Karachi.AI Meetup # 2: Artificial Intelligence in Finance/Accounting and Disrupting E-Commerce with AI

WELCOME TO • MEETUP #: 2
• DATE: 31 – MAR – 2018
ENABLING EVERYONE TO APPLY ARTIFICIAL INTELLIGENCE

WELCOME TO
Event Co-
Host
THANKS TO OUR
PARTNERS
Learning Photography
Sponsors &
Supporters
Giveaways

A
G
E
N
D
A
Speaker Topic Time Slot
Registration & Hi-Tea 30 Mins 6:00 PM
KARACHI AI Mesum Hemani 05 Mins 6:35 PM
Keynote Speaker Guest Speaker 10 Mins 6:45 PM
Reciept Bot Irfan Sharif AI in Accounting (NC*) 10 Mins 6:55 PM
Dante BaseH Anis A. Sheikh AI in Financial Reporting 20 Mins 7:15 PM
Quants Society Sarah Rasheed AI in Financial Trading 20 Mins 7:35 PM
Tez Financial Naureen Hyat AI in Financial Lending 20 Mins 7:55 PM
Challenges with AI 8:00 PM
Namaz Break 8:15 PM
Key note - PEC Anum Kamran About PEC & Karachi.AI 10 Mins 8:25 PM
Botsify Usama Noman Botsifying Ecommerce 20 Mins 8:45 PM
AI in Ecommerce Mesum Hemani Intuition of AI in Ecommerce 30 Mins 9:15 PM
Challenges with AI 9:20 PM
––––––– Closing Note ––––––– 9:30 PM
Networking and Dinner 10:00 PM

LOCAL QUARTERLY GATHERINGS
EDUCATION
ECOSYSTEM MAPPING
WHO WE ARE ?
APPLIED ARTIFICIAL
INTELLIGENCE COMMUNITY

1 5 M I N T A L K S B Y P E E R S
O N L E S S O N S L E A R N E D
A I C L I N I C F O R I N S T A N T
C H A L L E N G E F E E D B A C K
P E E R - T O - P E E R N E T W O R K I N G
F O R R E L E V A N T E N G A G E M E N T S
LOCAL COMMUNITY
QUARTERLY GATHERINGS

C O N T E N T O N L O C A L E C O S Y S T E M
A C T I V I T I E S & P L A Y E R S
C U R A T E D , I N T E R A C T I V E L I S T S O F
E C O S Y S T E M A C T I V I T I E S & P L A Y E R S *
S P E C I A L R E P O R T D E V E L O P M E N T O N
G L O B A L C H A L L E N G E S A P P L Y I N G A I *
ECOSYSTEM MAPPING

Artificial intelligence is all about technology,
what we do is all about people. We want
everyone to discover the possibilities of
artificial intelligence and have access to
tools and knowledge of applying it in
business. We want the global influencers in
the applied AI field to share their lessons
learned so we can learn from the best.
Ultimately, we want to enable more people
to apply AI and to connect & collaborate in
the field to leverage it's potential.
EDUCATION & AWARENESS
C O N T E N T C U R A T I O N &
D I S T R I B U T I O N O N A P P L I E D A I
W O R K S H O P S E T U P & T R A I N I N G
F A C I L I T A T I O N A R O U N D E V E N T S *
P R O D U C T I O N O N L E S S O N S
L E A R N E D & E D U C A T I O N A L
R E S O U R C E S O N L I N E *

LEVERAGING THE POTENTIAL OF AI IN 50+ CITIES
AFRICA
Accra - Lagos
ASIA
Bangalore - Bangkok - Delhi - Hanoi - Hong Kong – Lahore – Karachi
Jakarta - Kuala Lumpur - Pune - Seoul - Singapore - Taipei
AUSTRALASIA
Wellington
EUROPE
Amsterdam - Berlin - Bratislava - Brussels - Bucharest - Budapest -
Cambridge - Cluj - Copenhagen - Delft - Geneva - Hamburg - Helsinki -
Krakow - London - Madrid - Munich- Paris - Rome - Sofia - Stockholm -
Tallinn - Tirana - Valencia -Valletta - Vienna - Zurich
NORTH AMERICA
Austin - LA - New York - San Diego - San Francisco
SOUTH AMERICA
Bogota - La Paz - Sao Paulo

