Chatbot Research Paper_FIL GDW_Edited_v0

GLOBAL WEALTH
FIDELITY CHATBOT
RESEARCH
OCTOBER 2017
1

CONTENTS
EXECUTIVE SUMMARY 3
Overview 3
Context 4
Key Findings 5
The research team 6
USER RESEARCH 8
Overview 8
Persona 9
User Journey 10
Use Cases 13
Chatbot Service Blueprint 17
UK perception of Chatbot 23
German perception of Chatbot 26
Competitor Analysis 28
TECHNICAL RESEARCH 36
Introduction 37
Sample Architecture 39
Generative vs. Retrieval Based Chatbot Models 40
Implementation Options 41
Chatbot Capabilities 40
REFERENCE 46
MARKET RESEARCH 18
Global perception of Chatbot 19
2

EXECUTIVE SUMMARY S
Overview
Objective: develop an intelligent, scalable virtual assistant that will
enhance both our customer journey and experience for Fidelity’s
Global Wealth platform.
This workstream is currently working toward 2 sequential delivery
targets: the ‘Engage’ site (Q1’18) and the MVP launch (May ’18). To
maximise the benefits of a lean framework, we are taking a rapid
prototyping approach to the ‘Engage’ phase. This will allow us to
accelerate, learn and deliver in an agile manner.
This research paper presents the findings from the research phase of
this project, which follows a design thinking methodology and
commenced in September 2017, spanning 13+ weeks in total:
Research
Design
Build
2 weeks
3 - 4 weeks
8+ weeks (ongoing)
Design thinking puts our customers at the center of our platform. The
more our bot is designed with our customers needs in mind, the more
successful it’s likely to be. Understanding our customers needs, pain
points and desires therefore formed an integral part of our research.
In turn, our research informed several workshops involving the wider
GDW team (relevant stakeholders, incl. technologists, data scientists,
architectures) to formulate the use cases and user journeys that we
have also developed as part of this phase.
This paper also explores macro- and micro- factors relevant to the bot
landscape, including: customer perceptions of bots (especially within
our target markets), expectations, ‘best of breed’ bot qualities,
competitive landscape, technology integration and requirements.
The comprehensive bot-service blueprint (p.17) is a culmination of our
research and ultimately functions as a roadmap (that will continue to
shape as we gain traction) for us to maintain our long-term view as we
work toward our shorter-term delivery dates.
Structure: This paper consists of 3 primary sections, split across user,
market, and technical research.
• User research uncovers customer needs and identifies different
journeys that users might take to interact with our bot
• Market research includes bot capabilities within the wealth
management industry and across industry as well as chatbot
perception in the German market will determine our chatbot
design direction to optimise the customer experience.
• Technical research includes the feasibility of channel of
communication and an assessment of chatbot vendor options,
whilst identifying the data needed for the prototype. At the
end, this research will help inform our chatbot service blueprint
that brings together the customer journey map and customer
needs from a holistic viewpoint with the underlying technology
and data.
3

EXECUTIVE SUMMARY
Context
Boasting broad appeal due to their efficiency and ease of interaction,
chatbots are gaining traction globally and across industries. One
survey, incorporating more than 5,000 consumers from 6 countries,
found that 38% of consumers globally already have a positive
perception of chatbots, despite the technology being relatively new.
These findings align with the vision of key technology players including
Facebook, Google, Microsoft, Amazon, and IBM as well as Gartner.
The consensus is that chatbots, driven by artificial intelligence (AI), will
play important roles in interactions with consumers, within the
enterprise, and in business-to-business situations. Likewise, the
increasing amount of multiple open-source bot frameworks will lead to
a proliferation of readily available bots that can be used across
businesses.
From a business perspective, there are multiple benefits of a wellharnessed
chatbot. Their presence enables human servicing agents to
focus on higher value tasks, producing the potential to reduce both
complexity and costs behind the operating service model. From a
customer standpoint, as AI-related capabilities continue to become
commonplace, expectations will increase whether or not financial
services have caught up. Enterprises that fail to address the
developments of AI within their businesses are likely to suffer the
consequences.
Whilst overall sentiment toward bots outweighs the negative, the
majority of consumers still prefer human assistance. 56% of global
consumers still prefer speaking with humans, while 60% of respondents
believe a human would better understand their needs than a bot
would.
Nevertheless, advancements in artificial intelligence (AI), coupled with
the proliferation of messaging apps are fueling the development of
bots. A number of organisations have already deployed bots on their
messaging and collaboration channels, including Bank of America,
Wells Fargo, Mastercard, Alibaba, Wall Street Journal, and CNN. By
2020, nearly 80% of companies plan to field all first-line user-business
interactions via bots. A 2017 Gartner report similarly indicates that by
2019, 40% of enterprises will actively be using bots to facilitate
business processes using natural language interactions.
In UK, 75% of UK consumers have not yet interacted with a bot, but 57%
are aware of what bots are. Over 35% want to see more companies
using bots to answer questions, whilst 43% perceive bot adopters as
innovative. The German landscape is less developed but nonetheless
encouraging: 46% claim not to know what a bot is, but 1 in 4 citizens
(25%) are open to communicating with bots. 41% meanwhile find bots
attractive in customer servicing situations. Ultimately, indicating a
divide in opinion between those aware and unaware of bots. The
study also shows that the German market generally trusts bots to
complete simple tasks - such as updating an address or querying an
account. In a worldwide comparison, the Germans ranked as most
sceptical about bots when it comes to making payment.
4

Key Findings
User research looking at the needs and desires of users revealed
several use cases across user groups, which we categorized into 4
themes:
Seeking information:
Each individual is different. This means how a user perceives
information and the way they access and digest information are all
different too. With limited content on the marketing site including its
structure, layout, context, and mood and tone, sometimes it is difficult
for users to find information they are looking for. A chat bot can help
discover content by a user that might not immediately be signposted –
or might be obfuscated to improve the customer experience e.g. terms
and conditions.
Getting Guidance:
Several factors were highlighted as major concerns across all
participants, including: the ability to understand the service and how it
works, and the ability to make a decision around whether the service
is suitable for the individual. This was particularly concerning for those
new to investing.
Many participants felt clueless about the value of investing, lacking the
ability to determine how one service differs from another. That is,
many require a level of reassurance to ensure they are taking the right
investment decisions and their financial future is secure. This is a
significant opportunity to provide guidance and offer personalized
recommendations using a broad and varied set of data and analytics
capabilities.
Reporting problem/complaint/feedback:
According to a Nielsen study, 56% of consumers in Germany would
rather handle customer service issue by chat than over the phone.
When it comes to technical support, customers are already frustrated
enough – so as a service, we need to ensure that their issues are
resolved quickly and easily. On the other hand, businesses do not
want to prevent customers from completing transactions, especially
financial transactions including payments.
Given that most of customer inquiries will likely require similar,
repetitive answers from a support agent, a business can improve
efficiency through a chat bot by reducing time and effort dealing with
common issues – only escalating to a human where required.
Completing an action:
In a digital world, where customers are used to completing
transactions or orders via their virtual assistants (e.g. asking Amazon’s
Alexa to check bank balance or telling Apple Siri to transfer money), it
is necessary to manage customer expectations on a chat service. Key
metrics are ease, simplicity and security. The provision of these
positive effect on transaction rates, encourages further interaction and
provides a more convenient customer experience.
5

