anticipatory banking · service differentiation, growing brand value and nps score 10 mm (total...
TRANSCRIPT
Anticipatory Banking:
Using AI to Create Advantage in a Digital World
9 October 2019
RASHED HAQ Global Head of AI, Robotics & Data
Transformation of Retail Banking
2
Historic differentiators for
attracting and retaining
customers is eroding
AI is enabling new ways to
create offerings
Customer
Loyalty
Open Banking and the
emergence of banking platforms,
FinTechs and distributed ledgers
is reducing switching costs and
exclusivity of relationships
Open Ecosystems
The transformation of the back
office will remove operational
efficiency and scale as a
competitive differentiator
Competitive basis is shifting
to the front office
Operations
Transformation
3
Value (WHY)
Customer Centric Model
4
Confidence in Bank LO HI
% o
f C
usto
me
rs A
gre
e B
ank is D
oin
g T
his
LO
H
I
Looks after my
financial well being
Helps me manage
my finances
Communicates openly and
about meaningful topics
Lets me bank
anytime, anywhere
Source: Gallup
Branch, mobile &
online satisfaction Shift from being in the
financial services business
to being in the
financial health business
6X customers say their
bank is the only
financial institution they
need
Anticipatory Banking Maturity
5
Thinking
Data in Silos
Isolated AI PoCs
No Algorithmic Strategy
Improving in Silos
Marketing
Online Banking
Customer Service
Branch Management
Wealth Advisory
Transforming
Organizes for Scale
Values Data as Strategic Asset
Uses Unified AI/Data Platform
Has Organized for Learning
Anticipate customer needs and personalize services at scale to each individual
through their specific journey to maximize customer financial health
6
Understand Customer
Things about them
How they will behave
What their needs are
Maximize Financial Health
Financial health score
Percent of customers
who levelled up
Optimize Spending
Make payments on time
Spend less than earnings
Manage Loans
Have strong credit score
Ensure debt is sustainable
Grow Savings
Have short term rainy-day fund
Grow long term savings
Business Value for the Bank
7
Bank Outcome Size Benchmark Rate Δ (N) Value / Y
Customer Acquisition: Increase account openings by N% due to brand and
service differentiation, growing brand value and NPS score 10 MM
(total customers) $300 2% $60 MM
Customer Attrition: Boost customer satisfaction and retention and
decrease customers attrition by 5% 1.5 MM
(15% of 10 MM)
$500
($200 acquisition
cost)
5% $38 MM
Products and Services: Increase cross-sales and customer lifetime value
with an increase in products per customer by N% (e.g. from 1.3 products
/customer to 1.5)
10 MM $100 5% $50 MM
Deposits: Larger bank deposit balance per customer by N% 10 MM $50 7% $35 MM
Delinquencies: Reduce delinquencies on loans and credit cards and
subsequent charge-offs by N% 100 K $350 20% $7 MM
Efficiency: Improved employee productivity, and drive employee
engagement and retention 10 K $75 K 8% $60 MM
$250 MM Annual Financial Benefit
Impact of
Anticipatory
Banking
Early Adopters Will Capture a Disproportionate Share of Cumulative Benefits
8 Source: McKinsey Global Institute
122%
23%
9
Use Cases (WHAT)
10
Anticipatory Banking Framework
Engage
Customer
Understand
Customer
Data &
Signals
Decide
Product
or Service
Bank Transactions
User Activity
(1st party)
External Information
(3rd Party)
Machine Learning
Deep Learning
Natural Language
Processing
Machine Learning
Deep Learning
Semantic Reasoning
Journey Orchestration
Digital Content
Direct Messaging
Use Case 1: Need for Increased Credit
• Customer injures ankle and needs additional
money to cover medical expenses
• She reads about injury on WebMD
• While reading an article on EPSN’s website, she
sees a bank ad offering new/increased credit limit
• Sustained low liquidity levels
within the checking account
• Customer makes several doctors
visits and co-pays with credit
card indicating an increase in
health related spending
• Increased activity on health
related web articles (WebMD,
etc.)
