GPT for Wealth Management: Enhancing Customer Experience

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Introduction

In the dynamic world of finance, technology continually pushes boundaries. Today, financial institutions seek to enhance customer experiences with a powerful tool: Generative Artificial Intelligence (AI). This cutting-edge technology is revolutionizing finance, reshaping customer interactions, and elevating satisfaction and personalization.

Generative AI, known for creative output and data generation, is now making waves in finance. It offers unique opportunities to transform the customer experience. By harnessing Generative AI's capabilities, financial institutions gain valuable insights, provide hyper-personalized solutions, and align offerings with individual needs.

This article explores Generative AI's impact on Wealth Management in finance. We uncover innovative applications, from personalized financial product recommendations to intuitive virtual assistants meeting customer needs. Additionally, we discuss the benefits, challenges, and ethical considerations of using Generative AI to enhance customer satisfaction.

Customer Pain Points in Wealth Management

In the ever-evolving realm of finance, where wealth management and customer service intersect, customers often grapple with a host of challenges that can significantly impact their overall satisfaction. These obstacles stem from various sources and play a pivotal role in shaping customer loyalty. Here, we delve into some prevalent pain points experienced by customers in the finance sector, specifically in the context of wealth management and customer service:

1. Lack of Personalization: Many clients seek financial advice and solutions tailored to their distinct goals and circumstances. Yet, conventional wealth management approaches often fall short of delivering this level of customization, leaving customers feeling disconnected and dissatisfied.

2. Limited Accessibility: Accessibility issues can arise when clients encounter hurdles in accessing their financial data or communicating with their wealth managers and customer service representatives. Challenges in initiating contact, receiving timely responses, or navigating complex procedures can breed frustration and hinder the customer journey.

3. Complex and Confusing Information: Financial matters are inherently intricate, and the use of complex jargon and technicalities can overwhelm customers. When information is not conveyed clearly and effectively, clients may find themselves bewildered, making it arduous to make well-informed decisions.

4. Slow and Inefficient Processes: Lengthy processing times, excessive paperwork, and cumbersome procedures can be significant roadblocks in the customer experience. Clients demand streamlined, efficient processes that conserve time and effort, allowing them to manage their wealth seamlessly.

5. Inadequate Communication and Transparency: Effective communication stands as the bedrock of trust and robust relationships. Clients place a premium on transparent, proactive communication from their wealth managers and customer service representatives. Inadequate communication or a lack of transparency concerning fees, performance updates, or policy changes can breed dissatisfaction and erode trust.

6. Limited Innovation and Technology Adoption: Expectations are on the rise, with clients anticipating financial institutions to embrace technology and provide innovative solutions to enrich their financial management experience. A dearth of technological advancements, such as user-friendly digital platforms and interactive tools, can leave clients feeling underserved and disconnected.

Mitigating these recurring customer pain points necessitates a customer-centric approach. This approach should encompass personalized services, streamlined processes, transparent communication, and a wholehearted embrace of innovative technologies. Through active engagement with these pain points, financial institutions can craft superior customer experiences, foster lasting relationships, and set themselves apart in an increasingly competitive landscape.

How Generative AI can be used for Wealth Management?

Let's dive right into the crux of the matter. Customers look to financial institutions not just for financial guidance but for personalized advice that aligns with their unique wealth aspirations. They place a high premium on financial expertise to help them navigate the path to their financial goals. Traditional wealth management has traditionally excelled in fostering strong client relationships, with each customer paired with a dedicated relationship manager who intimately understands their individual objectives.

However, here's where things get interesting: the traditional methods of wealth management sometimes fall short of meeting the sky-high expectations for personalization. The limitations primarily stem from the scarcity of relationship managers, leading to challenges in scalability and sluggish communication. This communication bottleneck occasionally results in misunderstandings due to varying levels of subject comprehension. These roadblocks, unfortunately, can turn customers off, leaving them feeling adrift and dissatisfied.

Enter Generative AI, poised to be the game-changer in wealth management. With its ability to sidestep scalability issues, Generative AI emerges as a promising solution. Picture this: every customer is equipped with an AGI-powered Chatbot capable of addressing their queries, understanding their goals, and furnishing personalized financial plans tailored to their specific requirements. It's a potential paradigm shift in customer service that holds the promise of seamless, individualized wealth management experiences.

Now let us see the working of a use case. In this article, we will walk through an LLM-powered Chatbot that will answer user queries.