THE RESEARCH TEAM
This paper has been written by a research team following a 2-week Research phase, conducted by the following people:
SOPHIE
WIHLBORN
Fidelity, AI Product Owner
PLOY
SUTHILEELAKUL
SPARCK, Strategy Consultant
HARSHA
THARKABHUSHANAM
BJSS, Data Scientist
6

DETAILED FINDINGS:
USER RESEARCH
7

USER RESEARCH
Overview
Design thinking puts the user at the centre of the provision of a service or product. If they are designed with the user at their heart they are much
more likely to be successful and meet user needs. Understanding the needs, pain points and desires of the user is therefore a key focus area for any
research phase.
This research initiative was undertaken over a 3-week period beginning in September 2017. This section details the results from the user research and
includes:
1. Persona
2. User Journeys
3. Use cases
4. Chatbot Service Blueprints
8

Persona
Personae are composite characters created from the behaviours and
psychologies of your target users derived from user interviews and contextual
studies.
They are useful for helping team members understand and empathise with their
users, their needs and goals—and thus create better products for them. Personae
ensure the different users are at front of mind when making crucial design
decisions, for example, “What should be the mood & tone as well as the
personality of the chatbot for Brigitte, a career-driven young professional?
Each persona includes a variety of demographic information:
• A user quote and representative picture quickly establishes a more
personal identity for the persona, putting their main issue front and
centre.
• Their name, age, ‘job’, location, education, and biography are used to
broadly outline the parameters of that persona.
• Their motivations, capacities and issues provide important details that
inform the product design and prototyping stages.
• The technology they use frequently and their most popular social media
channels or tools are included to inform design decisions around the
suitable type of technical solution, user experience or social media
integrations that should be considered.
Together they help the team design a product that is attractive, useful, usable
and sticky.
For the project of this purpose, we have selected Brigitte as our key wealth
persona to focus on.
9

User Journey
User journeys are useful for capturing the customer experience across touch points, including what the customer is doing, thinking, and/or feeling. It
captures positive/negative aspects of the various touch points that users interact with. When designing a new service, user journeys enable us to
understand the ideal world of a customer’s pain points and desires and to see what services could fit seamlessly into a customer’s world.
In order to draw out the most effective journey that is relevant for Fidelity GDW, we chose to integrate key use cases into 2 different user journeys that
engage 2 different phases in our service blueprint: ‘ENGAGE’ and ‘IN-LIFE’ journey,
10

Engage Journey:
11

In-Life Journey:
12

Use Cases
Developing a deep understanding of users’ needs and desires within the context of the connecting customers to chatbot is essential for designing an
overall experience that meets their real needs. Based on the user journeys, user research, latest developments in the application of machine
learning, the following use cases were considered as key propositions.
I can’t find the
information I’m
looking for
I need instructions
for how to do things
I want to ask
questions about
service information
eg. fees
I have questions
related to my
portfolio that I want
answers to
I I I I
I want to talk about
specific news/events
in order to get more
insights I
I need an
explanation for this
term
I
I need someone to
assure that I’m doing
the right thing
G
I need guidance to
make decisions
G
I
G
P
Seeking information
Getting guidance
Reporting problem/complaint/feedback
I need some
information/stats/
data to help me
make decision
G
I need explanation
for what I’m reading
G
I want to discuss
about specific news/
events related to my
portfolio G
I need technical help
P
A
Completing an action
I need to provide
feedback or complain
I want to complete
this whole process
via chatbot
I need to make a
transaction
P A A
I want to make
changes to my
account details
A
Bots for Customer Support Agent
13

Use Case 1: Seek information
Each individual is different. This means how a user perceives
information and the way they access and digest information are all
different too. With limited content on the marketing site including its
structure, layout, context, and mood and tone, sometimes it is difficult
for users to find information they are looking for. A chat bot can help
discover content by a user that might not immediately be signposted –
or might be obfuscated to improve the customer experience e.g. terms
and conditions.
With natural language processing of chatbot, this will allow customers
to access information more quickly and convenient.
The use case will address following needs and pain points:
• I can’t find the information I’m looking for
• I need instructions on how to do things
• I want to ask questions about service information
• I have questions related to my portfolio that I want answers to
• I want to talk about specific news/events to get more insights
• I need an explanation for this term
The use case attempts to answer the following questions:
• Is this product right for me?
• What are the fees I have to pay?
• What is the account opening process?
Use Case 2: Get guidance
Understanding what the service is and how it works, and then
deciding whether the service suits them was a major concern for all
users; especially those who are new to investing.
Many felt clueless about investing and its value – and indeed how a
service is different from another in the market. Many need some level
of reassurance that their investment decision is right and financial
future is secure.
There is a significant opportunity to provide guidance and offer
personalised recommendations using a broad and varied set of data
and analytics capabilities.
The use case will address following needs and pain points:
• I need someone to assure that I’m doing the right thing
• I need guidance to make decisions
• I need some information/stats/data to help me make decision
• I need explanation for what I’m reading
• I want to discuss about specific news/events related to my
portfolio
The use case attempts to answer the following questions:
• How much should I invest?
• Why I should invest?
• Am I making the right decision?
14

Use Case 3: Reporting problem/complaint/feedback
Several factors were highlighted as major concerns across all
participants, including: the ability to understand the service and how it
works, and the ability to make a decision around whether the service
is suitable for the individual. This was particularly concerning for those
new to investing.
Many participants felt clueless about the value of investing, lacking the
ability to determine how one service differs from another. That is,
many require a level of reassurance to ensure they are taking the right
investment decisions and their financial future is secure. This is a
significant opportunity to provide guidance and offer personalized
recommendations using a broad and varied set of data and analytics
capabilities.
The use case will address following needs and pain points:
• I need technical help
• I need to provide feedback or complain
The use case attempts to answer the following questions:
• What should I do, the screen disappears after I confirmed my
top up order?
• Why I can’t access my account from the new laptop?
• I can’t remember my password, how do I reset?
Use Case 4: Complete action
In a digital world, where customers are used to completing
transactions or orders via their virtual assistants (e.g. asking Amazon’s
Alexa to check bank balance or telling Apple Siri to transfer money), it
is necessary to manage customer expectations on a chat service.
Key metrics are ease, simplicity and security – this has a positive effect
on transaction rates, encourages further interaction and provides a
more convenient customer experience.
The use case will address following needs and pain points:
• I want to complete this whole process via chatbot
• I need to make a transaction
• I want to make changes to my account details
The use case attempts to answer the following questions:
• Can you please top up £250 to my home goal?
• Can you please change my email address to….?
• Can you please send me the report from the last month?
15

Use Case 5: Chatbot for support agent:
On the other side of the coin, apart from considering how chatbots
could assist our end customers, it is worth exploring how chatbots
could assist our servicing agents in the future. According to IBM
Watson, 61% of failed customer support calls could have been
remedied if the agent had better access to data.
What if the support agent not only had access to real-time data,
delivered by chatbot, but also could get recommendations around
how they should best handle a customer’s problem? Additionally,
Gartner reports that by 2017, only 1/3 of customer service interactions
will involve human efforts. Chatbots are the face of a new era in
customer servicing technology.
The use case attempts to answer the following needs:
• I want to view last conversation that customer has with the
chatbot
• I want to extract data been collected by the chatbot
The use case attempts to answer the following questions:
• When did the customer report this issue?
• How much does the customer usually top up?
• What was the customer initial contribution?
From a conversational perspective however, there are gaps in natural
language capabilities amongst the majority of bots in financial
services. Ultimately, this culminates in a huge opportunity for Global
Wealth to emerge with a competitive advantage by properly
harnessing the benefits that come with a truly personable and
functionable customer facing bot.
Existing competitors are already starting to recognise how the AI and
conversational user interface behind bots can help offer a better
product and customer experience. In October 2017, MoneyFarm
secured a deal that acquires chatbot start-up, Ernest, with the goal of
integrating the technology across their product offering to enable them
to "assist over an individual's full wealth lifecycle" 1
16

