with transformative potential in Risk Management and Customer Decisioning, it's important to understand its promise, peril, and practical applications in Risk Management.
Key discussion highlights include:-
- Real-world machine learning and generative AI applications in Risk Management.
- Realized business value, efficiency gains, and productivity uplift.
- How paradigms are shifting to implement an AI-driven Enterprise Customer Decisioning strategy.

Risk-based Customer Decisioning in the age of AI

Scenario-based Risk Management including Climate Risk impact Simulation

SAS Risk Management

Issues faced in Retail Credit management are multiple data sources, manual processes leading to operational risk, lack of real-time customer insights, sub-optimal risk reward trade-off and lack of cutting edge analytical tools for identifying issues. Legacy platforms which do not support AI/Machine learning models/tools hold us back from quantum leap in sophisticated risk management.

In this session we'll cover:
- Benefits of single data source and automation
- Customer insight driven active risk management through use of advanced analytical skills
- Collection optimization through automated customer segmentation and treatments
- Data democratization for building data/analytics-driven culture

Automation and optimization of Retail Credit risk policies/processes with advanced risk analytics

Artificial Intelligence

Machine Learning

Risk Analysis

Analytics

Retail

Automation

Operational Risk

Customer Insight

Risk Management

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IT Service Management

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Cloud Computing

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Business Intelligence and Analytics

Welcome to the big data and data management community on BrightTALK. Join thousands of data quality engineers, data scientists, database administrators and other professionals to find more information about the hottest topics affecting your data. Subscribe now to learn about efficiently storing, optimizing a complex infrastructure, developing governing policies, ensuring data quality and analyzing data to make better informed decisions. Join the conversation by watching live and on-demand webinars and take the opportunity to interact with top experts and thought leaders in the field.

Big Data and Data Management

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Information Technology

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Customer Experience

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Automation and optimization of Retail Credit risk policies/processes with advanced risk analytics

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