Wealth Management News — June 2020 — Operating Model, Wealth tech, private Equity, Artificial Intelligence
Wealth Target Operating Model
Wealth Managers helped Millionaire clients grow richer during lockdown and some clients’ fortunes soared to new highs. Forbes reported 600 billionaires added more than $400 billion to their wealth during the pandemic, as markets crashed and then bounced back. Forbes
Structural issues can make it challenging for the wealth management industry to fully capitalize on Covid 19 to emerge from the crisis stronger, in the meantime Deutsche Bank combines wealth management and international retail ops.
Goldman Sachs has named a new head of its private wealth management business in the important New York region Barrons and is becoming the Blueprint for Wealth Managers
Wealth Management After the Storm
base case sees global high net worth (HNW) wealth lose more than a year of growth versus pre-Covid-19 forecasts before rebounding to growth in 2021.
HNW wealth declined by 4 percent or $3.1 trillion in 2020, a major departure from the previous decade’s consis- tent annual growth trajectory.
Wealth Managers Need To Invest In Digital Solutions That Support Flexible Digital Collaboration Models. Digital solutions are not only cutting-edge tools and capabilities from best-in-class vendors but holistic experiences across platforms that best replicate the traditional personal wealth management experience. There are four main themes to deliver an optimal digital wealth experience:
- Quick Access: Clients expect quick and seamless access to all their information without redundant sign-on or breaks in User-Interface (UI).
- Consistency in Experience: Omni-channel access is crucial, but the experience must be consistent across different entry points.
- Digital Collaboration: Different segments, even clients within the same segment, expect digital solutions to create different digital collaboration styles, across the wealth management value chain.
- Personal Services: Digital solutions and collaboration should not replace in-person access to advisors, but should look to augment the personalized experience for clients.
In Europe Alibaba poses the greatest threat to asset managers’ existing business models — The changing face of fund distribution in Europe, a report by Calastone,
Some key Findings:
72% of respondents say asset managers will introduce more ETFs and low-cost products as they refine their business models.
- 59% say fund managers will expand their wealth management arms and increase their focus on direct-to-consumer (D2C) channels.
- 65% say digital ledger technology (DLT) will deliver greater efficiency in fund trading and settlement.
- 46% say DLT will provide a foundation for better cooperation between participants in the funds value chain.
- 73% say that, as the funds industry comes under growing margin pressure, this burden will be felt most acutely by fund promoters.
- 80% say robo-advisory will expand as the funds industry seeks new mechanisms for delivering investment advice.
- 71% say that online retailers such as Alibaba pose the greatest threat to asset managers’ existing business models.
- 49% say that investment advice remains the “domain of the wealthy”.
- The ability to handle big data — to process large data sets, to work with high data velocity and with a wide range of data types and formats — underpins much of the innovation taking place now. It is no surprise, therefore, that respondents identify big data in their list of investment priorities — for example, to drive factor-based and quantitative investment strategies, to supply performance measurement and risk-analytics solutions, or as a key input for a wide array of AI strategies. This is a skill that underpins effective delivery in many of the service areas addressed in the survey
The report is here: Calastone, funds-europe
Wealth Technology
Fintech is the future of wealth management
Objectway Wins XCelent Depth of Service Award in Celent “Wealth Management Client Onboarding Platforms” Report
Brave New Coin Launches BNC Pro, A Digital Wealth Management Platform for Cryptocurrency Investors
Fidelity launches rewards program for wealth management clients
HNW Wealth Managers Must Shift Gears On Risk Management
Celent Recognizes Harvest as an “Up and Coming” Leader in Digital Onboarding Solutions
Itaú Private Bank upgrades int’l wealth management platform
Powerhouse Banks Raise The Stakes In China
Northern Trust Selected by Sancta Capital to Provide Institutional Brokerage and Global Custody Services
Asia Wealth tech Getting Ahead Of The Pack
Wealth Management Software Market With Impact of COVID19 Analysis By Top Keyplayers ,Misys ,Temenos ,FIS ,SS&C Tech ,SimCorp
PODCAST — Ginmon provides automated and personal online wealth management
Top Global Wealth Management And Advisory Companies In The World For 2020
Asian Wealth Management and Asian Private Banking — The Dawn of a New Era: The Implications for Digital Technology & Solutions in Wealth Management
Robinhood traders cash in on the market comeback that billionaire investors missed
Artificial Intelligence
Melius Investments has introduced a platform containing 10 model portfolios that use artificial intelligence to identify the highest-conviction picks from successful active mutual fund managers, and then puts them into tidy packages designed to generate investment alpha.
