ai and ml in wealth management

AI AND ML IN WEALTH MANAGEMENTVASUNDHARA

PLAN OF TALK

Overview of AI and ML in Wealth Management

AI and ML on Advisor End

AI and ML on Client End

Future of AI and ML in Wealth Management

Drawbacks of AI and ML in Wealth Management

Conclusion

VASUNDHARA, CASE STUDY 1

OVERVIEW OF AI AND ML IN WEALTH MANAGEMENT







Conclusion

THE PAST TWO DAYS……


Human

Machine

Statistical

Data

Empathy

Fin

anci

al

Advi

ceFutureClients

Qualitative

Inve

st

Evolve

Risk

Business

Accuracy

Models

Portfolio

Security

Tre

nds

Crisis

Investments

Analysts

WHY AI/ML IN WEALTH MANAGEMENT?

NLP, Computer Vision, Voice Recognition can be used for analyzing data hidden in phone and video calls,

documentation, web scraping client and competitor websites

Genetic algorithms, ANNs can be used for portfolio optimization

ANNs, SVM can be used to give a more accurate estimate of expected returns

SVM, Decision Trees, Cluster Analysis can be used for stock market prediction


[1]



[2]



95% of respondents continue to

rely on MS Excel and 75% on

desktop market data tools for

their investment strategy and

processes

[3]

WHERE TO APPLY AI/ML IN WEALTH MANAGEMENT?


Cybersecurity

Client Communication Risk Management

Overall Client

ExperienceInvestment Advice

Forecasting Portfolio Returns

Trading Strategies

Personalized Insights

BEFORE MANAGING WEALTH


Journey Continues

1. Person A,

goes on the

website and

clicks on a

link

2. Based on

the article,

draw insights

3. Offer a

monthly

newsletter?

4. If accepted,

track their

interests,

behavior

5. Make an

email offer

6. Get a data

point

[4]

AI AND ML ON ADVISOR END







Conclusion

HOW INTELLIGENT MACHINES CAN HELP?


Seamless Client Experience

Digital technologies can be used to

deliver a personalized, consistent

and efficient experience. Robo-

advice is AI based automated

advice solutions which supports

clients when they make decisions

Marketing and Sales

Optimization

Enable business development by

providing tools and insights for

better results. Use AI enabled

dashboards, which adapt to every

interaction between advisor and

client to access information

Content Effectiveness

Produce and distribute relevant

high quality content on demand to

consumers. Predictive modelling

can provide unique insights and

better decision making

[5]

HOW INTELLIGENT MACHINES CAN HELP?


Portfolio Management

Generating automated insights by

reading transcripts to assess

management sentiment. Using

corporate website traffic to gauge

future growth along with clients’

behavioral patterns. Mapping

market trends and clients’ financial

goals

Client Engagement

Identifying non-intuitive

relationships between securities

and market indictors. Smart client

outreach and demand generation

via analytics, using alternative data

sources such as social media data

Front, Middle and Back

Office Efficiency

ML is used to automate functions.

AI and ML based algorithms for

cyber security. Chatbots and ML

used to respond to client and

investor queries, generating

management report on demand

[5]

SURVEY RESULTS


Wealth Managers, When asked which statement

best expresses your opinion of the digitization of

wealth management services?

[6]

Forbes and Temenos surveyed a

sample of 219 wealth managers

Wealth managers see AI as a game changer

and important tool for delivering their

results.

33% believe AI has the ability to transform

wealth management for better, 71% are already

seeing results from these technologies in

portfolio returns, 71% in client communication

and 68% in overall client experience.

SURVEY RESULTS


Wealth Managers, How do you characterize your

level of deployment or interest in AI technologies

in your organization?

As a wealth manager, how do you view robo-

advisors?

[6]

AI AND ML ON CLIENT END







Conclusion

CLIENT SERVICE – FLOW CHART


CLIENT CATEGORIES


Traditional

Generally, older

Less tech savvy

Need more human intervention

More wealth accumulation

New Age

Generally, younger

Tech enabled

Need less human intervention

Growing wealth

AI/ML FOR CLIENT’S BENEFIT


Client Knowledge

Tailoring investment decisions

based on social indicators directing

towards major life events.

Personalized Engagement

Meeting client demands like ways

and frequency of communication

i.e. most effecting way of engaging

with them. Providing explanations

for financial decisions.

Ensuring Compliance

Providing insightful content and

timing to financial advisors which

must fall within bounds of internal

policies and external regulatory

compliance

SURVEY RESULTS


What is your attitude about the use of AI in

managing your wealth?

Percentage of clients who agree with the

following -

Forbes and Temenos surveyed a sample of

91 high-net-worth individuals (76% with

net worth between £1million and £ 9

million)

FUTURE OF AI AND ML IN WEALTH MANAGEMENT







Conclusion

FUTURE OF WEALTH MANAGEMENT


“Your next financial adviser might be a

centaur -- not half-human, half-horse,

but half-human, half-machine.

It’s Not Creepy, It’s the Future by Jason Zweig,

Wall Street Journal, September 2016

FUTURE OF WEALTH MANAGEMENT


Robo-Advisors

Automate asset allocation and

portfolio management

Chatbots

Respond to individual client’s

situation and predict certain issues

that might arise. Can offer correct

answers or information to clients’

concern or need. Create a

wholesome experience in first

experience

AI + HI Model

Big data is better processed by

machines, however, human

intervention is necessary to

maintain these models and ensure

robust outcomes. Analysts can be

used for higher value tasks

requiring more experience and

judgement

DRAWBACKS OF AI AND ML IN WEALTH MANAGEMENT







Conclusion

DRAWBACKS

COST – Upfront launching and maintenance

TECHNOLOGY – Still in its nascent stages, staying current with latest challenges

VISION and TIME – Fully penetrate into business and integrate into existing investing process takes time

HUMAN INTERVENTION – Lacks human empathy, human intervention required in decision making with respect

to rare events and noise

CLIENT SATISFACTION – Clients interested in process too not just results, AI lacks transparency

MODEL BIASES – AI models might have their own biases based on the data or training process


CONCLUSION







Conclusion

CONCLUSION

AI/ML is a promising technology that can reduce the negative effects of human biases on investment decisions

Can be used at various stages of the wealth management process like security selection, portfolio construction

and trading executions

Goal is to create models that prioritize and learn using the FA’s intuition, experience and empathy and create a

list of things that are the best possible action to take

Humans do things differently and powerful ways and machines do things in very technical and capable ways,

should not be compared, but marry those two things together

AI of the future – Will be imaginative, creative, ask questions about the data, draw insights like a person


REFERENCES

1. Artificial intelligence in asset management, CFA Institute Research Foundation, Literature Review, 2020

2. Transformative nature of AI in wealth management, Capco

3. AI pioneers in investment management, CFA Institute, 2019

4. Presentation by Chris Kovel, Managing Director – Wealth Management Technology, Morgan Stanley -https://www.youtube.com/watch?v=XCpOZCIAs0k&t=1390s&ab_channel=Ai4

5. Artificial Intelligence: The next frontier for investment management firms by Deloitte

6. AI and the Modern Wealth Manager: How Artificial Intelligence is Creating a Personalized Investing Experience, by Forbes Insights and Temenos


https://www.youtube.com/watch?v=XCpOZCIAs0k&t=1390s&ab_channel=Ai4

ai and ml in wealth management

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