Chatbots enabling efficiencies and improvements in financial services

1. Ness
Digital
Engineering
Bots in Financial Services
Chatbots – Enabling CX & Process Improvements
by Sanjay Bhakta
What’s my account balance?
What’s my spending
breakdown?
Would like to transfer money
from savings to checking

2. 2 © 2017 Ness Digital Engineering . All Rights Reserved
Executive Summary
Challenges
• Increasing operational expenses
• Customer satisfaction
• Customer retention
• Customer Experience (CX)
Chatbot
• Self-service “always on”
• Online, mobile, & social
• Actions: inquires, account balances,
spending breakdown, money transfer,
financial instruments pricing
information
Operational efficiencies
• Customer Care / Contact Centre
 Reduce wait & hold time
 Callbacks reduction
 Expedite resolution(s)
 Optimize customer inquiries
Personalization
• Concierge “like experience”
 Obtain account balance and breakdown of
spending by categories
 Transferring money between accounts
 Retrieving IPO information
 Acquire investment prices as market
fluctuates
Strategic Imperatives Approach

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Chatbot Landscape
Fundamentals
• Taxonomy
• Agent – trained application(s)
• Entity – concepts mapping natural language to canonical statement(s)
• Intent – user’s purpose of an operation to perform
• Action – step(s) executed based upon intent specified
• Context – condition(s) supporting intent
• Model types: Retrieval vs Generative
• Retrieval – uses rules (such as AIML) and / or machine learning to select a response from
a repository of predefined responses
• Generative – generates new responses based on machine translation techniques
• Today: production models are typically Retrieval and use NLP / NLU
• Challenges: context, long conversations, open domain (without clearly defined intent), & consistent
responses
Frameworks – Sampling
• API.ai, Bottr, ChatterBot,
ChatScript, LUIS.ai,
Microsoft Bot, Wit.ai
Platforms – Sampling
• Chatfuel, ChattyPeople,
Facebook Messenger, Telegram
nltk
Lancaster
Stemmer
numpy
tflearntensorflowrandom
json
pickle sys
namedtupleMetricSpecfunctools itertools
timeos
Python Dependencies

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Chatbot Construction
Steps to implement a Tensorflow Contextual Retrieval Model
1
Outline Intents
2
Establish corpora
4
Build Classifiers
5
Contextualize
state
3
Baseline Model
6
Define Evaluation
Metrics
7
Create Deep
Learning Model
8
Train Model
9
Test Model
10
Make Predictions

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Chatbot Conceptual Architecture (1 of 3)
Corpora
Corpus
(other)
Corpus
(contact
center)
Corpus
(social)
Corpus
(chat)
Customer
Journey
Map
Conver-
sational
training
Persona(s)
Exceptions
Manage-
ment
Personality
Customer
Analytical
Modeling
Utterances
& Intents
Routable to
human
VOC
Analysis
CX & UX
(Customer Experience & User Experience)
• Customer Satisfaction Modeling
1
Outline Intents
2
Establish corpora
• Define taxonomy
• Identify sources
• Curate
• Prescribe rules
• Transform / translate
• Tokenize

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Chatbot Conceptual Architecture (2 of 3)
Evaluation
Metrics
F-measureBLEU
NIST Recall@k
Probability
Distri-
butions
Training
Data
PositiveNegative
Corpora
Test
Data
Incorrect
Utterances
Correct
Utterance
Clustering
Algorithms
Corpora
Contextual
TF-IDF
5
Contextualize
state
3
Baseline Model
4
Build Classifiers
6
Define Evaluation
Metrics

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Chatbot Conceptual Architecture (3 of 3)
Others
Neural
Networks
seq2seqLSTM
7
Create Deep
Learning Model
9
Test Model
8
Train Model
10
Make Predictions
Actual
Predicted
Training,
Testing, &
Predicting
Response
Text
Embedded
Context
Entropy
Loss
function
Training
Data
Neural
Networks

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Summarization
• Chatbots may facilitate achieving strategic imperatives such as increasing operational efficiencies
and improving the customer experience with personalization
• Chatbot Best Practices:
• CX & UX assessment
• Establishing corpora
• Extensive training & testing data
• Continuous calibration using evaluation metrics
• Options constructing Chatbots
• Utilize existing frameworks
• Utilize existing platforms
• Develop neural network models for performance improvements
• Incorporate machine learning such as clustering to match pre-existing response corpora

9. Thank You
Drive New
Business Growth
Create a Connected
Customer Experience
Deliver Products to
Customers Faster
Experience Design as a
Competitive Advantage
Work with Ness in creating new
products and business models that
create sustainable growth.
Understand the journey of the
customer across all touch-points
with a customer centric approach to
product development.
Rationalize product innovation,
create tangible prototypes, user
test and get to market faster.
Raise the bar. Create enterprise
applications not just with modern
but cutting edge design and
functionality.
Sanjay Bhakta
Senior Director Solutions
sanjay.bhakta@ness.com