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Risk-Based Decisioning in an Age of Uncertainty Part 1
Manage episode 375084575 series 1756199
Is it possible for financial institutions to offer on-demand, superior customer experiences while making risk decisions in near real-time in an increasingly digital and interconnected world? That is the question we’ll explore in this podcast featuring Terisa Roberts, Global Solution Lead, Risk Modeling and Decisioning at SAS, and Bruce Erb, Director – Credit Risk Consulting, KPMG.
Traditional financial institutions are encountering additional hurdles, including fierce competition from agile newcomers, new regulatory demands for operational resiliency, and increased technology risk. In an age of digital lending driven by artificial intelligence, what are modern financial institutions doing differently to remain agile and profitable while keeping costs in check?
We’ll delve into several strategies that financial institutions are adopting for risk-based decision-making to bolster their resilience in times of uncertainty.
Speakers
Terisa Roberts, Global Solution Lead, Risk Modeling and Decisioning, SAS
Terisa Roberts is a risk management professional with 15 years of experience primarily in the financial services sector. She is currently a Director and Global Solution lead for Risk Modeling and Decisioning at SAS.
Terisa has an extensive background in risk modeling for retail and commercial portfolios including regulatory capital stress testing and IFRS9/CECL. She advises banks, other financial services providers, and regulators concerning innovations in Risk Modeling and Decisioning including artificial intelligence and machine learning.
Teresa holds a Ph.D. in Operations Research and Informatics and lives in Sydney, Australia.
Bruce Erb, Director – Credit Risk Consulting, KPMG
Bruce Erb has been a risk professional for over 23 years in both industry and consulting. At KPMG, he has supported financial services clients in a variety of risk programs and initiatives with a current focus on transformation of credit and risk governance operating and execution models leveraging alternative approaches including automation, advanced analytics, and cognitive technologies.
Bruce was the product owner and co-inventor of an audit investigation tool that leveraged digitization, automation, and cognitive components to augment the way risk professionals evaluate and score a commercial loan. He was a loan officer for more than nine years before joining KPMG.
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Over the years, GARP and SAS have partnered to bring risk practitioners unique insights on a variety of topics related to risk management. Now we present a series of podcasts focused on making financial risk-based decisions in light of the rapid evolution of artificial intelligence and machine learning.
About SAS
As a leader in analytics, SAS’ award-winning capabilities in analytics, risk management, and other technology areas have helped customers across the globe solve their toughest and ever-evolving business problems. Its unrelenting commitment to innovation enables organizations across financial services to modernize and sustain a competitive edge. Through the latest developments in machine learning, natural language processing, forecasting, and optimization, SAS supports diverse environments and scales to meet changing needs. Learn more about how SAS is driving innovation and business value for risk and finance professionals at www.sas.com/risk
79集单集
Manage episode 375084575 series 1756199
Is it possible for financial institutions to offer on-demand, superior customer experiences while making risk decisions in near real-time in an increasingly digital and interconnected world? That is the question we’ll explore in this podcast featuring Terisa Roberts, Global Solution Lead, Risk Modeling and Decisioning at SAS, and Bruce Erb, Director – Credit Risk Consulting, KPMG.
Traditional financial institutions are encountering additional hurdles, including fierce competition from agile newcomers, new regulatory demands for operational resiliency, and increased technology risk. In an age of digital lending driven by artificial intelligence, what are modern financial institutions doing differently to remain agile and profitable while keeping costs in check?
We’ll delve into several strategies that financial institutions are adopting for risk-based decision-making to bolster their resilience in times of uncertainty.
Speakers
Terisa Roberts, Global Solution Lead, Risk Modeling and Decisioning, SAS
Terisa Roberts is a risk management professional with 15 years of experience primarily in the financial services sector. She is currently a Director and Global Solution lead for Risk Modeling and Decisioning at SAS.
Terisa has an extensive background in risk modeling for retail and commercial portfolios including regulatory capital stress testing and IFRS9/CECL. She advises banks, other financial services providers, and regulators concerning innovations in Risk Modeling and Decisioning including artificial intelligence and machine learning.
Teresa holds a Ph.D. in Operations Research and Informatics and lives in Sydney, Australia.
Bruce Erb, Director – Credit Risk Consulting, KPMG
Bruce Erb has been a risk professional for over 23 years in both industry and consulting. At KPMG, he has supported financial services clients in a variety of risk programs and initiatives with a current focus on transformation of credit and risk governance operating and execution models leveraging alternative approaches including automation, advanced analytics, and cognitive technologies.
Bruce was the product owner and co-inventor of an audit investigation tool that leveraged digitization, automation, and cognitive components to augment the way risk professionals evaluate and score a commercial loan. He was a loan officer for more than nine years before joining KPMG.
-----------------------
Over the years, GARP and SAS have partnered to bring risk practitioners unique insights on a variety of topics related to risk management. Now we present a series of podcasts focused on making financial risk-based decisions in light of the rapid evolution of artificial intelligence and machine learning.
About SAS
As a leader in analytics, SAS’ award-winning capabilities in analytics, risk management, and other technology areas have helped customers across the globe solve their toughest and ever-evolving business problems. Its unrelenting commitment to innovation enables organizations across financial services to modernize and sustain a competitive edge. Through the latest developments in machine learning, natural language processing, forecasting, and optimization, SAS supports diverse environments and scales to meet changing needs. Learn more about how SAS is driving innovation and business value for risk and finance professionals at www.sas.com/risk
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