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The transformation of ALM / Balance Sheet Management to deliver optimized performance management

Multiple factors such as competition, cost of regulation, low interest rates, margining under stress…) are pushing treasurers, ALM leaders and finance directors more and more to rethink their entire performance framework. It is time to investigate if there are more predictive and optimized strategies that can be applied, using advanced analytics, advisory robots and modern technics such AI/ML.

At this webinar, industry experts will discuss the use of dynamic forecasting, predictive and optimizing platforms based on advisory robots and ML/AI techniques.

The session will cover the following discussion areas:

• Big data and advanced analytics entering forecasting and balance-sheet management domain, is it really happening or so far just an experiment?

• Is ML/AI mature enough to contribute to real life challenges of Treasury and Balance Sheet Management? Where will these technics have the most beneficial impact (predictive, forecasting, behavioral, strategic planning…)?
• What advantages would these techniques bring vs the ubiquitous standard statistics/ linear regression?
• The digitization of ALM/Treasury department implies new type of profiles / resources, what is the real impact and plan? Does it push for a collaborative approach between FinTech, universities, banks?
• Are we ready to use / trust balance-sheet optimization advisory robots? How far can we go? We will be exploring first experiences and use cases?
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This webinar is made possible through the generous support of Finastra

About Our Experts
		Marcus Cree, Risk Specialist, Finastra Marcus Cree has worked in financial risk management for over 20 years, including asset management and tier 1 banking, in the role of practitioner as well implementation and consultancy. Covering Market, Credit and Liquidity risk, Marcus has worked through Basel 2 and 3, as well as Dodd Frank implementations. His current role is as Global Sales Specialist for the Global Risk Practice for Finastra.
		Arnaud Picut, Global Head of Risk Practice, Finastra Arnaud Picut heads up the risk management practice at Finastra. He has started off as a co-founder of risk management software in 2001 which was subsequently sold in 2006. He has been involved in risk management software ever since, predominately to develop international business for risk management and regulatory compliance. He has joined Misys in 2011, and been responsible for the entire chain of commercialisation of FusionRisk, from value proposition generation to building go-to-market strategies and building global ecosystems supporting it. If you have any feedback for Arnaud or would like to contact him, you can reach him at [email protected].
		Dr. Thomas Krabichler, Senior Lecturer, Lucerne University of Applied Sciences and Arts Dr. Thomas Krabichler is a leading lecturer and quantitative finance researcher at the Lucerne University of Applied Sciences and Arts. He holds a doctoral degree in mathematical finance from ETH Zurich and closely collaborates with prof. Josef Teichmann from ETH Zurich on applications of machine learning in finance (recently so-called deep hedging). Previously, for over a decade, Thomas worked in the industry (including an eight years tenure at PwC Switzerland) in the areas of financial modelling, valuation and risk quantification.
		Cansu Kanli, Senior ALM/Treasury Specialist, ABN AMRO