Demonstrating a use-case: Context-based LLM-powered chatbot for Financial advice

# Importing Dependencies

import streamlit as st
from streamlit_chat import message
import openai
import os

# Mentioning API key

openai.api_key = 'PASTE-YOUR-KEY'
os.environ['OPENAI_API_KEY'] = "PASTE-YOUR-KEY"

# Function to return response from GPT

def fun(prompt):
    response = openai.ChatCompletion.create(
                engine="engine_name",
                messages = [
                            {'role': 'user',
                             'content': prompt}
                          ],
                temperature=0,
                max_tokens=800,
                top_p=0.95,
                frequency_penalty=0,
                presence_penalty=0,
                stop=None)

    response = response['choices'][0]['message']['content']
    return response

# Function that checks whether the question asked is out of context or not. Returns True or False

def context_check(prompt):
    testing_query = f'''
    Instructions:
    Answer the questions only related to "{context_topics}".
    
    Query:
    Study the prompt "{prompt}" and tell whether the user directly or indirectly asking questions related to "{context_topics}".
    Give a response only in "True" or "False".
    
    Remember:
    1. Do no generate any other output, example, code etc. 
    2. Answer should be 1 word only. True or False.
    '''
    response = fun(testing_query)
    return response

#Returns filtered response after context checking

def generate_response(prompt):
    for topic in context_topics:
        if topic not in prompt:
            is_contexual = 'False'

    instructions = f''' 
        Instructions:
        0. Assume yourself to be an expert in answering Financial queries
        1. Answer questions only to the topics mention in: "{context_topics}" at all costs!
        2. Be precise and crisp.
        3. Answer in short.
        '''
    is_contexual = context_check(prompt)
    if is_contexual == 'True':
        prompt += instructions
        response = fun(prompt)
        return response
    elif is_contexual == 'False':
        return "Sorry the question asked doesn't follow the guidelines."

# Gets the input text from streamlit

def get_text():
    input_text = st.text_input("How may I help?", key='input')
    return input_text


with open('only_reply.txt', 'r') as f:
        context_topics = f.read()
context_topics = context_topics.split('\n')[:-1]
# context_topics = ['Finance', 'Wealth Management', 'Investment', 'Wealth']
st.set_page_config(
    page_title="FinBot",
    page_icon="💰",
)st.write("# Welcome to FinBot💰!")
changes = '''
<style>
[data-testid = "stAppViewContainer"]
    {
    background-image:url('https://i.ibb.co/qrrD42j/Screenshot-2023-09-15-at-5-41-25-PM.png');
    background-size:cover;
    }
    
    div.esravye2 > iframe {
        background-color: transparent;
    }
</style>
'''

st.markdown(changes, unsafe_allow_html=True)
if 'generated' not in st.session_state:
    st.session_state['generated'] = []

if 'past' not in st.session_state:
    st.session_state['past'] = []user_input = get_text()
if user_input:
    output = generate_response(user_input)
    js_clear_input = """
    <script>
    const inputElement = document.querySelector('.stTextInput input');
    inputElement.addEventListener('keydown', function(event) {
        if (event.key === 'Enter') {
            inputElement.value = '';
        }
    });
    </script>
    """

# Display the JavaScript code

    st.markdown(js_clear_input, unsafe_allow_html=True)
    st.experimental_set_query_params(text_input="")
    st.session_state.past.append(user_input)
    st.session_state.generated.append(output)

if st.session_state['generated']:
    for i in range(len(st.session_state['generated'])-1, -1, -1):
        message(st.session_state['generated'][i], key=str(i))
        message(st.session_state['past'][i], key="user_"+str(i), is_user=True)

Screenshots

Blocking Out of context question

Contextual Questions

Conclusion

In conclusion, Generative AI stands as a game-changing force in the realm of wealth management. Its ability to provide personalized financial advice and solutions on a scale previously unattainable is reshaping the landscape of financial services. By leveraging the vast potential of Generative AI, financial institutions can navigate the complexities of modern finance with unparalleled precision.

The anticipated impact is profound: clients receive tailored recommendations that align seamlessly with their unique financial goals, risk profiles, and the ever-evolving market dynamics. This, in turn, leads to improved investment outcomes, heightened client satisfaction, and a deepened sense of trust in financial institutions.

As we march forward, the synergy between technology and human expertise will continue to define the future of wealth management. Generative AI, as a powerful ally, empowers advisors and clients alike to make informed decisions, optimize portfolios, and nurture enduring financial success. In this dynamic landscape, the marriage of cutting-edge technology and personalized financial guidance promises to usher in an era of unprecedented prosperity and financial well-being for all.

Author Bio

Bhavishya Pandit is a Data Scientist at Rakuten! He has been extensively exploring GPT to find use cases and build products that solve real-world problems.