I can’t find the
information I’m
looking for
I want to talk about
specific news/events
in order to get more
insights I
I need some
information/stats/
data to help me
make decision
I need to provide
feedback or complain
I
P
FAQ Content
Register
Interest
Generic chat
Conversatio
n
Create
investing
profile
Provide
Recommend
ation
Explain
decisions
Payment
Setting
View Chat
History
Geo Analysis
Behaviour
Monitoring
Client
identification
(non-secure
site)
Conversation
Response
Generation
Customer
Profile
XX
I need instructions I want to ask
I have questions
for how to do things questions about
related to my
service information portfolio that I want
I I eg. fees
I answers to I
G
Seek information
I need an
explanation for this
term
I need explanation
for what I’m reading
I want to complete
this step via chatbot
Report problems/complaints/Feedback
Marketing
Content
Export chat
history
Share news/
insights:
internal
Goal
Suggestion
Provide
Forecast
Top up/
Withdraw
What-if
scenarios
Update
Profile
Local
language
integration
(NLG)
Help Desk
Augmentatio
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Enrichment
Risk Profile
XX
I
G
Service
Information
Terminology
explanation
Share news/
insights:
external
Goal Setting
Account
Opening
Process
Provide
Transaction
History
Provide
Report
Account
Management
Help Desk
Integration
Sentiment
analysis
Anomaly
Detection
Natural Language
Understanding
I need someone to
assure that I’m doing
the right thing
I want to discuss
about specific news/
events related to my
portfolio G
I need to make a
transaction
P A A
Bots for Customer Support Agent
Digital
Passport
User Details
XX
G
A
G
I need guidance to
make decisions
I need technical help
I want to make
changes to my
account details
Get guidance
Complete action
People Like
you Analysis
Tool Tips
(how-to’s)
Voice
Command
Goal Editing
Portfolio
Information
Notification
Service
Provide
Portfolio
updates
Profiling
Engine
Context
Storing &
Recall
Authenticati
on
Dialogue
Management
Intent
Mapping
Content
Management
XX
G
P
A
I can’t find the
information I’m
looking for
I need some
information/stats/
data to help me
make decision
FAQ Content
Register
Interest
Generic chat
Conversatio
n
Create
investing
profile
Provide
Recommend
ation
Explain
decisions
Payment
Setting
View Chat
History
Geo Analysis
Behaviour
Monitoring
Client
identification
(non-secure
site)
I need instructions I want to ask
I have questions
for how to do things questions about
related to my
service information portfolio that I want
I I eg. fees
I answers to I
I want to talk about I need an
I need someone to I need guidance to
specific news/events explanation for this assure that I’m doing make decisions
in order to get more term
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insights I I
G G
I need explanation I want to discuss
I need technical help
for what I’m reading about specific news/
events related to my
G G portfolio G P
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changes to my
account details
P A A A
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Response
Generation
Customer
Profile
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Marketing
Content
Export chat
history
Share news/
insights:
internal
Goal
Suggestion
Provide
Forecast
Top up/
Withdraw
What-if
scenarios
Update
Profile
Local
language
integration
(NLG)
Help Desk
Augmentatio
n
Service
Information
Terminology
explanation
Share news/
insights:
external
Goal Setting
Account
Opening
Process
Provide
Transaction
History
Provide
Report
G
A
Account
Management
Help Desk
Integration
Sentiment
analysis
Anomaly
Detection
Get guidance
Complete action
People Like
you Analysis
Tool Tips
(how-to’s)
Voice
Command
Goal Editing
Portfolio
Information
Notification
Service
Provide
Portfolio
updates
Profiling
Engine
Context
Storing &
Recall
Authenticati
on
I can’t find the
information I’m
looking for
I
P
FAQ Content
Register
Interest
Generic chat
Conversatio
n
Create
investing
profile
Provide
Recommend
ation
Explain
decisions
Payment
Setting
View Chat
History
Geo Analysis
Behaviour
Monitoring
Client
identification
(non-secure
site)
I need instructions I want to ask
I have questions
for how to do things questions about
related to my
service information portfolio that I want
I I eg. fees
I answers to I
I want to talk about I need an
I need someone to I need guidance to
specific news/events explanation for this assure that I’m doing make decisions
in order to get more term
the right thing
insights I I
G G
I need some
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data to help me
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for what I’m reading about specific news/
events related to my
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changes to my
account details
P A
A A
Seek information
Report problems/complaints/Feedback
Marketing
Content
Export chat
history
Share news/
insights:
internal
Goal
Suggestion
Provide
Forecast
Top up/
Withdraw
What-if
scenarios
Update
Profile
Local
language
integration
(NLG)
Help Desk
Augmentatio
n
Service
Information
Terminology
explanation
Share news/
insights:
external
Goal Setting
Account
Opening
Process
Provide
Transaction
History
Provide
Report
Account
Management
Help Desk
Integration
Sentiment
analysis
Anomaly
Detection
G
A
Get guidance
Complete action
People Like
you Analysis
Tool Tips
(how-to’s)
Voice
Command
Goal Editing
Portfolio
Information
Notification
Service
Provide
Portfolio
updates
Profiling
Engine
Context
Storing &
Recall
Authenticati
on
I can’t find the
information I’m
looking for
I need some
information/stats/
data to help me
make decision
FAQ Content
Register
Interest
Generic chat
Conversatio
n
Create
investing
profile
Provide
Recommend
ation
Explain
decisions
Payment
Setting
View Chat
History
Geo Analysis
Behaviour
Monitoring
Client
identification
(non-secure
site)
I need instructions I want to ask
I have questions
for how to do things questions about
related to my
service information portfolio that I want
I I eg. fees
I answers to I
I want to talk about I need an
I need someone to I need guidance to
specific news/events explanation for this assure that I’m doing make decisions
in order to get more term
the right thing
insights I I
G G
I need explanation I want to discuss
I need technical help
for what I’m reading about specific news/
events related to my
G G portfolio G P
I need to provide
I want to complete I need to make a
I want to make
feedback or complain this step via chatbot transaction
changes to my
account details
P A
A A
I
P
Seek information
Report problems/complaints/Feedback
Marketing
Content
Export chat
history
Share news/
insights:
internal
Goal
Suggestion
Provide
Forecast
Top up/
Withdraw
What-if
scenarios
Update
Profile
Local
language
integration
(NLG)
Help Desk
Augmentatio
n
Service
Information
Terminology
explanation
Share news/
insights:
external
Goal Setting
Account
Opening
Process
Provide
Transaction
History
Provide
Report
Account
Management
Help Desk
Integration
Sentiment
analysis
Anomaly
Detection
G
A
Get guidance
Complete action
People Like
you Analysis
Tool Tips
(how-to’s)
Voice
Command
Goal Editing
Portfolio
Information
Notification
Service
Provide
Portfolio
updates
Profiling
Engine
Context
Storing &
Recall
Authenticati
on
I can’t find the
information I’m
looking for
FAQ Content
Register
Interest
Generic chat
Conversatio
n
Create
investing
profile
Provide
Recommend
ation
Explain
decisions
Payment
Setting
View Chat
History
Geo Analysis
Behaviour
Monitoring
Client
identification
(non-secure
site)
I need instructions I want to ask
I have questions
for how to do things questions about
related to my
service information portfolio that I want
I I eg. fees
I answers to I
