disruption in investment managementdisruption in investment … · 2016-11-02 · mutual funds...

Disruption in Investment ManagementDisruption in Investment Management

November 1, 2016

Thank you for the opportunity to be here today

By way of introduction How I wanted to use the time

Brent BeardsleySenior Partner & Managing Director, BCG N Y k

Set a bit of context – current state of the Asset Management industry in 2016

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• Global Head of BCGsAsset and Wealth M t P ti

Discuss disruption at our door step• Digital• Advanced data analytics / AI

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Implication for the asset management fi f th f t

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Nov 1st CFA_CDP Conference vF.pptx 1

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Most challenging time for asset managers since the financial crisis

Worst year since crisis

Stalled asset growth: AuM grew only 1% due to generally turbulent and negative markets

Variation in growth across

regions

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Tepid net flows in the US, but stronger flows in Europe and Asia-Pacific;overall growth still impacted by market impact

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outflows; operations/IT complexity; market uncertaintyChallenging

outlook

regions g p y p

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Data-driven disruption

Advanced technologies start to emerge at mainstream firms and can unleash disruptive opportunitiesAsset managers need to evolve their operating models to support required

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Regulatory pressure

New regulations will enhance challenges, and formalized risk management programs are required

g p g pp qinvestments in data and analytics


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6p g p g q

However, remains highly profitable business overall, and several pockets of growth remain

Industry growth stalled in 2015 – negatively impacted by markets and currency rates

...while net flows held steady at 1.5%AuM rose 1% globally in 2015, holding

industry assets at $71T...

4.04

Average net flows as a % of AuM at beginning of each year

80

100

Global AuM ($T)

1%

5%

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2

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0.1

-0.2-0.5

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29

20

40

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20142013

20122011

20102009

20082015

02014200820072002 2015

Industry growth constrained rather than fueled by capital markets t fl b i d i f th

2003-2007


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Note: Sizing corresponds to AuM professionally managed in exchange for management fees; includes captive AuM of insurance groups or pension funds if those AuM are delegated to asset management entities with fees paid; 43 markets covered globally, including offshore AuM. For all countries whose currency is not the US dollar, we applied the average 2015 exchange rate to all years to neutralize currency impact. AuM decreases shown for past years reflect the 2015 appreciation of the US dollar.Sources: BCG Global Asset Management Market-Sizing Database 2016; BCG Global Asset Management Benchmarking Database 2016

as net flows become primary driver of growth

Profitability continues to be strong, despite decline in net revenues

Net revenues1 (basis points) down 0.4 bpsOperating profit margin held steady

in the 35-40% historical range

373837363535

31

36

4040%

Operating profits/Net revenues1 (%)

27.728.128.928.829.129.026.827.933.6

28.0

20

40

Net revenues1/AuM (bp)

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3129

20%

30%02015201420132012201120102009200820072003

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10%

17.317.518.218.619.018.918.618.020.319.920

40

Costs/AuM (bp)

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0%2015201420132012201120102009200820072003

020152003 20142013201220112010200920082007

Asset managers continue to undertake profound


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1. Management fees net of distribution costs.Note: Based on our benchmarking sample; historic years' data restated to ensure consistency of samples over time.Source: BCG Global Asset Management Benchmarking Database 2016

g pefforts on costs to adapt to decreasing fee margins

Global profit pool remained flat at the 2007 levelFee compression kept growth in net revenue below growth in assets

Global market AuM evolution Average AuM Net revenues1 Costs Profit pool

Evolution of key economics in absolute terms for all asset managers

717180

($T) +1%139

134140

Index+4%

140

Index+3% 140

+4%Index

140

Index

+1%

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71

43

5260 96100

80

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120 114111

80

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120120116

86

100

80

100

120

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69

100

80

100

120+1%

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0End 15

End 14

End 08

End 07

0

20

Avg 15

Avg 14

Avg 08

Avg 07

0

20

151408070

20

0807 15140

20

15140807


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1. Management fees net of distribution costs.Note: Values with fixed exchange rates, year-end 2015 rate; historic years' data restated to ensure consistency of samples over time.Sources: BCG Global Asset Management Market-Sizing Database 2016; BCG Global Asset Management Benchmarking Database 2016

Significant decline in growth across all product categoriesBut strong growth prospects for alternatives, passives, and solutions

Estimated share of cumulative net flowsGlobal AuM split by product (%)

Active specialties2

Alternatives1

$71T7% / ($2T)

22% / ($16T)

12% / ($8T)

$71T

23% / ($16T)

11% / ($8T)

