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Risk-based Customer Decisioning in the age of AI
Dr Terisa Roberts, Global Solution Lead – Risk Modeling and Decisioning, SAS
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.
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Scenario-based Risk Management including Climate Risk impact Simulation
Anselmo Marmonti, Global Head of Risk & Finance Advisory, SAS & Martim Rocha, Global Head of Risk Banking Solutions, SAS
Having a Scenario-based environment to simulate Capital and the Balance Sheet measures, holistically, is nowadays a common practice and a must have. Simulate impacts coming from Climate Risk and model climate-related events on various aspects of an organization's operations, is one of the reasons why the above is now business critical, but the capability should be cross topics and consistent across the organization.
In this session, we'll discuss the structured way to execute scenario-based Capital and Balance Sheet . Key discussion points include:-
- How to understand how a scenario impacts the business main drivers
- How to ensure flexibility and consistency across risk types and financial statements
- How does climate risk impact your business?
- How do you convert climate risk factors into well-known risk factors?Speakers:
Anselmo Marmonti, Global Head of Risk & Finance Advisory, SAS
Martim Rocha, Global Head of Risk Banking Solutions, SAS -
Risk-based Customer Decisioning in the age of AI
Dr Terisa Roberts, Global Solution Lead – Risk Modeling and Decisioning, SAS
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.