I want to talk about I need an
I need someone to I need guidance to
specific news/events explanation for this assure that I’m doing make decisions
in order to get more term
the right thing
insights I I
G G
I need to provide
I want to complete I need to make a
I want to make
feedback or complain this step via chatbot transaction
changes to my
account details
P A
A A
I
P
Seek information
I need explanation
for what I’m reading
Report problems/complaints/Feedback
Marketing
Content
Export chat
history
Share news/
insights:
internal
Goal
Suggestion
Provide
Forecast
Top up/
Withdraw
What-if
scenarios
Update
Profile
Local
language
integration
(NLG)
Help Desk
Augmentatio
n
G
I want to discuss
about specific news/
events related to my
portfolio G
Service
Information
Terminology
explanation
Share news/
insights:
external
Goal Setting
Account
Opening
Process
Provide
Transaction
History
Provide
Report
Account
Management
Help Desk
Integration
Sentiment
analysis
Anomaly
Detection
G
A
I need technical help
Get guidance
Complete action
People Like
you Analysis
Tool Tips
(how-to’s)
Voice
Command
Goal Editing
Portfolio
Information
Notification
Service
Provide
Portfolio
updates
Profiling
Engine
Context
Storing &
Recall
Authenticati
on
P
I can’t find the
information I’m
looking for
I
P
FAQ Content
Register
Interest
Generic chat
Conversatio
n
Create
investing
profile
Provide
Recommend
ation
Explain
decisions
Payment
Setting
View Chat
History
Geo Analysis
Behaviour
Monitoring
Client
identification
(non-secure
site)
I need instructions I want to ask
I have questions
for how to do things questions about
related to my
service information portfolio that I want
I I eg. fees
I answers to I
I want to talk about I need an
I need someone to I need guidance to
specific news/events explanation for this assure that I’m doing make decisions
in order to get more term
the right thing
insights I I
G G
I need some
information/stats/
data to help me
make decision
I need explanation I want to discuss
I need technical help
for what I’m reading about specific news/
events related to my
G G portfolio G P
I need to provide
I want to complete I need to make a
I want to make
feedback or complain this step via chatbot transaction
changes to my
account details
P A A A
Seek information
Report problems/complaints/Feedback
Marketing
Content
Export chat
history
Share news/
insights:
internal
Goal
Suggestion
Provide
Forecast
Top up/
Withdraw
What-if
scenarios
Update
Profile
Local
language
integration
(NLG)
Help Desk
Augmentatio
n
Service
Information
Terminology
explanation
Share news/
insights:
external
Goal Setting
Account
Opening
Process
Provide
Transaction
History
Provide
Report
Account
Management
Help Desk
Integration
Sentiment
analysis
Anomaly
Detection
G
A
Get guidance
Complete action
People Like
you Analysis
Tool Tips
(how-to’s)
Voice
Command
Goal Editing
Portfolio
Information
Notification
Service
Provide
Portfolio
updates
Profiling
Engine
Context
Storing &
Recall
Authenticati
on
I can’t find the
information I’m
looking for
I need some
information/stats/
data to help me
make decision
FAQ Content
Register
Interest
Generic chat
Conversatio
n
Create
investing
profile
Provide
Recommend
ation
Explain
decisions
Payment
Setting
View Chat
History
Geo Analysis
Behaviour
Monitoring
Client
identification
(non-secure
site)
I need instructions I want to ask
I have questions
for how to do things questions about
related to my
service information portfolio that I want
I I eg. fees
I answers to I
I want to talk about I need an
I need someone to I need guidance to
specific news/events explanation for this assure that I’m doing make decisions
in order to get more term
the right thing
insights I I
G G
I need explanation I want to discuss
I need technical help
for what I’m reading about specific news/
events related to my
G G portfolio G P
I need to provide
I want to complete I need to make a
I want to make
feedback or complain this step via chatbot transaction
changes to my
account details
P A A A
I
P
Seek information
Report problems/complaints/Feedback
Marketing
Content
Export chat
history
Share news/
insights:
internal
Goal
Suggestion
Provide
Forecast
Top up/
Withdraw
What-if
scenarios
Update
Profile
Local
language
integration
(NLG)
Help Desk
Augmentatio
n
Service
Information
Terminology
explanation
Share news/
insights:
external
Goal Setting
Account
Opening
Process
Provide
Transaction
History
Provide
Report
Account
Management
Help Desk
Integration
Sentiment
analysis
Anomaly
Detection
G
A
Get guidance
Complete action
People Like
you Analysis
Tool Tips
(how-to’s)
Voice
Command
Goal Editing
Portfolio
Information
Notification
Service
Provide
Portfolio
updates
Profiling
Engine
Context
Storing &
Recall
Authenticati
on
I can’t find the
information I’m
looking for
I need some
information/stats/
data to help me
make decision
FAQ Content
Register
Interest
Generic chat
Conversatio
n
Create
investing
profile
Provide
Recommend
ation
Explain
decisions
Payment
Setting
View Chat
History
Geo Analysis
Behaviour
Monitoring
Client
identification
(non-secure
site)
I need instructions I want to ask
I have questions
for how to do things questions about
related to my
service information portfolio that I want
I I eg. fees
I answers to I
I want to talk about I need an
I need someone to I need guidance to
specific news/events explanation for this assure that I’m doing make decisions
in order to get more term
the right thing
insights I I
G G
I need explanation I want to discuss
I need technical help
for what I’m reading about specific news/
events related to my
G G portfolio G P
I need to provide
I want to complete I need to make a
I want to make
feedback or complain this step via chatbot transaction
changes to my
account details
P A A A
I
P
Seek information
Report problems/complaints/Feedback
Marketing
Content
Export chat
history
Share news/
insights:
internal
Goal
Suggestion
Provide
Forecast
Top up/
Withdraw
What-if
scenarios
Update
Profile
Local
language
integration
(NLG)
Help Desk
Augmentatio
n
Service
Information
Terminology
explanation
Share news/
insights:
external
Goal Setting
Account
Opening
Process
Provide
Transaction
History
Provide
Report
Account
Management
Help Desk
Integration
Sentiment
analysis
Anomaly
Detection
G
A
Get guidance
Complete action
People Like
you Analysis
Tool Tips
(how-to’s)
Voice
Command
Goal Editing
Portfolio
Information
Notification
Service
Provide
Portfolio
updates
Profiling
Engine
Context
Storing &
Recall
Authenticati
on
I can’t find the
information I’m
looking for
I need some
information/stats/
data to help me
make decision
FAQ Content
Register
Interest
Generic chat
Conversatio
n
Create
investing
profile
Provide
Recommend
ation
Explain
decisions
Payment
Setting
View Chat
History
Geo Analysis
Behaviour
Monitoring
Client
identification
(non-secure
site)
I need instructions I want to ask
I have questions
for how to do things questions about
related to my
service information portfolio that I want
I I eg. fees
I answers to I
I want to talk about I need an
I need someone to I need guidance to
specific news/events explanation for this assure that I’m doing make decisions
in order to get more term
the right thing
insights I I
G G
I need explanation I want to discuss
I need technical help
for what I’m reading about specific news/
events related to my
G G portfolio G P
I need to provide
I want to complete I need to make a
I want to make
feedback or complain this step via chatbot transaction
changes to my
account details
P A A A
I
P
Seek information
Report problems/complaints/Feedback
Marketing
Content
Export chat
history
Share news/
insights:
internal
Goal
Suggestion
Provide
Forecast
Top up/
Withdraw
What-if
scenarios