Fa-mag
Envestnet Connect will use AI to integrate a client’s personal household financial data with relevant and customized news content that aligns with their values and their financial status, in hopes of helping end-clients establish deeper connections with their advisors and achieve greater levels of financial wellness. Leveraging AdvisorStream’s advanced content marketing platform, Envestnet Connect will for the first time enable advisors to intelligently deliver personalized content that matches the financial interests, life events, and lifestyles of their clients.”
fa-mag
Machine Learning is getting huge in the UK Financial Services
Key findings of the survey are:
- ML is increasingly being used in UK financial services. Two thirds of respondents report they already use it in some form. The median firm uses live ML applications in two business areas and this is expected to more than double within the next three years.
- In many cases, ML development has passed the initial development phase, and is entering more mature stages of deployment. One third of ML applications are used for a considerable share of activities in a specific business area. Deployment is most advanced in the banking and insurance sectors.
- From front-office to back-office, ML is now used across a range of business areas. ML is most commonly used in anti-money laundering (AML) and fraud detection as well as in customer-facing applications (e.g. customer services and marketing). Some firms also use ML in areas such as credit risk management, trade pricing and execution, as well as general insurance pricing and underwriting.
- Regulation is not seen as an unjustified barrier but some firms stress the need for additional guidance on how to interpret current regulation. Firms do not think regulation is an unjustified barrier to ML deployment.
- The biggest reported constraints are internal to firms, such as legacy IT systems and data limitations. However, firms stressed that additional guidance around how to interpret current regulation could serve as an enabler for ML deployment.
- Firms thought that ML does not necessarily create new risks, but could be an amplifier of existing ones. Such risks, for instance ML applications not working as intended, may occur if model validation and governance frameworks do not keep pace with technological developments.
- Firms validate ML applications before and after deployment. The most common validation methods are outcome-focused monitoring and testing against benchmarks. However, many firms note that ML validation frameworks still need to evolve in line with the nature, scale and complexity of ML applications.
- Firms use a variety of safeguards to manage the risks associated with ML. The most common safeguards are alert systems and so-called ‘human-in-the-loop’ mechanisms. These can be useful for flagging if the model does not work as intended (eg in the case of model drift, which can occur as ML applications are continuously updated and make decisions that are outside their original parameters).
- Firms mostly design and develop ML applications in-house. However, they sometimes rely on third-party providers for the underlying platforms and infrastructure, such as cloud computing.
- The majority of users apply their existing model risk management framework to ML applications. But many highlight that these frameworks might have to evolve in line with increasing maturity and sophistication of ML techniques. This was also highlighted in the BoE’s response to the Future of Finance report.(6) In order to foster further conversation around ML innovation, the BoE and the FCA have announced plans to establish a public- private group to explore some of the questions and technical areas covered in this report. Bank of england
Computer-driven asset management firms are trying to tap into artificial intelligence and machine learning to untangle reams of data and place potentially lucrative bets. The average quantitative hedge fund lost 5.25% in the first four months of 2020 while the average hedge fund lost 6.56% during the same time, data from Hedge Fund Research shows.
Nasdaq
A move that comes with heightened regulatory scrutiny
AI-driven financial advice is getting regulators’ attention — Some key areas of concern, FCA documents state, are the practical challenges and barriers to deployment of AI and its potential risks.
Theglobeandmail
In India, DriveWealth, a U.S. based firm in digital trading technology, announced that the firm has partnered with INDmoney, an artificial intelligence (AI) and machine-learning based wealth management platform in India, to bring U.S. stock investing technology and capability to INDmoney clients. INDMoney will be one of the first Indian FinTechs to offer a simple, straightforward experience for investing in U.S. stocks. This will give clients access to the much-demanded U.S. listed stocks and exchange-traded funds (ETFs) using fractional trading.
Finextra, Crowdfundinsider
Private Equity
An Inconvenient Fact: Private Equity Returns & The Billionaire Factory report here (if you read anything this week…)
Private equity funds have failed to outperform equity indices over a 10-year period, but still charged pension funds and wealthy investors billions of dollars in performance fees, according to analysis by the University of Oxford. “This wealth transfer from several hundred million pension scheme members to a few thousand people working in private equity might be one of the largest in the history of modern finance,” Ludovic Phalippou, head of the the finance, accounting and management economics group at Oxford, said in the study released last week.
Fa-mag FT Reddit
Despite COVID-19 Disruption Private Equity Firms Are Still Acquiring Wealth Managers
GTCR has taken a 25% stake in Captrust Financial Advisors, in a deal that values the registered investment advisor at $1.25 billion.
Training
16 Nonspecialist Resources For Learning The Basics Of Wealth Management
Books:
- A Beginner’s Guide to the Stock Market
- The Intelligent Investor
- The Warren Buffett Way
- The Investment Answer
- Mastering the Market Cycle,
- The Power of Zero,
- MONEY Master the Game
- Becoming Your Own Banker
- The Truth About Money
- Simple Wealth, Inevitable Wealth
- Understanding Stocks, for investors, and Understanding Options,
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