• Ad impressions from sports
websites
• Pays debts timely
• This is a bank user who is likely
dealing with an unexpected
health event
• Does not have liquidity to
manage an unexpected event
• Has low credit risk to date
• Offer new credit line
• Offer advice for making sound
credit related decisions
• Show digital ad through ESPN
INCREMENTAL INSIGHTS
• May need advice managing
credit
• Enjoys reading about sports
INCREMENTAL INSIGHTS
• Needs a savings plan
Engage
Customer
Understand
Customer
Data &
Signals
Decide
Product
or Service
Use Case 2: Need for Savings
• Customer earns a promotion to Senior Architect
and a significant pay increase
• Customer signs into online account to pay bills
• A masthead notification reminds her of prior unexpected
spending spike and suggests it’s a good time for an
emergency savings account.
• Increase in the frequency of a
higher direct deposit amount
• Sustained low liquidity levels
within the checking account
• Lack of secondary account
with funding
• Previous record of an injury
and unexpected financial event
• This is a bank user who had an
increase in her monthly income
• Does not have enough liquidity
to manage an unexpected event
• Offer advice to build an emergency
fund through a savings account
• Show masthead with
recommendation
INCREMENTAL INSIGHTS
• Customer is focused on career
• She is working in a company
that offers a path for career
improvement
INCREMENTAL INSIGHTS
• She is smart about savings
• She is interested in planning
for the future
Engage
Customer
Understand
Customer
Data &
Signals
Decide
Product
or Service
Use Case 3: Need for a Mortgage Loan
• Customer starts thinking
about purchasing a condo
• She begins looking at home buying sites
• She receives a personalized email from her bank that
includes tips on buying homes in his area, mortgage
calculator for how much she can afford, and how to
apply for pre-approval
• Increase in savings, and lower
spending, for a longer than
normal period
• Increase in frequency of logging
into bank’s online account
• Web activity showing increased
interest in real estate related
browsing, including searching for
Mortgages and comparing
• Increased visits across various
city neighborhoods, via location
graph from his device info
• This is a bank user who is actively
looking to purchase a home
• She is researching the financial
instrument available that can
facilitate a purchase
• Suppress credit related marketing
• Offer advice on buying a new home
and provide a link to a local branch and
the name of the Branch Manager
• Send email with
recommendations
INCREMENTAL INSIGHTS
• Comparison shopper
INCREMENTAL INSIGHTS
• Accessible during weekdays
Engage
Customer
Understand
Customer
Data &
Signals
Decide
Product
or Service
14
Enablers (HOW)
Key Enablers
15
Data
Aggregate sufficient data depth
and bread to get meaningful
behavioral signals
Include sufficient 3rd party data
AI Platform
Build the AI platforms and
processes to experiment and
deploy AI models at scale
Govern AI model risk for
fairness, transparency and
other policies at every step
Journey Orchestration
Map out customer journeys and
knowing where the insights will
be used and in what way
Integrate systems and
processes, with pre-approved
messaging, so activations can
be real time
Organization
Orient all employees towards
learning (create new
knowledge) through
experimentation
01 Collect a broad set of data
to create a digital twin of your
business
Media
• Using tracking resources (script,
pixel, image)latitude and longitude
• city, state, country and zip code
• unique ID or fingerprinting from
combination of: operating system,
browser information, screen size,
screen resolution, etc.
Users
• CRM, call center, social
Transactions
• Checking, savings, credit card,
investments
Branch
• Pixel-tracking users in store through
wi-fi Source: New York Times
By Farhad Manjoo, Nadieh Bremer
02 Connect critical pieces of data (e.g. customer graph) and keep lineage
17
Shared view
of customer Communications ID
Audience
Data Platform
Customer
Data Platform
Customer ID – Communication ID
Identity Linking with deterministic
and probabilistic match
DMP CDP
03 Use modern techniques in AI/ML
18
Moore’s Law
03 Use modern techniques in AI/ML e.g. embeddings and wide-and-deep models
19
Embedding are mappings from
discrete objects such as customers or
products (and their attributes), to multi-
dimensional vectors of real numbers
king
queen
female
male
(king + female – male) = queen
king
queen
female
male
Personalization is based on user and
product interactions using techniques
such as collaborative filtering. Extend to
journeys with embeddings.