$43T

21% / ($9T)

11% / ($5T)

$34T

20% / ($7T)

15%

5%10%

9%

-3%

4%

23

100%

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Solutions/LDI/Balanced3

13% / ($9T)12% / ($9T)

( )

8% / ($4T)6% / ($2T) 14%

16%6%

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Active core4

Passive excl. ETFs

39% / ($28T)

Passive excl. ETFs

39% / ($27T)49% / ($21T)58% /($20T) 2% 4% 1%

1%42

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PassiveETFs 4.0% / ($3T)

2015

10.8% / ($8T)

2014

ETFs 3.7% / ($3T)11.0% / ($8T)

2008

10% / ($4T)

2003

8% / ($3T)

CAGR

9% 16%-1%

-24

2016 2020

9%


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62016-20201. Includes hedge funds, private equity, real estate, infrastructure and commodity funds, liquid alternative mutual funds (e.g., absolute return, long/short, market neutral, volatility) 2. Includes equity specialties (foreign, global, emerging market, small and mid caps, sector) and fixed-income specialties (emerging market, global, high yield, convertible) 3. Includes target-date, global-asset -allocation, flexible, income, liability-driven and traditional balanced investments 4. Includes actively managed domestic large-cap equity, domestic government and corporate debt, money market and structured products.Sources: BCG GAM Market-Sizing 2016; BCG GAM Benchmarking 2016; ICI; Preqin; HFR; Strategic Insight; BlackRock ETP report; IMA; OECD; Towers Watson; P&I; Lipper; BCG analysis

Winner-take-all trend accelerated in US, held steady in EuropePassive assets dominate net flows in US market

Top 10 asset managers, by mutual fund flows in the US

Top 10 asset managers, by mutual funds flows in Europe

Assetmanager

2015 net flows ($B)

Cumulative share of

total market net flows

Cumulative share of net flows of players with

positive net flows

Passive flows per

firmAsset

manager

2015 net flows ($B)

Cumulative share of

total market net flows

Cumulative share of net flows of players with

positive net flows

Passive flows per

firm

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Vanguard 230 128% 38% 97%

BlackRock 106 187% 56% 96%

TCW1 17 196% 59% 0%DimensionalFund Advisors 16 205% 62% -1%

BlackRock 65 13% 10% 56%

Deutsche AM 26 18% 14% 43%

ISP-Eurizon 22 23% 17% 0%

UBS 20 27% 20% 42%

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Edward Jones 15 214% 64% 0%CharlesSchwab 14 222% 67% 105%

DoubleLine 14 229% 69% 0%

WisdomTree 14 237% 71% 103%

Pioneer 19 31% 23% 0%

Credit Suisse 17 34% 25% 46%

Nordea 16 37% 28% 4%

Standard Life 16 41% 30% 0%

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JP Morgan 13 244% 73% -2%

Deutsche AM 13 251% 75% 123%

Total market 180

Vanguard 16 44% 33% 100%

Allianz GI2 15 47% 35% -1%

Total market 497

121% 68%2014 ratios: 42% 31%2014 ratios:

versus versus


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1. TCW includes Carlyle Group Funds 2. Excludes PIMCO.Note: Analysis excluding money market funds.Sources: Strategic Insight, BCG analysis

xx: New player in top-10 ranking in 2015, compared with 2014 rankings

121% 68%2014 ratios: 42% 31%2014 ratios:

Technology has led to a 'big bang' of new informationTrying to process the arrival of news as the driver of the random walk of security prices

1890s 1990s1970s1960s 2018 – 2020+

1994Electronic

1900s 1980s

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al

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1897Edison Universal Stock Ticker

1909John Moody develops Bond Ratings

1962Electronic company fundamentals

1960Historical pricing databases

1971Earnings estimates

1984Electronic broker research

Electronic filings

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Tech ad

1963Econometric time series on securities

1979Institutional holdings

New unstructured datasets and machine intelligence

1906Summarized company financials

1989Program trading starts to be used by financial institutions

2000Introduction of high frequency trading

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Inst

itutio

nal

capa

bilit

ies


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Source: BCG, Visible Alpha

Innovative models: Fintechs are seeking to change the game

Robo-Provide automated financial advice and portfolio constructionRobo-

advisorsconstruction

• Build portfolios based on user-defined risk limits and goals• Rebalance portfolios automatically

Portfolio Aggregate positions across multiple client accounts

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Portfolio management

platforms

gg g• Aggregates data from multiple accounts, to simply tracking,

analysis and development of a consolidated view

Data Consolidate and analyse information from multiple sources

ng G

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analytics and information providers

