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The New Physics of Financial Services - a discussion with Jesse McWaters, Lead Author.

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Treść dostarczona przez WYFT-What’s Your Focus Today?. Cała zawartość podcastów, w tym odcinki, grafika i opisy podcastów, jest przesyłana i udostępniana bezpośrednio przez WYFT-What’s Your Focus Today? lub jego partnera na platformie podcastów. Jeśli uważasz, że ktoś wykorzystuje Twoje dzieło chronione prawem autorskim bez Twojej zgody, możesz postępować zgodnie z procedurą opisaną tutaj https://pl.player.fm/legal.
I had the chance and privilege to recently sit down and talk in detail with Jesse McWaters, lead author of this important and very detailed report. If you want to find out how AI and machine learning is transforming the financial services industry, listen to our discussion here, and refer to the full document on the WEF website for the whole package @ (https://goo.gl/UzDw71). From the website: Artificial intelligence is fundamentally changing the physics of financial services. It is weakening the bonds that have held together the component parts of incumbent financial institutions, opening the door to entirely new operating models and ushering in a new set of competitive dynamics that will reward institutions focused on the scale and sophistication of data much more than the scale or complexity of capital. A clear vision of the future financial landscape will be critical to good strategic and governance decisions as financial institutions around the world face growing competitive pressure to make major strategic investments in AI and policy makers seek to navigate the challenging regulatory and social uncertainties emerging globally. Building on the World Economic Forum’s past work on disruptive innovation in financial services, this report provides a comprehensive exploration of the impact of AI on financial services. Key findings include: • From cost centre to profit centre: Institutions will turn AI-enabled back-office operations into external services, both accelerating the rate at which these capabilities improve and necessitating others to become consumers of those capabilities to avoid falling behind • A new battlefield for customer loyalty: As past methods of differentiation erode, AI presents an opportunity for institutions to escape a "race to the bottom" in price competition by introducing new ways to distinguish themselves to customers • Self-driving finance: Future customer experiences will be centred around AI, which automates much of customers’ financial lives and improves their financial outcomes • Collective solutions for shared problems: Collaborative solutions built on shared datasets will radically increase the accuracy, timeliness, and performance of non-competitive functions, creating mutual efficiencies in operations and improving the safety of the financial system • Bifurcation of market structure: As AI reduces search and comparison costs for customers, firm structures will be pushed to market extremes, amplifying the returns for large-scale players and creating new opportunities for niche and agile innovators • Uneasy data alliances: In an ecosystem where every institution is vying for diversity of data, managing partnerships with competitors and potential competitors will be critical but fraught with strategic and operational risks • The power of data regulators: Regulations governing the privacy and portability of data will shape the relative ability of financial and non-financial institutions to deploy AI, thus becoming as important as traditional regulations to the competitive positioning of firms • Finding a balanced approach to talent: Talent transformation will be the most challenging speed limit on institutions’ implementations of AI, putting at risk the competitive positioning of firms and geographies that fail to effectively transition talent alongside technology • New ethical dilemmas: AI will necessitate a collaborative re-examination of principles and supervisory techniques to address the ethical grey areas and regulatory uncertainties that reduce institutions’ willingness to adopt more transformative AI capabilities This report is the culmination of one year’s worth of research, including over 200 interviews with subject matter experts and seven global workshops, prepared by the World Economic Forum in collaboration with Deloitte. --- Support this podcast: https://podcasters.spotify.com/pod/show/WYFT/support
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Artwork
iconUdostępnij
 
Manage episode 311249741 series 3097555
Treść dostarczona przez WYFT-What’s Your Focus Today?. Cała zawartość podcastów, w tym odcinki, grafika i opisy podcastów, jest przesyłana i udostępniana bezpośrednio przez WYFT-What’s Your Focus Today? lub jego partnera na platformie podcastów. Jeśli uważasz, że ktoś wykorzystuje Twoje dzieło chronione prawem autorskim bez Twojej zgody, możesz postępować zgodnie z procedurą opisaną tutaj https://pl.player.fm/legal.
I had the chance and privilege to recently sit down and talk in detail with Jesse McWaters, lead author of this important and very detailed report. If you want to find out how AI and machine learning is transforming the financial services industry, listen to our discussion here, and refer to the full document on the WEF website for the whole package @ (https://goo.gl/UzDw71). From the website: Artificial intelligence is fundamentally changing the physics of financial services. It is weakening the bonds that have held together the component parts of incumbent financial institutions, opening the door to entirely new operating models and ushering in a new set of competitive dynamics that will reward institutions focused on the scale and sophistication of data much more than the scale or complexity of capital. A clear vision of the future financial landscape will be critical to good strategic and governance decisions as financial institutions around the world face growing competitive pressure to make major strategic investments in AI and policy makers seek to navigate the challenging regulatory and social uncertainties emerging globally. Building on the World Economic Forum’s past work on disruptive innovation in financial services, this report provides a comprehensive exploration of the impact of AI on financial services. Key findings include: • From cost centre to profit centre: Institutions will turn AI-enabled back-office operations into external services, both accelerating the rate at which these capabilities improve and necessitating others to become consumers of those capabilities to avoid falling behind • A new battlefield for customer loyalty: As past methods of differentiation erode, AI presents an opportunity for institutions to escape a "race to the bottom" in price competition by introducing new ways to distinguish themselves to customers • Self-driving finance: Future customer experiences will be centred around AI, which automates much of customers’ financial lives and improves their financial outcomes • Collective solutions for shared problems: Collaborative solutions built on shared datasets will radically increase the accuracy, timeliness, and performance of non-competitive functions, creating mutual efficiencies in operations and improving the safety of the financial system • Bifurcation of market structure: As AI reduces search and comparison costs for customers, firm structures will be pushed to market extremes, amplifying the returns for large-scale players and creating new opportunities for niche and agile innovators • Uneasy data alliances: In an ecosystem where every institution is vying for diversity of data, managing partnerships with competitors and potential competitors will be critical but fraught with strategic and operational risks • The power of data regulators: Regulations governing the privacy and portability of data will shape the relative ability of financial and non-financial institutions to deploy AI, thus becoming as important as traditional regulations to the competitive positioning of firms • Finding a balanced approach to talent: Talent transformation will be the most challenging speed limit on institutions’ implementations of AI, putting at risk the competitive positioning of firms and geographies that fail to effectively transition talent alongside technology • New ethical dilemmas: AI will necessitate a collaborative re-examination of principles and supervisory techniques to address the ethical grey areas and regulatory uncertainties that reduce institutions’ willingness to adopt more transformative AI capabilities This report is the culmination of one year’s worth of research, including over 200 interviews with subject matter experts and seven global workshops, prepared by the World Economic Forum in collaboration with Deloitte. --- Support this podcast: https://podcasters.spotify.com/pod/show/WYFT/support
  continue reading

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