Update
Profile
Local
language
integration
(NLG)
Help Desk
Augmentatio
n
Service
Information
Terminology
explanation
Share news/
insights:
external
Goal Setting
Account
Opening
Process
Provide
Transaction
History
Provide
Report
Account
Management
Help Desk
Integration
Sentiment
analysis
Anomaly
Detection
G
A
Get guidance
Complete action
People Like
you Analysis
Tool Tips
(how-to’s)
Voice
Command
Goal Editing
Portfolio
Information
Notification
Service
Provide
Portfolio
updates
Profiling
Engine
Context
Storing &
Recall
Authenticati
on
I can’t find the
information I’m
looking for
I need some
information/stats/
data to help me
make decision
FAQ Content
Register
Interest
Generic chat
Conversatio
n
Create
investing
profile
Provide
Recommend
ation
Explain
decisions
Payment
Setting
View Chat
History
Geo Analysis
Behaviour
Monitoring
Client
identification
(non-secure
site)
I need instructions I want to ask
I have questions
for how to do things questions about
related to my
service information portfolio that I want
I I eg. fees
I answers to I
I want to talk about I need an
I need someone to I need guidance to
specific news/events explanation for this assure that I’m doing make decisions
in order to get more term
the right thing
insights I I G G
I need explanation I want to discuss
I need technical help
for what I’m reading about specific news/
events related to my
G G portfolio G P
I need to provide
I want to complete I need to make a
I want to make
feedback or complain this step via chatbot transaction
changes to my
account details
P A A A
I
P
Seek information
Report problems/complaints/Feedback
Marketing
Content
Export chat
history
Share news/
insights:
internal
Goal
Suggestion
Provide
Forecast
Top up/
Withdraw
What-if
scenarios
Update
Profile
Local
language
integration
(NLG)
Help Desk
Augmentatio
n
Service
Information
Terminology
explanation
Share news/
insights:
external
Goal Setting
Account
Opening
Process
Provide
Transaction
History
Provide
Report
Account
Management
Help Desk
Integration
Sentiment
analysis
Anomaly
Detection
G
A
Get guidance
Complete action
People Like
you Analysis
Tool Tips
(how-to’s)
Voice
Command
Goal Editing
Portfolio
Information
Notification
Service
Provide
Portfolio
updates
Profiling
Engine
Context
Storing &
Recall
Authenticati
on
I can’t find the
information I’m
looking for
I need some
information/stats/
data to help me
make decision
FAQ Content
Register
Interest
Generic chat
Conversatio
n
Create
investing
profile
Provide
Recommend
ation
Explain
decisions
Payment
Setting
View Chat
History
Geo Analysis
Behaviour
Monitoring
Client
identification
(non-secure
site)
I need instructions I want to ask
I have questions
for how to do things questions about
related to my
service information portfolio that I want
I I eg. fees
I answers to I
I want to talk about I need an
I need someone to I need guidance to
specific news/events explanation for this assure that I’m doing make decisions
in order to get more term
the right thing
insights I I
G G
I need explanation I want to discuss
I need technical help
for what I’m reading about specific news/
events related to my
G G portfolio G P
I need to provide
I want to complete I need to make a
I want to make
feedback or complain this step via chatbot transaction
changes to my
account details
P A A A
Bots for Customer Support Agent Bots for Customer Support Agent Bots for Customer Support Agent Bots for Customer Support Agent Bots for Customer Support Agent
Bots for Customer Support Agent Bots for Customer Support Agent Bots for Customer Support Agent Bots for Customer Support Agent Bots for Customer Support Agent
Response
Enrichment
Risk Profile
XX
Natural Language
Understanding
Digital
Passport
User Details
XX
Dialogue
Management
Intent
Mapping
Content
Management
XX
Conversation
Response
Generation
Customer
Profile
XX
Response
Enrichment
Risk Profile
XX
Natural Language
Understanding
Digital
Passport
User Details
XX
Dialogue
Management
Intent
Mapping
Content
Management
XX
Conversation
Response
Generation
Customer
Profile
XX
Response
Enrichment
Risk Profile
XX
Natural Language
Understanding
Digital
Passport
User Details
XX
Dialogue
Management
Intent
Mapping
Content
Management
XX
I need some
information/stats/
data to help me
make decision
Conversation
Response
Generation
Customer
Profile
XX
G
Response
Enrichment
Risk Profile
XX
Natural Language
Understanding
Digital
Passport
User Details
XX
Dialogue
Management
Intent
Mapping
Content
Management
XX
Conversation
Response
Generation
Customer
Profile
XX
Response
Enrichment
Risk Profile
XX
Natural Language
Understanding
Digital
Passport
User Details
XX
Dialogue
Management
Intent
Mapping
Content
Management
XX
Conversation
Response
Generation
Customer
Profile
XX
Response
Enrichment
Risk Profile
XX
Natural Language
Understanding
Digital
Passport
User Details
XX
Dialogue
Management
Intent
Mapping
Content
Management
XX
Conversation
Response
Generation
Customer
Profile
XX
Response
Enrichment
Risk Profile
XX
Natural Language
Understanding
Digital
Passport
User Details
XX
Dialogue
Management
Intent
Mapping
Content
Management
XX
Conversation
Response
Generation
Customer
Profile
XX
Response
Enrichment
Risk Profile
XX
Natural Language
Understanding
Digital
Passport
User Details
XX
Dialogue
Management
Intent
Mapping
Content
Management
XX
Conversation
Response
Generation
Customer
Profile
XX
Response
Enrichment
Risk Profile
XX
Natural Language
Understanding
Digital
Passport
User Details
XX
Dialogue
Management
Intent
Mapping
Content
Management
XX
I
P
Response
Customer
Profile
Seek information
Report problems/complaints/Feedback
Marketing
Content
Export chat
history
Share news/
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Local
language
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(NLG)
Help Desk
Augmentatio
n
Multichannel
compatibility
Multichannel
compatibility
Multichannel
compatibility
Multichannel
compatibility
Multichannel
compatibility
Multichannel
compatibility
Multichannel
compatibility
Multichannel
compatibility
Multichannel
compatibility
Multichannel
compatibility
Multichannel
compatibility
Response
Service
Information
Terminology
explanation
Share news/
insights:
external
Goal Setting
Account
Opening
Process
Provide
Transaction
History
Provide
Report
Account
Management
Help Desk
Integration
Sentiment
analysis
Anomaly
Detection
Digital
Passport
G
A
Get guidance
Complete action
People Like
you Analysis
Tool Tips
(how-to’s)
Voice
Command
Goal Editing
Portfolio
Information
Notification
Service
Provide
Portfolio
updates
Profiling
Engine
Context
Storing &
Recall
Authenticati
on
Intent
Mapping
Chatbot Service Blueprint
After developing a deep understanding of users’ needs and desires for chatbot, we developed our Chatbot Service Blueprint to illustrate what an
intelligent chatbot service could look like across our Global Wealth customer journey. This Blueprint brings together the customer journey and
customer needs with the underlying use cases, technical capabilities and data captured/required. This also defines how the chat service will be
delivered.
Engage & Guidance Digital Advice Invest & In-Life (DFM)
ENGAGE
A. DEFINE GOAL B. CHOOSE & CONFIRM GOAL C. USER PROFILING D. PROVIDE ADVICE E. REVIEW ADVICE & CONFIRM F. ADD MONEY G. VIEW GOALS & PORTFOLIO H. GET INSIGHTS I. GOAL EDITING J. TOP UP & WITHDRAW
DATA
COGNITIVE PLATFORM
BACK-END CABALITIES
CHANNEL CHATBOT FUNCTIONAL CABALITIES CAPABILITIES
CHATBOT USE CASES
Conversation Natural Language Dialogue
Understanding Management
Generation
Enrichment
Risk Profile User Details Content
Management
XX XX XX
XX
More details of underlying technical capabilities and data in the Technical Research section (p.40)
17