Consolidate and analyse information from multiple sources• Help support investment decisions, using information from

news, social media and other investor opinions

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Network investors

Track strategies across a network of investors • Allow users to observe and replicate the portfolio of other

successful investors• May also provide execution capabilities


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Source: Company websites

Various actors are starting to play across the value chain –many moves driving increasing disintermediation

Manufacturers(Asset Managers)

Distributors(Channels)

Other intermediaries(New models, influencers)

I ti t di t ib tInvesco continues to distribute through advisors, but provides new robo tools with embedded product

Goldman acquires Honest Dollar, a retirement robo for small business employees –tapping into new and different pools of money

State Street builds innovative end

+

Manufacturers(e.g., CG, Blackrock, Franklin,

+

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ChinaAMC disrupts the traditional consumer distribution models by partnering with WeChat to sell mutual funds directly to investors

State Street builds innovative end investor engagement tools with"Ideas" iPad app, including thought leadership +

PIMCO, T Rowe, etc)

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Distributors ('Channels' – wirehouses, RIAs, BDs,

etc.)

Vanguard disintermediates traditional advisors & adapts offering with branded, hybrid (digital + human) model, Personal Advisor Services

Schwab moves into asset manufacturing – develops proprietary funds

Home office has growing

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Other intermediaries(Digital platforms for direct purchase /

robo providers)

Betterment building capabilities to support advisors, acting similarly to TAMPs / middleware providers

influence over advisor decisions


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Disruption across the value chain is impacting the traditional model

Digital maturity in investment management still relatively low

Technology Advancement

AI as a major tool throughout wealth value

chainPortfolio analysts at risk

TodayAdvancement

Client management optimized with cognitive

computing Advisors act primarily as

chainas most allocation is automated

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White-labeled portfolio management tools become popular

Strategic / Smart Beta strategies become

co pu g Advisors act primarily as relationship managersResearch analysts at risk

as data aggregation and analysis is automatedElectronic

trading revolution launched

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Excel-based wealth management and risk measurement

Paper-based onboarding

Investment automation tools released Quantopian, QuantConnect

and Uqer.io crowdsource quant investment strategies

strategies become increasingly popular

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WM b i i ti i /

Funds explore quantitative finance IBM Watson explores wealth

management applications. DWMs like Marstone develop

B2B offering for FAs


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TimeWMs begin investing in / exploring robo advisors

As digital maturity grows, significant opportunity for innovative technologies are not that far away

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Big Data Machine Learning Cognitive ComputingData sets too large for traditional processing methods to work. Several methods have been

t d t ll t t d

Machine learning enables a computer to improve decision-making and conclusions by

ti l i

Development of a model that simulates human cognition. Models develop inference

tt i hi l iWhat is it?

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analyze big data to reveal previously unknown insights

continuously processing new observational data

patterns using machine learning algorithms to solve problems such as games of chess

Firms able to reconcile and analyze big data can better

Machine learning can help advisors better

Models built from cognitive computing can support

What is it?

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ny g• Understand and predict client

patterns• Provide superior market

insights to clients• Monitor suspicious activity

• Recommend products that similar customers have used

• Monitor market trends to support investment decisions

• Understand changing risk

g• Prediction of client life events

and expected impact on portfolio constraints

• Improvements to rebalancing based on needs assessment

How can it be applied to Wealth Manage-ment?


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6p yand risky behaviour

• React to issues in corporate operations

g gfactors in volatile markets • Semantic analysis of client

communications

ment?

Data-enabled advanced analytics starting to exist across scope of Asset Management activities

Example uses of advanced analytics, Machine learning tools, etc

Lattice, a California-based start-up, (is partnering with Invesco (and

others) to develop predictive sales analytics models for wholesalers

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Compliance ITResearch and investment

Marketing, Distribution

& Sales

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Aidyia, a hedge fund inH K h l h d f d

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HFs experimenting with tools like Palantir and Digital Reasoning to integrate internal & external data to identify likely insider trading violations


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Opportunities to leverage new tools exist at each step in the investment process

Surface questions & topics

Develop hypotheses Test hypothesis Take investment

action

Monitor & update

decision

Learn from previous decisions

Explore open-ended ideasWhat will the "Internet of things" mean for different companies in the consumer packaged-goods space?

1

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Develop and test hypothesesWhat is the impact of an interest rate increase on financial companies with a low P/E?

2

Surface patterns and triggers3

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3

Visualize data in ways that raise new questionsHow will my duration exposure change with my decisions?

