Chapter 3: Supporting savers to make the right choice at retirement for them and their family and how to build on the lessons of auto-enrolment

We will investigate whether it is possible to design a set of good decumulation defaults and default pathways at retirement which will be suitable for most savers, in the same way that a good default investment strategy in the accumulation phase can be designed. Even if this is possible, we accept that it is likely that more people might opt for a different retirement income plan than the estimated 10% of people who reject the default accumulation fund. For example, some retirees might be in poor health and so might choose to access their funds in full at the date of retirement – or over as short a period as possible (staggered to avoid paying unnecessary income tax). Given the complexities of retirement expenditure decision making, we will examine the support in terms of guidance, help and advice that savers need in order to make the right choices for them and their family. Building on the lessons of auto-enrolment, we will examine what nudges would be useful to move people towards making decisions that are in their best long-term interests. We will also consider the barriers, especially the regulatory barriers, to implementing a default. The overriding question that we seek to answer in this Chapter is this: Is it possible to design safe harbour retirement income plans which combine safe harbour products with financial help or guidance (that confirms the suitability of the product for the client) in order to provide retirement income journeys that are good enough for most of Middle Britain

A digital marketing strategy in a fintech start-up: Advicefront

Advicefront is a start-up founded by Portuguese whose core business is developing software planning solutions for financial advisers. The company started in 2015 and attracted the attention of multiple investors and firms interested in accompanying the evolution of the product. Through time, Advicefront crossed some uncertainty periods which eventually led to a shift in product offering. Instead of offering a single software solution the company is now selling a modular approach where separate modules address specific challenges advisers face in their daily workflow. Advicefront has always maintained true to its unique selling proposition, based on showcasing pristinely designed interfaces, integrating with popular tools among advisers, and offering an unmatched user experience for advisers and investors, adapting to each user profile’s actions and intended outcomes. The financial advice software market is still attached to old-fashioned paper-based processes and bureaucracies which are becoming obsolete. Adding to this, the sector going through not only a shift in players, since many advisers are approaching retirement, but also a renovation of investors, as millennials are now becoming financially independent with an investment-oriented approach to their income. Thereby, considering this market in turmoil, Advicefront has an incredible market opportunity to present a software shaped to serve these new populations of advisers and investors. The present project aims to propose a marketing plan for Advicefront branching in a strategic plan as well as an operational plan with recommended actions for each aspect of the marketing-mix. It is also presented a communication plan to be implemented during 2019.A Advicefront é uma start-up cujo principal negócio é desenvolver software de planeamento para consultores financeiros. A empresa surgiu em 2015 e atraiu a atenção de investidores e empresas interessadas em acompanhar a evolução do produto. Com o tempo, a Advicefront ultrapassou períodos de instabilidade que culminaram numa mudança na oferta. Ao invés de oferecer uma única solução de software a empresa desenvolveu um sistema onde módulos separados respondem a necessidades específicas do fluxo de trabalho de consultoria financeira. A Advicefront manteve-se sempre fiel à sua proposta de valor, baseada na criação de interfaces com um design de excelência, na integração com ferramentas populares, e oferecendo uma experiência de utilização inigualável, adaptando-se ao perfil do usuário. O mercado de software de consultoria financeira está ligado a processos antiquados e burocráticos que estão a tornar-se cada vez mais obsoletos. Somando o facto de ser ainda um setor a atravessar um rejuvenescimento de consultores, uma vez que muitos estão a aproximar-se da reforma, mas também uma renovação de investidores. Os millennials estão a tornar-se financeiramente independentes e com orientados para investirem os seus rendimentos. Considerando este mercado em tumulto, a Advicefront tem uma oportunidade no mercado para apresentar um software desenvolvido para responder à nova população de consultores e investidores. Este projeto visa propor um plano de marketing para a Advicefront que se ramifica num plano estratégico bem como um plano operacional com ações recomendadas para cada aspeto do marketing-mix. É ainda apresentado um plano de comunicação a ser implementado em 2019

Artificial intelligence – a key success factor for wealth management industry

The Private Banking & Wealth Management (PWM) industry is generally seen as embodying traditional, old- fashioned and even archaic values. Upheld for centuries, its business model, which is based on intensive, comprehensive and discreet personal interactions between financial advisors and wealthy clients, is put to the test today. In today's dynamic and highly connected world, a large number of HNWIs (High Net Worth Individuals) want faster and more convenient value propositions and a cutting-edge digital experience – a trend that the pandemic has amplified many times over. In order to meet the increased expectations of this clientele, private banks and other institutions in the sector are increasingly investing in a number of new technologies and tools, artificial intelligence (AI) taking a leading place among them. In addition to enabling a more complete and qualitative satisfaction of user needs, AI promises benefits for PWM companies in a number of other areas: risk management, compliance, cost reduction, etc

Financial Robo-Advisor: Learning from Academic Literature

Financial Robo-Advisor is the technology that integrates machine learning and self-identification to determine investment decisions. This study explores the financial robo-advisor based on bibliometric analysis and a systematic literature review. The method used three steps: determining the keyword, bibliometric analysis of literature metadata using VOSviewer, then collecting and analysing the articles. The bibliometric analysis results show five cluster keywords defined with different colors. In the network visualization, the robo-advisor connects to other keywords: investment, fintech, and artificial intelligence. Furthermore, the systematic literature review shows that the articles are divided into seven research objectives: (1) Law, Regulation, and Policy; (2) Investment Literate and Education; (3) Offered Services; (4) Present Risk-Portfolio Matching Technology; (5) Optimal Portfolio Methods; (6) Human-Robo Interaction; (7) Theoretical Design and Gap. Furthermore, this study can be used by academicians and practitioners to find out about robo-advisors based on an academic perspective