DETAILED FINDINGS:
MARKET RESEARCH
18

MARKET RESEARCH
Global perception of Chatbot
Chat bots are gaining popularity globally. A 2017 survey by
Liveperson 2 , which surveyed over 5,000 participants across 6 countries,
found 38% of consumers globally already rated their overall
perception of chatbots as positive, despite the technology as relatively
new. Only 11% of those surveyed globally reported a negative
perception of chatbots, while the remaining 51% took neutral stances.
However, it is interesting to note that over half of consumers in Japan
and Germany would prefer to speak with a bot than a human (Table
2).
Table 2: Communication method preference
While overall sentiment toward chatbots outweighed the negative
(Table 1), the majority of consumers still prefer human assistance. 56%
of global consumers still prefer speaking with humans, with 60%
believing that a human would better understand their needs than a
chatbot would 3 .
Table 1: Sentiment toward chatbots
The usage of chatbots continues to gain momentum. Of consumers
who have interacted with bots during the past year, 67% used them for
customer support while 30% chatted for fun and 25% for purchases
(Table 3). In regard to customer support, globally, most consumers
(52%) would not be open to waiting more than 2 minutes to chat with
19

customer care agents, considering that to be a sub-par experience.
That said: consumers in Japan and Germany appear to be the most
patient, 25% of respondents from both countries would be willing to
wait 3 minutes and still rate the customer service as excellent.
Interestingly, 25% of UK respondents would wait more than 5 minutes.
Table 3: Bot with name & personality
apt opportunity to harness the strength of both bot and human
channels, use the bot first: 67% want to be transferred directly to a
human when the bot does not understand what they need. 26% are
more forgiving and would be prepared to reword or try their requests
again.
Research highlights that bots with personalities are generally
preferred (Table 4). Many customers, especially in the US, don’t care
about personality, however more than 40% of German and Japanese
consumers believe in giving bots names and personalities. Friendly
bots are generally preferred over formal bots except in Japan, where
a formal personality rules the consensus.
In terms of chatbot implementation, 92% of businesses want to build
chatbot on Facebook Messenger, while 80% want to house their
chatbots on their own company website, followed by Slack and Twitter
respectively, according to another Chatbot Survey by Chatbots
Journal 4 . One of the biggest statistics comes from Facebook, in just a
year, Facebook Messenger has significantly grown to enable more
than 100,000 developers who have made around 100,000 bots.
According to Venturebeat survey, Facebook Messenger now has more
than 11,000 chatbots have been created for users to try. 5
It is expected that chatbot adoption will drastically pick up and
become more intelligent in 2017.
The survey suggests that human support agent is still essential for
businesses that integrate chatbots into their services. This identifies an
20

Table 4: Type of bot personality
Source: LivePerson Survey 2017, surveying 5,000 consumers from France, Germany, Australia, Japan, US, and UK 6
21

Other key figures on global perspective
Source: Chatbot Survey 2017 by Chatbot Journals, surveying 300+ organisations 7
22

UK perception of Chatbot
A recent study conducted by Morar Consulting 8 surveying 2,000 UK
consumers to better understand their attitude towards the rising growth
in chatbots suggests that chatbots are gaining popularity in UK and
consumers are willing to talk to businesses via new channels and
technology. This perception is aligned with the global perspective. This
means that it is a great opportunity for UK businesses to start adopting
chatbot technology.
The majority of British consumers (68%) state that reaching a desired
outcome is the most important thing when communicating with
a brand, followed by ease of experience, speed, availability,
friendliness, and personalisation (Table 6).
Table 6: The most important thing in communicating with a brand
In UK, three-quarters (75%) of consumers have not yet spoken to a
chatbot. The majority of consumers are aware of what a chatbot is
(57%) and over a third (35%) want to see more companies using
chatbots to answer their questions (Table 5).
Table 5: Chatbot adoption
Even though the global study found that most of consumers still prefers
to speak with a human instead of a chatbot. UK study found it is
interesting to see the reasons why consumers would be more courage
to engage with a chatbot. Nearly 70% believe that they will get instant
answers to their questions via chatbot and over 21% see a chatbot as
the easiest way to contact a business (Table 7).
23

Table 7: Reasons of using chatbot
Table 8: Negative chatbot experience
43% of UK consumers perceive companies that offer a chatbot as
innovative while 35% perceive in negative way that they are less
personal in providing the service. In terms of utility, customers found
that those companies are helpful (30%) and efficient (22%)
Despite the majority of consumers having had positive experiences
with chatbots, 21% of UK consumers had a negative experience with
12% reporting that the chatbot didn’t respond with the right information
and 9% saying that the chatbot was clunky and difficult to use. The
research also uncovered a need for more education around how
consumers should engage with chatbots (Table 8). 40% of UK
consumers said that would not think to engage with a chatbot, or do
not know how to engage.
The research suggests that chatbots must make customer experience
efficient and reliable, but also delight customers. They will not only
deliver the excellent customer service needed, but they will offer a
novel experience that cannot be delivered by any other means of
digital contact. One way to achieve this is to embed a brand persona
into a chatbot which helps increase brand recall. By doing so, brands
can have personalised, two-way conversations in real time, at scale.
Consumer trust in chatbots will come when brands can deliver a good
experience. In 2017, people don’t expect to have in-depth, human-like
conversations with automated technology such as Alexa – they just
want to be able to get the information they need, quickly.
Looking forward, when consumers trust that brands can deliver the
experience they demand from chatbots, widespread adoption will
take hold. This expectation is aligned with findings from Juniper
research. 9 Juniper forecast that the success rate of bot interactions will
increase significantly in 5 years especially in healthcare and banking
sector. In the healthcare sector will move from 12% currently, to over
75% in 2022. In the banking sector, Juniper expects this to reach over
90% in the same year.
24

Other key figures on UK perspective
Table 9: Amount of money consumers willing to spend via a chatbot
Table 10: Top reasons to use a chatbot
Source: Chatbot Survey 2017 by Morar Consulting, 2,000 UK consumers 10
25

German perception of Chatbot
Based on the LivePerson survey 11 , consumers in Germany is considered
as the most openness to bots, as more than half would prefer to speak
with a bot over a human and believe that chatbots gives them faster
and better service.
Similar trend from a recent Bitkom Research 12 , surveying 1,005
consumers in Germany, even though 46% claim not to know what a
chatbot is, but every fourth citizen (25%) would be open to
communicate to one. 41% find chatbots attractive for use in customer
service to handle requests for orders and complaints. This indicates
that there is a split – those who are aware and those who are not. The
study also shows that the German markets trust bots to achieve simple
tasks - such as updating an address or querying an account. In a
world-wide comparison, the Germans are most sceptical about
chatbots when it comes to making payments 13 .
• 68 % want to use chatbots as personal scheduling assistant
• 64 % want to use it to reserve or buy event tickets
• 58 % want to use chatbots for online shopping, for example
when searching for specific products
• 58 % want to use travel bookings, flights, train travels or hotels
• 53 % want to access daily information such as the weather,
news, traffic situation or stock market values
• 41 % find chatbots attractive for customer service calls to ask
for orders and complaints
• 23 % find it interesting to use chatbots in connection with
delivery services, for example, to order food or flowers by
voice command
26

