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    • AlgoMe
      By AlgoMe
      AI and Data Science in Trading
      WWW.AIDATATRADING.CO.UK    
    • Jonathan Max
      By Jonathan Max
      AI is coming for you: One in three City of London jobs at risk from automation - CityAM
      WWW.CITYAM.COM More than one in three jobs in the City of London are under threat from automation, a study has found. [...]  
      The buzz this week has been back on Crypto; rising Bitcoin and the launch of Libra.
       
      Do you think that up to 33% of jobs could really be at risk from AI? - or has the Office of National Statistics overshot somewhat?
       
      Read our survey to find out more
       
    • AlgoMe
      By AlgoMe
      As more asset managers acquire –or develop- Artificial Intelligence (AI) and Machine Learning (ML) solutions to maximise their alpha generation, market growth and operational cost reduction; it is clear that the industry needs to prepare to face the future challenges these solutions will bring when they become mainstream. 
       
      Are you prepared for AI implementation?
      Do not miss out on this unique opportunity to discuss how AI will impact key business areas while creating greater opportunities for the asset management community.
       
      https://www.theia.org/events-training/event?eventtemplate=204-techtalk-new-frontiers-how-ia-is-transforming-asset-management&event=416
       
    • Luuk Jacobs
      By Luuk Jacobs
      The event will be focused on data, operations, blockchain, compliance, legacy, regulation and AI.
       
      European FundTech Lab London, Spring 2019
      WWW.EVENTBRITE.COM Funds Europe in conjunction with Amundi Services, Calastone, Metrosoft, Milestone Group and Oracle will be hosting the fifth European FundTech Lab forum which will be taking place in London on Thursday, 16 May 2019...  
    • Luuk Jacobs
      By Luuk Jacobs
      The FCA has now recognised the increased use of big data and AI across the Investment Management and banking value change.  It is aiming to better understand the impact it has and will have, the benefits and harms and implications for regulation. One of their focus points in their 2019 Research agenda on the theme of technology, big data and artificial intelligence (AI) is the economics and ethics of this theme.
       
      The economics of the use of big data and AI in general are already quite well understood. They have changed the way of doing business and generating value enormously. Industries have been and continue to be disrupted; examples like Amazon, Apple, Facebook, Uber and even Microsoft have shown how the philosophy of platforms has moved us from single supplier mentality to open marketplaces.  These places where producers and consumers come together in interactions that create value for both parties, whether it is peer to peer or direct to consumer and disrupt the existing status quo.
       
      Platforms are not an entirely new phenomena as it has existed already in traditional open air market places around the world or for example in stock markets. What is new, is the addition of digital technology enabling platforms to enormously extend their reach, speed, convenience and efficiency.
       
      I would argue that the real impact of big data and AI has not hit Investment Management yet. Yes, there is robo-advice providing digital financial advice based on mathematical rules or algorithms (examples like Nutmeg). The majority of them however have been struggling to make their platform economically viable and according to a Deloitte report robo-advisers would need around £6bn assets under management to generate enough revenues to cover their costs. Nevertheless, also Investment Management is at the start of using big data, blockchain/ Distributed ledger technology and natural language processing. The benefits are seen already in better informing (investment) decisions, driving operational efficiency and fraud prevention and compliance.
       
      Arguably lesser known are the potential ethical impacts that will be associated with the use of these technologies while companies move from the traditional commercial yardsticks to include ethical and value-based decision making.
      The established players like Facebook and Alphabet (through the accusations of distributing fake news), Uber (sexual harassment and leadership style), AirBnB (destroyed properties from their users), have and continue to show that the ability to embed ethical awareness and decision making across functions will emerge to be a key attribute of successful digital organisations. The Investment Management industry is to be warned.
       
      Governments are stepping up (the FCA research agenda aims at looking at the implications on regulation) and, for example, GDPR is a first step. Nevertheless, the industry should not be waiting for governments and regulators to step in. I would argue that especially in an industry like Investment Management which is based on trust, companies that put ethics and morality front and centre of their organisation and especially with regards to big data and AI, are more likely to engender the trust of customers and differentiate themselves from competitors in the market.
       
      So what are the ethical questions ‘big data and AI’ that should be asked?  
       
      Can artificial intelligence exacerbate, hide and create unintended biases? Do network effects reduce competition and, in turn, impact consumer choice? How can we be accountable for big data? How do we define big data? How do we adjust risk management frameworks? What are the benefits and, more importantly who will benefit and who might be at risk by this?  
      According to Charles Ellis, CFA, and chair of the Whitehead Institute, Cambridge, Massachusetts, the “biggest challenge” with regards to ethics for the investment management industry is to “find the pathway to reassert the dominance of the profession over the business”; an inherent conflict of interest in the Investment Management business as they are supposed to deliver financial performance both to their owners and their clients. 
       
      Regulation is in the end already in place and leaves little room for ambiguity ie to treat the clients in a fair and ethical way with the general principle to always put the clients’ interest first (AIFMD, UCITs IV and MiFID II).
       
      It is up to the industry now to ensure that these principles are followed and embedded when using big data and AI.  There is no magic pill for it yet, but the market shapers and early adopters will show how easy or difficult this might be.
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