Join us at SAS Risk Week, and embark on a journey filled with new learnings. This virtual event will explore some of the innovative steps taken by groundbreaking companies to overcome recent circumstances how they are leveraging analytics to plan their decisions for the near future. We'll also discuss what worked for these companies with these innovations in risk management.
Register and learn how to: (1) increase accuracy of your models, (2) leverage simulations to mitigate risks and financial losses, and (3) optimize your journey to regulatory compliance.
Crammed with key insights delivered by 15 speakers 3 days.
Risk Analytics and MRM
- Advanced analytics and decisioning can help organizations to innovate the digital experience offered to their customers
- It is possible to further reduce credit losses and increase portfolio penetration beyond what is seen with current processes while maintaining the same risk exposure.
- Internal modeling allows financial institutions to leverage their internal data along with the external models and scores and thus make better decisions
- The duration of the analytical cycle is one of the most underrated KPIs in the Industry. Having the shortest analytical cycle allows an organization to always have the best possible model in production.
- SAS can enable organizations to have the same flexibility and model sophistication of Fintechs (ex. Machine learning models) and at the same time meeting governance and regulatory standards.
There are some challenges in doing this journey alone. SAS can enable it to become a reality.
- Why should you care about Model Risk Management
- Stories on How MRM can support the analytical modernization
- Key myths about MRM – Ex. What it is and how is it different from Model Validation
- Why will it become more important the more sophisticated are your models
- SAS knows MRM and we can help in your journey
Scenario Based Management and CECL
Why should you care about Scenario Based Management?
- The relevance of Scenario Based Management and how it can be used for commercial and managerial purposes beyond risk management.
- In particular, how it can be used to maximize returns in the near future with the range of scenarios of the economic recovery and inflation.
CECL beyond meeting the regulation.
- How can smaller banks leverage their CECL infrastructure and data for managerial purposes and still meet the deadline for Jan 2023.
- The benefits of a white box approach to better manage your provision and how it allows for a lower cost implementation.
- How ML with automated real timing decisioning can drastically improve the premium calculation process and help bring in more customers
- ML can offer a much better insights than deterministic models to identify different cluster of customers´ behavior and accurately calculate the risk premium and offer a competitive insurance policy in real time
- LDTI beyond meeting the regulation.
- How can insurance companies leverage their LDTI infrastructure and data for managerial purposes and still meet the deadline for Jan 2023.
- How to simulate cashflows and integrate with GL. One stop shop reduces risk.
Meet our experts
Senior Advisor, Risk and Quantitative Solutions at SAS
LATAM and SMB Head of Risk Management Solutions at SAS
North America Head, Risk & Finance Advisory at SAS
Global Director, Risk Business Consulting at SAS
Senior Risk Analytical Consultant at SAS
Senior Industry Consultant at SAS
Lead Solutions Architect at SAS
Stefan De Lombaert
Global Lead Insurance Risk & Finance Solutions at SAS
Senior Manager at Deloitte Consulting
Senior Manager | Digital Business Integration at Accenture
Partner at Oliver Wyman
Director of Business Analytics at FRG
FCAS, MAAA Managing Director at KPMG