According to a study conducted by Fittkau & Maaß Consulting among
1,200 German Internet users 14 , one third of the interviewees believe in
the potential of chatbots: in their opinion, these are currently still undeveloped,
but they will develop rapidly and then unfold their full
potential.
YouGov, a global market research and analytics firm, survey 15
suggests that companies should not be afraid to explore and
implement chatbot technology - customers will appreciate the
advantages including personalised communication that tailors to their
individual needs, and a more personal identity that brands can be
achieved through a chatbot.
Referring to the LivePerson survey 16 , consumers prefer chatbot to have
a name and personality. In Germany, 58% of respondents select
friendly bots as their top choice. 11% says they prefer bots to rather be
formal and another 11% says they prefer humorous chatbots. A
personality gives consumers an experience that’s most similar to
interacting with a real person, whether it’s through an online shopping
experience, a weather forecast, a customer service helpdesk
conversation, a virtual assistant, or other transactions. A chatbot’s
personality provides consumers with the most pleasurable experience
possible so that they remember the brand and look forward to using a
particular product or services again and again 17 .
In terms of chatbot landscape in Germany, based on available data
from Chatbots.org, the world’s fastest growing community on humanlike
conversational AI, there are 61 chatbots including virtual
assistants, chat bot, conversational agents, virtual agents in
Germany. 18 48 out of 61 (80%) chatbots are using Web as a platform
while only 8 (13%) chatbots are using Facebook Messenger.
27

Competitor Analysis
The broad appeal of chatbots stems from the efficacy and ease of
interaction that they facilitate across the customer experience. As AI
capabilities continue to emerge across industries, and the wider public
becomes accustomed to chatbots and AI assistants, customer
expectations will increase regardless of whether or not financial
services has caught up to speed. Consequently, companies that fail to
address AI’s development within their industries will likely suffer the
consequences of seeing their competitive advantages reduced.
A quick scan of the competitor’s landscape indicates that the financial
services industry is still in early stages when it comes to chatbot
adoption. Within wealth management particularly, chatbots are still in
infancy, with no major competitors having rolled out any sophisticated
tools thus far. The biggest developments are happening within the
Banking sphere, with the integration of bots such as erica (BoAML)
and Luvo (RBS, Natwest) into the their websites and/or apps to answer
customer questions and perform simple banking tasks, e.g. money
transfers, within smart Whatsapp-like conversations.
We have also noticed regional difference in bot approaches: in the
US, the trend has been to ‘unbundle’ apps into separate, use case
specific bots (e.g. Facebook’s separation of Messenger into its own
platform, with a chat-based personal assistant and tie-ins to third party
apps) 19 .
Meanwhile in China, the trend is very much the opposite, as exampled
by the likes of dominant social network, WeChat.
When looking at ‘best of breed’ qualities, discoverability, shortcuts and
proactivity are integral to good conversational interfaces. Whilst a NLP
engine should be able to understand everything a user is saying, new
users also need to understand the scope of what they can ask, which
can be achieved by utilising autocomplete tools and menus, among
other things. Likewise, proactive behaviour underlies the most
intelligent bots. That is, when bots can take initiative to instigate
conversation - e.g. providing portfolio updates, or delivering time
sensitive notifications 20 .
Additionally, research shows that the best bots are those that provide
users with a sense of control over the conversation. This can be done
through ‘stop gaps’ that allow the user to confirm or cancel certain
processes, giving the impression of control.
From a conversational perspective, there are nonetheless still gaps in
natural language capabilities amongst financial services bots and
beyond.
It is thus important to look beyond financial services when seeking
inspiration and ‘best practice’ analysis of the competitive landscape.
We split up our research into 4 different guiding topics: form filling,
content delivery, conversational skills, and financial services based.
28

1. Chatbot that help with Form Filling:
Hello.Vote
• What: Voter registration in 2 minutes
• Like: Targets people more likely to engage via smartphone than
respond to a mass mailing campaign
SPIXII
• What: Insurance
• Like: Designed to enhance customer experience by replacing form
filling
• Regulated by the FCA and can speak all existing languages
29

Habito
• What: AI mortgage advisor
• Queries an applicant’s financial status, personal life, employment
info
• Like: After a 10-15m ‘chat’, the bot collates the data given and
queries hundreds of products
• Produces recommendations in a fraction of the time that a human
advisor would need
30

2. Chatbots that Deliver Content:
IBM DeveloperWorks News Bot
• What: Delivering news
• Like: Specify topics of interest, drill further into topics
• Chatbot also supports searching for other / relevant articles using
Google-like queries
CNN News
• What: News delivery
• Like: ‘Get a Summary’ button on each story card - tapping this
gives a short summary of the article, within your conversation feed
• Available across messaging apps like Kik, LINE, and Facebook
Messenger as well as voice-activated devices like Amazon Echo.
31

Complex
• What: News delivery
• Like: Good use of space via a menu that highlights a list of the
most useful bot commands a user might not have been aware of
Marriott Hotel: ChatBotlr and Marriott Rewards Chatbots
• What: ChatBotlr, available via text message, gives guests a new
way of making service requests
• Like: Order room service, set up wake up calls, get information
about the hotel, listen to the music, and connect with the front desk
- even when they’re not on-property.
• What: Marriott Rewards 21 serves loyalty members before, during,
and between stays
• Like: Members can research/book over 4,700 hotels, link Rewards
accounts, and plan for upcoming trips using articles from the
Marriott’s digital magazine.
• They can also chat directly with customer engagement associates.
• Available on Facebook Messenger, Slack, WeChat, Google
Assistant.
32

3. Chatbots with Good Conversational Skills:
woebot
• What: 24/7 therapist
• Like: Personality exists behind the bot: fun, casual, friendly
• A combination of natural language processing, therapeutic
expertise, personalized content, and a sense of humour all exist to
“create the experience of a therapeutic conversation for everyone
who uses him” 22
Taco Bell
• What: Food ordering/delivery
• Like: conversational language and tone; personality; helpful
guidance: e.g. ‘the most popular add-on’s are…’; learning element
that incorporates ‘Tips’ that teach the user how to maximize the
bot
Alibaba
• Among other features, this bot is able to respond to questions with
images, e.g. product photos and emojis, to add depth to its
answers
• It can even make customer-specific recommendations for shoe and
clothing sizes, and answer technical questions about consumer
electronics (e.g. the data-storage capacity for a smartphone
model)
33

4. Chatbots in Financial Services
erica, Bank of America Merrill Lynch
• What: make payments; check balances; save money; pay down
debt; look at educational videos; etc.
• Like: Lots of work went into teaching erica to learn conversational
nuances and conversational contexts
• Bot is also being trained to find insights for customers and make
recommendations: e.g. if a customer’s FICO score dropped, for
instance, erica might suggest better money habits, drawing on a
partnership with Khan Academy, a provider of educational tools.
The chatbot may identify ways the customers could save more or
pay down debt. erica could help customers avoid mistakes like
missing a mortgage payment.
• Next steps: BoAML is looking at integrating the technology with
mainstream virtual assistants like Alexa and Siri. Working proof of
concepts already exist 23
Wells Fargo
• What: account balance reporting; finding closest branches;
providing spending breakdown; launched May 2017
• Next steps: the bot is powered by machine learning, i.e. an
engine that learns over time, so eventually its keyword responses
will be replaced by full conversation. Once the bot has mastered
the art of conversation, it will learn emotional comprehension 24
34