Preserving Human Agency in Automated Compliance

As technology transforms financial services, so too must it transform the regulation of financial markets and intermediaries. The imperative of real-time, prophylactic regulation increasingly compels reallocation of regulatory and compliance budgets to surveillance and enforcement technology. At the same time, in light of the well-known weaknesses of automated systems, securities firms (and their regulators) must temper investment in automation with efforts to augment the agency of compliance professionals. This symposium contribution considers how investment in the professional development of compliance personnel can better integrate automated tools within established compliance and supervisory structures and thereby advance regulatory and operational objectives

Preserving Human Agency in Automated Compliance

As technology transforms financial services, so too must it transform the regulation of financial markets and intermediaries. The imperative of real-time, prophylactic regulation increasingly compels reallocation of regulatory and compliance budgets to surveillance and enforcement technology. At the same time, in light of the well-known weaknesses of automated systems, securities firms (and their regulators) must temper investment in automation with efforts to augment the agency of compliance professionals. This symposium contribution considers how investment in the professional development of compliance personnel can better integrate automated tools within established compliance and supervisory structures and thereby advance regulatory and operational objectives

Robo-Advisors - A Future Way To Invest?

Research Question: Are robo-advisors the future of investing? As the capabilities of technology continue to advance, alternatives to conventional practices are created in an attempt to boost convenience and efficiency. This paper will focus on one such alternative, robo-advisors, an automated investment advisor platform. The technology is evaluated to answer the research question above and to assess whether it holds promise in the world of finance as well as the potential to ultimately outpace traditional forms of investment advice. To accomplish this goal, in-depth research is provided covering a broad range of topics concerning robo-advisors including the platform’s history, analysis of the industries it falls under, underlying mechanics, firms, its regulatory framework, and comparisons to traditional financial advisors. Next, knowledge from this preliminary research was used to report additional insights gained from interviews conducted with one representative of a robo-advisor platform and another representing a traditional financial advising firm. The paper then provides a cost-benefit analysis quantifying the tangible historical gains and losses clients have experienced from using both robo-advisors and financial advisors. Finally, personal investments were made with one robo-advisor platform to test the effectiveness of the technology over the course of 1.5 months in order to share user experiences, feedback, suggestions, recommendations and to reconfirm earlier insights reported in the paper. To assist in writing the report, websites, peer-reviewed journals and scholarly articles, data sources such as Statista and Morningstar, tools like Portfolio Visualizer and Excel, phone calls, emails, web portals, and an app were utilized. In the end, it was found that robo-advisors have a strong, positive outlook in terms of future growth. However, hybrid robo-advisors and models of investing were determined to be the norm looking ahead since they effectively integrate the advantages of both robo-advisors and traditional financial advisors as well as address the downsides with each approach. Furthermore, it was concluded that there was no clear answer whether robo-advisors in their current state are better than conventional practices since it all depended on a client’s financial situation and needs. Still, potential college entrants and those looking to generate retirement savings were deemed best fits for the technology. Regardless, it was discovered that robo-advisors would continue to improve in the future by expanding their investment offerings, strategies, plans, making significant strides in artificial intelligence, and continuing to remain cost-efficient

Artificial Intelligence and Bank Soundness: A Done Deal? - Part 1

Banks soundness plays a crucial role in determining economic prosperity. As such, banks are under intense scrutiny to make wise decisions that enhances bank stability. Artificial Intelligence (AI) plays a significant role in changing the way banks operate and service their customers. Banks are becoming more modern and relevant in people’s life as a result. The most significant contribution of AI is it provides a lifeline for bank’s survival. The chapter provides a taxonomy of bank soundness in the face of AI through the lens of CAMELS where C (Capital), A(Asset), M(Management), E(Earnings), L(Liquidity), S(Sensitivity). The taxonomy partitions opportunities from the main strand of CAMELS into distinct categories of 1 (C), 6(A), 17(M), 16 (E), 3(L), 6(S). It is highly evident that banks will soon extinct if they do not embed AI into their operations. As such, AI is a done deal for banks. Yet will AI contribute to bank soundness remains to be seen

Driverless Finance

While safety concerns are at the forefront of the debate about driverless cars, such concerns seem to be less salient when it comes to the increasingly sophisticated algorithms driving the financial system. This Article argues, however, that a precautionary approach to sophisticated financial algorithms is justified by the potential enormity of the social costs of financial collapse. Using the algorithm-driven fintech business models of robo-investing, marketplace lending, high frequency trading and token offerings as case studies, this Article illustrates how increasingly sophisticated algorithms (particularly those capable of machine learning) can exponentially exacerbate complexity, speed and correlation within the financial system, rendering the system more fragile. This Article also explores how such algorithms may undermine some of the regulatory reforms implemented in the wake of the Financial Crisis to make the financial system more robust. Through its analysis, this Article demonstrates that the algorithmic automation of finance (a phenomenon I refer to as “driverless finance”) deserves close attention from a financial stability perspective. This Article argues that regulators should become involved with the processes by which the relevant algorithms are being created, and that such efforts should begin immediately – while the technology is still in its infancy and remains somewhat susceptible to regulatory influence