✓ ✓
✓
✓ ✓
✓ ✓
✓
✓ ✓
Modern personalization uses wide and
deep AI models that bring
understanding of interactions (wide) and
characteristics of products (deep)
04 Leverage the power of multiple models to solve real use cases
20
Most retailers think of
personalization through the lens
of matching the best content to
customers, but different kinds of
content need to be modeled
separately
Actively communicating with
known customers requires
thinking about the entire journey
The same information used to
personalize one experience,
should be reused consistently
across other experiences
One use case could touch
several of these models
Product Recommendation
Personalized
Offers / Discounts
Personalized
Search Results
Best Product Creative
(Size, Color, Pattern)
Personalized
Non-Sales Content
(Loyalty, FAQs)
CONTENT EXPERIENCE CUSTOMER MOMENT
Point in Journey
Lead Scoring Model
Lifetime Value / Loyalty
Current Sentiment
DELIVERY EXPERIENCE
Best Channel Prediction
Next Best Action
Prediction
Returns Predication
Preferred Frequency
Prediction
Likely to Churn
04 But plan to deal
with multi-model scale
21
Predict
Life Event
Novel
Item
Desire
Genome User
Intent
Search Social Ad Imp Transactio
n
Brows
e Offer
Account
Activity
Call
Center
Recommend
Product in
App
Direct Send Recommended
Product
Direct Send
Offer
Improve
Operations
Predict Best
CoSelling
Products
(Xsell)
Propensit
y to Buy
Future
Purchase
s
Customer
Lifetime
Value
Best
Recommen-
dation
by Channel
Demand
Forecast
Best Offer
Type by
Channel
Best
Channel Best Offer
Type
Ideal
Price
Point
Best
Alternate
Product
(Upsell)
Call
Volume
Forecast
Call Intent Customer
Churn
Topic
Modeling
Discover
Churn
Reason
Item
Impulse
Desire
05 Build an enterprise AI & analytics platform to experiment fast and scale
22
Impact of
AI Platform
Approach
Regulatory &
Compliance
Pressures
Typical Bank Leading International Bank Digitally native company
No. o
f m
od
els
pe
r m
on
th p
er
pe
rso
n
No. of data scientists
Feature
Marketplace
Data collection and
readiness for
modeling
Model
Builder
Model creation,
refinement and
validation
Inference
Activator
Risk governance,
model deployment
and production
activation
Performance
Manager
Production
monitoring and
potential retraining
30X SCALE ● 5X SPEED ● 0.5X
COST
06 Orchestrate across relevant journeys rather than at single touchpoints
23
Customer Data Platform
CRM
Web Mobile Email Social Digital Ad Shipping
Inventory Call Center Content
Management
Ad
Impressions
Journey Orchestration
Transactions
Intelligence Journey Reports
07 Build model risk governance into each phase of the project lifecycle
24
Data Quality
Data Bias Detection
Protected Features
Model Reproducibility Fairness Testing
Model Interpretability Retraining Triggers
Model Regularization
for Bias
Boundary Conditions &
Sensitivity Testing
Failsafe Circuit Breaker Fair Data Preprocessing Equalized Odds
Postprocessing
BEFORE MODELING DURING MODELING AFTER MODELING
08 Create an organizational model for experimentation and learning
25
FEDERATE
D
CONTROL
CENTRAL
CONTROL
EXPERIMENT
DRIVEN
DESIGN
DRIVEN
Approach used
by startups
IDEAL
APPROACH
Approach used
by Large Organizations
Finding the right balance
between central vs federated
approaches is necessary while
planning each activity within the
algorithmic journey.
Traditional approaches
tend to deliver a low
pace of adoption.
