The document discusses how artificial intelligence (AI) can enhance wealth management by addressing client management issues through real-time financial planning, tailored solutions, and improved portfolio performance. AI's capabilities, including natural language processing and machine learning, allow advisors to better understand client needs, predict financial events, and respond promptly to uncertainties, thus improving customer experience and operational efficiency. The implementation of AI in wealth management is expected to become widespread, with a significant percentage of advisors recognizing its potential to automate reporting and deliver personalized client interactions.

1. How Artificial
Intelligence can help
Wealth Mangers in
facing Client
Management
issues?
To be presented by : Keyur

2. Assess goals
Define strategy
Implement
Monitor
Key Drivers :
• Advisor gathers info from various department to
offer suitable product
• Open questions leading to frequent inputs from
Clients
• Longer time for planning/offering products
How AI can help?
AI can help in robust Real Time Financial
Planning, make initial meeting more
productive.
With AI’s Natural Language Processing (NLP)
technique, advisor can offer best tailored
solution for client without missing even a
single input from them.
Need to implement:
• Per leading consulting companies wealth management reports, more than 40 % advisors have shown interest in using AI to provide more tailored solutions to the
mass affluent & HNWI (High Net Worth Individual) including millennial's which was otherwise given mainly to UHNWI (Ultra High Net Worth Individual) .
• By 2025, more than 50% of the companies will be using AI to evaluate client’s profile, & offer more suitable products considering various other factors.
AI can dynamically
process/synthesize client’s
inputs in real time by accurately
predicting clients goals &
financial events, estimate
projection & help WM offer
robust tailored financial
solution.
Review Strategy
Client management Issue:
• Build a portfolio as per clients growing needs & changing
expectations
NLP : sentence as spoken : I want to retire at 56.
structured data: Need Life’s event Parameter Trigger Rules
Current Approach :

3. Key Drivers :
• During monitoring period, advisors monitor
performance, associate a reason for non
performance if any.
• Revise strategy, implement the revised strategy
• Resulting, longer time to detect an underlying issue,
Loss in downside/non performing portfolio.
Need to implement:
• As per the reports of leading consulting companies, 68% of advisors feels that AI can help detect & predict 35% of uncertainties, which can be used to protect portfolio
performance.
• By 2021, 40% of risk models will be AI enabled, which can be used to manage downside in portfolio performance due to uncertainties.
Client management issue :
• Maintain portfolio performance as per
client’s expectation in a period of
uncertainty.
• Geopolitical uncertainty
• Growing concerns over the trade war
How AI can help?
• AI’s unsupervised algorithm (Machine learning) uses deep learning technique
which can analyze data from various sources, and arrive at conclusion.
• Combining the above technique with predictive algorithm can help infer results,
Thereby enable advisor to detect & react first in uncertainties.
• AI’s ability to detect uncertainties can help advisor respond timely & mitigate
downside risk, maintain portfolio performance
• AI enabled sophisticated risk based models can thus be applied on the client’s
portfolio, which can protect its performance

4. Key Drivers :
• Frequent regulatory changes, compliance are raising a lot
of doubts/queries.
• Maintaining balance between expectation of Gen X vs
Gen Y, Old vs New, Manual vs Automatic, Slow vs fast.
Need to implement:
• About 54% of advisor believes that AI can help improve customer experience, reduce attrition, concerns can be addressed with accuracy & in real time
• 62% of millennial prefers robo advisor (chatbots), consider its to use, easy advice & offerings, making exciting/interactive experience
Client management issue :
• Address client’s concerns on the fly
• Honor millennial’s expectation such as lower
fees, simple products, greater portfolio
transparency
How AI can help?
• AI’s ML combined with Augmented reasoning (AR) techniques can analyze data
from various sources & logically derive accuracy. This can address client’s
concerns on the go such as complexity around cross border business, compliance
risk. Such questions otherwise are difficult to be answered by advisor.
• Its about giving right info at right time to clients. WM can’t ask clients to wait to
resolve such concerns on their own. These form a key for better customer
experience.
• With AI ML supervised algorithm, Robo advisor, chatbots can be trained by
advisor with samples, which then makes rule & can be used dynamically to
analyze clients input and predict financial events, suggest portfolio.
• Its cost effective, offers simple & comprehensive products information, thereby
help to drive down cost, provide ace customer experience expected by Millennial.

5. Key Drivers :
• Advisors spending a lot of time analyzing data for client’s
reporting.
• Source & amount of data to be analyzed for client’s
reporting are growing & getting complex, thereby taking lot
of advisor’s time collating necessary details.
Need to implement:
• Advisors spend around 15% to 20% of their time in gathering necessary details for client’s reporting.
• Most of them believe AI can help automate, produce most accurate data for reporting, freeing their time to attend more clients.
Client management issue :
• Need for tailored reporting is growing,
mass affluent clients are expecting
personal attention
• Advisors manually gather required data
& prepare performance reports as per
client’s need.
How AI can help?
With help of AI, client’s reporting experience can be taken to a whole new level.
• NLP can help understand clients reporting need from the meeting
• Infer frequency of reporting
Analyze unstructured data gathered in the call, synthesize the scenarios
automatically gather required data from various sources, financial reports and
present advisor with relevant/accurate details for client’s reporting.
Consequently, advisors can focus more time on client’s acquisition, interaction and
still provide tailored client reporting.

6. References
1. “Transformative Nature of AI in Wealth Management”, Dejan Knezevic , Gary Teelucksingh, Capco.
2. “Trends in Wealth Management 2017-18”, Capgemini Wealth Management Report, June 2018.
3. “Disruptive Trend’s in Wealth Management”, Gauthier Vincent, Jared Goldstein, Sean Cunniff, Deloitte.
4. “Could your client need be your competitive advantage? The experience factor: the new growth engine in Wealth
Management”, Ernst & Young Report, EY 2017
5. “Applying AI in Wealth Management”, Ernst & Young, Finantix report, Wealth Briefing, 2017 ClearView Financial
Media Ltd.