GUEST SPEAKER
SHOAIB UL
HAQ(Assistant Professor, Karachi
School of Business & Leadership)
PhD in Business Administration

Karachi AI 2.0
AI in Finance
Shoaib Ul-Haq

Overview of AI
• What is AI?
– “The ability of a machine to perform cognitive functions we
associate with human minds”
– Ex: Perceiving, reasoning, learning, problem solving
• Goal of AI
– Develop computer systems that exhibit intelligence or
simulate the ability to think
• AI pioneered by Computer Science
• But, AI involves a combination of
– Computer Science, Biology, Psychology, Linguistics,
Mathematics, Engineering

What really is Intelligence?
• Specifically, what are the signs
of Intelligent Behavior?

AI revolution in finance
• Explosion of interest in quantitative investing
• Use high-speed computers and AI algorithms
• Find out patterns which can be exploited by trading algorithms
– Spot even transitory opportunities
– Continuous research on new signals and data sets
• Cost efficiency
– Pressure on fees and margins

Ron Kahn, Head of research at SAE
“There is a lot of disruption going on in asset
management. It may not be a great time to be
a 50-year old asset manager but it is a great
time to be a 28-year old with a lot of
quantitative abilities”

Challenges of algorithmic trading

Gold in yellow, left axis; S&P in green

IRFAN SHARIF
Co-Founder Receipt Bot
on
Applications of AI in Accounting
SARA RASHEED
Quant @ Matrix Systems Pvt Ltd
on
Application of AI in Financial
Trading
LESSONS LEARNED BY
ANIS SHEIKH
Founder Base-H
on
Applications of AI in Content
Writing
NAUREEN HYAT
Co-Founder Tez Financial Services
on
Applications of AI in Financial
Lending

Applications of
AI in Accounting
& Reconciliation
[ KARACHI AI ]
BY: IRFAN SHARIF (ACCA, Ex PwC)

Artificial Intelligence
In
Accounting

Irfan Sharif
• Cofounder and COO Receipt Bot – AI Driven Bookkeeping App
• Previously
• PwC – Oracle EBS Functional Consultant
• Rb – Finance Manager
• Lecturer – Accounting & Finance

Agenda
• What is Accounting?
• How AI will impact Accounting and Bookkeeping?
• What Receipt Bot is doing using AI?
• What technologies are available or becoming available?
• Summary
• Questions

AI in Accounting
Receipt Bot
Xero
QuickBooks
Sage
Exact
Recording
Account
Coding and
Categorization
Reporting and
Queries, Analysis
Compliance
Reporting
Summarising
Power
BI
Sage
Pegg
Reconciliation
Tax
preparation
and filing
Forecasting
Turbo
Tax
H&R
Block
Caseware
TaxCalc

Receipt Bot
• Paper sorting and recognition
• Document Tagging
• Data Entry
• Categorisation
• Duplication and missing documents checking

Accounting Coding & Categorisation
• Xero for Revenue code prediction
• Receipt Bot offers a similar feature on expenses
• Auto-coding based on history
• Other parameters if there is no historic data

Accounting Chat Bots
• Sage’s Pegg
• Hey Xero
• Amazon Alexa or Apple Siri like chatbot.
• Use the data in the accounting software for reporting
• Easier for entrepreneurs to get answers for quick
accounting questions.

Additional Areas
• Reconciliations: only a matter of time, when SMB bank
reconciliations are fully automated.
• Customer Relationship Management: Practice
Management and Customer Relationship Management
applications.
• Salesforce’s Einstein predicts potential sales or upsell
opportunities based on client interactions.
• Big Data availability provides analytics for companies.