Chatbots Landscape 2017
35

DETAILED FINDINGS:
TECHNICAL RESEARCH
36

TECHNICAL RESEARCH
Introduction
The chatbot market place is currently flooded with a range of chatbot
solutions from novel implementations to enterprise grade. It is
predicted that by year 2020, 80% of all first-line user-business
interactions would be fielded by a chatbot. A chatbot enables the
human agent to concentrate on higher valued tasks like business
development, customer understanding, tailoring products/ services
and conversations per user, reduce organization costs, among many
benefits. This brings to the fore the key question – “How do I design
and implement an enterprise grade chatbot?” 25
There are three design principles which can be used for this as shown
in diagram below. And technology selection and implementation is the
3rd step in this process. Once the business has a good understanding
of why and if the users would want it, then comes the technology
question – which platform to use, what NLP engine to implement, how
to design conversations, etc?
Recognizing the market trend, all of the technology giants have
already made their foray into this area, either for improvement of their
own products/ services or as a commercial offering for other
organizations to implement on their own. Google integrated API.ai into
their cloud offering and has been acquiring additional businesses to
bolster their offering. Microsoft built Language Understanding
Intelligent Services (LUIS) which can plugin into any dialog manager
as well as their own BOT framework. Facebook has recently acquired
wit.ai to enhance their products. IBM has built the most popular
enterprise chatbot infrastructure as part of their Watson conversation
engine 26 (Table 11).
37

Table 11: AI Vendor Assessment
38

Sample Architecture
The existing technology providers are rapidly addressing organization needs and security requirements in terms of re-usability of conversations for
community model training, PII, etc. In any chatbot infrastructure or technology stack, there are certain core components of an enterprise grade
chatbot architecture. They are listed below and these are incorporated into the available offerings in varying degrees of flexibility and stability.
At a very high level, as described in a best practice article for building bots, the general areas of a chat bot are as follows.
The figure below shows a sample architecture that is built with a vendor agnostic view of the chatbot solution. The exact architecture will be designed
in the next phase, but the figure below is a step in that direction. The technologies and vendors will be finalised in the design phase. GDW would be
integrating into this architecture via API calls to the CRM systems and any user related data warehouses. One of data content providers would be the
CMS system, providing curated content from FIL. There is no specific data technologies in use, especially for the Engage phase, but once the scope of
the phase is finalized, the exact data technology requirements will be finalised as well.
39

Generative vs. Retrieval Based Chatbot Models
There are broadly two types of chatbots, as defined by the way they
respond to user interactions 27 :
Generative models are difficult and complex to build as they rely on
the model to learn automatically from the conversations, but are also
prone to learning abusive, unconventional and un-curated content.
These models are still the lab phase.
Retrieval-based models are those seen implemented commercially as
they provide consistent responses using curated content and
conversations. They rely on the fact that there is a list of responses to
choose from and the model chooses the closest to right response from
the list. In effect, it retrieves a response instead of generating it. This
process of response retrieval can be made as bespoke and as
business rule friendly as possible. See diagram on the right such
version.
40

Implementation Options
Our research in chatbot technology stacks and implementations has identified the following breakdown of different components of an enterprise
chatbot implementation (see Appendix 1 for terminology):
Conversation Channel
Messaging
Service
Conversation Providers
Dialog Managers with
Convo. Design
Chatbot Analytics
External Content
Providers
• Facebook
• SF chat add-in
• SMS
• iMessage
• Slack, etc.
• Pubnub
• Twilio
• RabbitMQ,
etc.
• Detects presence of users
• Delivers content to the user via channel of choice
• Real time or otherwise
• Tree based
• Graph based
• Branded
• Unbranded – Built
bespoke
• News articles
• Reports
Internal Content
Providers
Analytics Engine Conversation Data Conversation Engine Data Storage
• News articles
• Fidelity product
Reports
• Fidelity curated
marketing material
• ML Knowledge Base
w/ Insights engine
• Customer profiler
• Product/ Service
recommendation
engine
• Sentiment analyser
• Emotion analyser
• NLP service (optional)
• Data
transformation
service
• Conversation
map
• NLP Engine: Interprets user entered text into machine readable and machine
interpretable content
• Rules/ Transformation engine: Business rules and logic is applied to the logic
• Intent service: Identifies the intention behind a conversation from a predefined
list of intents
• Entity service: Extracts conversation specific data-objects which are passed on
to other services as parameters
• Context service: Captures context and carries forward or relinquishes context
of a sub-section of a conversation, based on the conversation map
• Fulfilment engine: Defines the logical and (or) data end point of a
conversation that defines the end of context and intent
• Emotion service: Identifies the emotion of the user via the conversation text
• Sentiment service: Identifies the sentiment of the user via the conversation text
• User
• Conversations
• Contexts
• Conversational
metadata
• Session
Within Fidelity, there are several instances of a chatbot being implemented for specific purposes with varied degrees of success. One of the pivotal
pieces of work has been in the area of creating a template of an enterprise grade chatbot architecture from FMR. There have been other successful
chatbot implementations in HK, etc using ClaireAI (similar to traditional big players of API.ai or IBM Watson). These would be explored in further
detail in the next phase and a decision made and a solution designed in the next phases of Design and Build.
41

Chatbot Channel Functional Capabilities
FAQ Content
Marketing
Content
Service
Information
People Like
you Analysis
Register
Interest
Export chat
history
Terminology
explanation
Tool Tips
(how-to’s)
Generic chat
Conversatio
n
Share news/
insights:
internal
Share news/
insights:
external
Voice
Command
Create
investing
profile
Goal
Suggestion
Goal Setting
Goal Editing
Provide
Recommend
ation
Provide
Forecast
Account
Opening
Process
Portfolio
Information
Explain
decisions
Top up/
Withdraw
Provide
Transaction
History
Notification
Service
Payment
Setting
What-if
scenarios
Provide
Report
Provide
Portfolio
updates
View Chat
History
Update
Profile
Account
Management
(see Appendix 2 for terminology)
Back-end Capabilities
Cognitive Platform
Conversation
Natural Language
Understanding
Dialogue
Management
Response
Generation
Response
Enrichment
Digital
Passport
Intent
Mapping
42

Appendix 1: Technologies involved in chatbots - explanations
A chatbot offering might consist of a variety of technologies and services from different providers. The technologies involved can be categorised as
follows (Gartner, 2017):
• Messaging Platform: where the conversation between the human and machine occurs
• Speech to text: the engine used to convert speech to text – text is the most common implementation method, but not the only one
• Natural language processing: the engine that takes the textual input and maps it to a particular intent (with a confidence score). This is
usually done with machine learning algorithms
• Tree walker: The decision tree is used to take an intent and map to actions, responses, or follow up questions
• Knowledge repository: if not using a tree walker, the chatbot becomes more of a front-end to a search engine and it will convert input into a
query for a search engine. This might lead to a list of results or an attempt to summarise an answer based on the content of the repository
• Natural language generation: in some cases, linking to an article in a knowledge repository might be seen as only ‘glorified search’, but
attaching a step where the chatbot response is generated based on a summarization or refinement of the contents in the repository can be a
differentiator.
43

Appendix 2: Channel Functional Capabilities- explanations
44

45

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18
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20
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21
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22
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23
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24
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25
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26
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27
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47