4

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Aggregate, synthesize, and automate informationCan we build "institutional memory" around analyses, specific targets?

5


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Learn from previous behaviors and decisionsHas exposure to lower P/Es and profit margins and higher dividend payouts improved my portfolio returns?

6

Similar story in distribution

Three levels of maturity of Advanced Analytics in Distribution

Predictive analytic tools to make advisors 'smarter'

3 3

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advisor base on new information and

advisors smarter

2 2

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new heuristics2 2

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Collection of new & betterdata on advisors & their clients1 1


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Advanced analytics can be used across Distribution activities

Distribution Performance

Distribution lifecycle

Examples of common use cases

stat

ic

Performance managementProspect & acquire Sustain & grow Retain

Consolidated management

Create baseline advisor segmentation by value and behaviors (e.g., to prioritize sales activities, create customized sales plans)

Identify most effective tactics to influence intermediaries (e g sharing proprietary insights

1

2 10

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Mor

e Consolidated management dashboards

Identify most effective tactics to influence intermediaries (e.g., sharing proprietary insights, relationship building)

Model performance data to optimize incentive structure for sales team and for intermediaries

Identify best prospects (from new/existing intermediaries) for new fund launches

3

6

11

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s rIdentify fund-level triggers (e.g., outperform, underperform) most likely to create sales or redemptions opportunities

Systematically generate lead lists based on advisor profiles

Provide recurring data-driven feedback to Product teams

intermediaries

Predict which advisors have highest potential to drive additional sales (e.g., up-and-

4

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"rea

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Develop advisor-specific, time-relevant product recommendations (e.g., cross-sell)

Proactively identify intermediaries 'at risk' for large redemptions or change in sales patterns

p ( g , pcoming)

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Mor

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Systematically identify "next best actions" for wholesaler associates

p

5

Innovative players have started to apply new technologies to solve regulatory compliance pain points

Challenges for captive AMs

Example of emerging RegTechsolutions tackling pain points Example of vendorscaptive AMs solutions tackling pain points Example of vendors

Compliance dashboards

• Machine learning and advanced analytics to organise and analyse large volumes of unstructured and structured data

• Data visualisation, reporting, and workflow to track, report

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and resolve compliance issues

Data sharing and regulatory

• Facilitates secure sharing of information between institutions (e.g. asset managers and insurers), using encryption and data ingestion technology

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reporting • Data standards, designed around regulations, for streamlined reporting

Monitoring internal culture

• Help improve communications surveillance, recognise behavioural patterns from data to prevent fraud

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• Machine learning and predictive analytics for markets trade surveillance to prevent insider trading

Interpreting new • Cognitive computing/deep learning techniques that enable "regulatory radar" software with understanding of


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6p gregulations regulatory radar software with understanding of

regulations

Source: Press clippings, BCG analysis

Investment Management Firm of the Future

Today's Investment Firm Investment Firm of the Future

• Correlation models / predictive analytics based on observable historical data

• Data / data mgmt as competitive advantage• Big Data , Artificial Intelligence, Social Media

powering investment decisionsTechnology

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• Post-crisis regulatory environment focused on the past crisis issues

• CIO communicating to clients/regulators

• Regulatory oversight with external boards• Due diligence as a systematic, on-going

oversight and governance processTransparency

A t l il i k t ith t ti fi Ri k b d l di i di t t l i

ng G

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s r• Asset class silo risk systems with static firm-

wide risk systems (e.g., counterparty risk)• Operational risk silo

• Risk based on leading indicators not lagging• Integrated, dynamic risk management across

public and private/ illiquid asset classesRisk

Management

I di id l it l ti ti f d I t t th d t

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n• Individual security selection active fund section asset allocation with passive

• Investment theses expressed across asset classes including public and private / illiquid

• Influencing outcomes / activist investingAlpha Creation

• Focus on cohesive culture • Professionalize human capital management


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6• Focus on cohesive culture• Little real talent management

• Professionalize human capital management –workforce planning, leadership development

• Firm leadership as a professional CEO – not part time CIO/Sales

Culture / Talent

Unless they evolve, today's leaders will be replaced...Today's Leader Potential Future Leader

Discount / Online BrokerageR bi H d

g

Full-service Brokerage

Robin Hood

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Fixed Income Manager

Public Equities Manager

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Private Equities Manager

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Fund of Funds

Angel Investing

Direct Investment

Individual angel groups


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Questions?

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Thank you

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disruption in investment managementdisruption in investment … · 2016-11-02 · mutual funds...

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