Applications of
AI in Financial
Content Writing
[ KARACHI AI ]
BY: ANIS SHEIKH (MS Comp. Sci)

Applications of AI in Financial Content
Writing

Applications of
AI in Financial
Trading & Markets
[ KARACHI AI ]
BY: SAARAH RASHEED (B. Comp Finance)

ARTIFICIAL INTELLIGENCE
IN FINANCIAL TRADING
Saarah Rasheed
Picture Credits:
techcrunch

OUTLINE OF PRESENTATION
Overview of Financial Trading
Types of Analysis
Let’s Make Some Signals!
Success Stories
Potential Problems for AI in Finance
Potential Areas of Innovation
QAs!

FINANCIAL TRADING
Financial Trading is the practice of buying
and selling financial securities or
instruments to make profit, or at least,
hoping to.
A rational investor has an expectation of
profit from his or her investment. The
chance of not meeting that expectation
results in risk.
The variety of instruments traded adds up or
reduces the risk associated with trading.

ANALYZING MEANS OF
PROFITABILITY
BASED ON DURATION
• Long Term Trading
• Short Term
• High Frequency
BASED ON ASSET CLASSES
Portfolio Construction and Selection
Portfolio Rebalancing

TYPES OF ANALYSIS
There are two main schools of
thoughts in the world of finance.
• Those who believe in Random
Walk Theory
• And those who don’t.
“ Past
prices or
trends of
stock
prices can
not
predict
future
prices or
trends. ”

TYPES OF ANALYSIS
TECHNICAL ANALYSIS
• Short Term
• Relying on historical prices solely.
• Expecting profits through capital
appreciation
• Mitigating risk through off-setting
investment
FUNDAMENTAL ANALYSIS
• Long Term
• Taking into account the financials of
the company
• Expecting profits through capital
appreciation and dividend/fixed
income
• Mitigating risk through diversification

TYPES OF ANALYSIS
QUANTITATIVE ANALYSIS
• Heavily relying on mathematical compositions to understand
variation in instrument prices and quantifying the underlying factors.
• Scary looking models to analyze portfolio models and risk.
• Makes use of techniques from both fundamental and technical
analysis

LET’S MAKE SIGNALS!
Algorithmic Trading is an automated form of trading where on the
basis of certain ‘buy’ or ‘sell’ signals, the computerized platform
executes trades for you.
Algorithmic trading can be performed either on small time frames
(nanosecond as UHFT) or for large time frames (rebalancing bi-
monthly, etc).
Let us have a look at what these signals look like!

LET’S MAKE
SIGNALS!
A very simple and commonly used
signal for algorithmic trading is
Simple Moving Average or SMA.
It is computed over a certain
window say, of n periods, and
computes average over a rolling
period.
By using SMA of two different
windows, say x and y, where x >
y, we can generate buy and sell
signals for a particular stock in
real time and have the platform
execute sales on our behalf. Picture Credits:
OnlineTradingConcepts

LET’S MAKE SIGNALS!
Similarly, using mean and
variance, and other statistical
measures, signals can be
constructed to predict immediate
price changes and conduct buy-
sell to generate profits.
Some Indicators
and Oscillators to
know!
• SMA-100
• SMA-50
• RSI
• EMA
• MACD
• Stochastic
Oscillators

WHERE DOES AI COME INTO PLAY?
Wherever we deal with selection of
stocks or instruments or rebalancing
portfolio, or more generally, making a
decision regarding our investment
whether to buy, sell or hold a
commodity is capable of being done
through AI.
Before we dive in to possibilities, let’s
have a look at the problems regarding
why financial data is a tough choice for
predictions.

POTENTIAL
PROBLEMS
FOR AI IN
FINANCE
Financial Data is noisy!
•Overfitting
•Unstable Trends
•Difficulty in extraction of ‘useful’ information

SUCCESS STORIES
CASE STUDY: KAVOUT
• Investing with the power of AI
and quantitative analysis.
• Smart Advisor
• Predictive Ranking
• AI Powered Charts

SUCCESS
STORIES
A comparison of AI
managed funds vs.
traditionally managed
funds and their
performance over the past
few years.
There are some
interesting results!
Picture Credits:
Sigmoidal

SUCCESS STORIES
CASE STUDY: QPLUM
• Personal chatbot advisor
• Algorithmic Trading
• AI Managed Funds
• Low Cost
• Modern Quant

POTENTIAL OPPORTUNITIES FOR
A.I. IN FINANCE
If you are not directly forecasting prices, there is much
more you can do with AI:
• Building hedging strategies
• Understanding variation and risk
• Smart advisors
• Lower cost models for investment
In short, observe now to prepare for the future.

AREAS OF INNOVATION
Given the access to abundance of data and advanced computational
power available at our disposal, investments can be made more
transparent, secure and robust through AI.
Possible areas of innovations include:
• Portfolio Construction and Rebalancing
• Risk Analysis
• Personal Banking and Chatbots
• Trend Analysis

AREAS OF INNOVATION
• Hedging
• Algorithmic Trading
• Augmented Analysis through Sentiment Analysis
• Credit Scoring
• Predictive Analytics
And many more!

SKILLS YOU NEED
If you are a finance graduate and are looking to shift to AI or learn
and apply its technique, whether for research or to make a product,
make sure that:
1. Math doesn’t scare you. (At the very least, have knowledge of linear
algebra, matrices and vectors. For more advanced techniques,
know calculus!)
2. Statistical and probabilistic measures are your thing. (At the very
least know distributions. For more advanced techniques, know
stochastic and random processes!)
3. Acquaintance with one programming platform. (Python, R, C#,
C++, Java, MQL4)
4. You have an eye for opportunities, a self-driven motivation to
unlearn and learn!

QUESTIONS AND ANSWERS Ask away!
Picture Credits:
techcrunch

Applications of
AI in Financial
Lending & Credit
[ KARACHI AI ]
BY: NAUREEN HYAT (CFA)

Technological Advancement
Artificial Intelligence
Analytics
Cloud
Smartphones and smart devices
Software
Computing power
Connectivity
1970 1980 1990 2000 2010 2020 2030
Era of connectivity and
automation
Era of digitalizationEra of post industrialization

The Exponential Growth
4 thousand terabytes
data per day
2016
25 million terabytes
data per day
2017
Number of connected
device in 2010
8.4 billion
Number of connected
device in 2017
22.6 billion
Source: Domo

What AI can do for FinTech?
Recommendation
Suggest something on user behavior
Suggesting a financial product,
guestimate income or savings level
Goal Management and Budgeting
Automation
Perform a task based on user behavior
Algorithm performs action on behalf of
the user
Investment management
Prediction
Predict an outcome based on user
behavior
Algorithm predict the occurrence of an
event
Lending
Prevention
Prevent an outcome based on user
behavior
Algorithm can identify suspicious activity
or behavior
AML,
Identity fraud

Landscape in Pakistan
Source: Planet N

One mobile application that aggregates financial services for the un-banked, under banked and millennial users
Enabling them access to financial inclusion without any friction!
TEZCOMMITTEE
TEZADVANCE
TEZBIMA
TEZSARMAYA
Draw them in through
NANO-LOANS
Interest them through
community-led
DIGITAL ROSCAS
Provide protection via Life &
Health
INSURANCE
Economically empower them via
avenues of
INVESTMENTS
Tez Financial Services

AI in Tez
Collecting and
Structuring the
Data
Analyzing the
Data
Primary Purpose
Know your
customer

AI in Tez
Reducing
customer churn
Secondary Purpose
Up and cross sell
financial products
Customers
segmentation

AI in Lending
Suggestion
Prediction
Prevention

How a Limit is Created in Tez
1. Collecting Data 2. Identifying Pattern 3. Building Product
Student
Aptitude
test
Past
Papers
3000 monthly
expense
IBA
Intern at
HBL
Social Media
Digital Data
Financial Data
Pages liked
Interest
Time spend
Apps installed
Data usage
Battery usage
Bank Balance
Transactions
Billing behavior
Education
Entertainment

With great data
comes great
responsibility

• COLLABORATE ON INDUSTRY SPECIFIC GUIDANCE
• SHARE YOUR PERSONAL CHALLENGE APPLYING AI
• RECEIVE INSTANT FEEDBACK FROM PEERS
• ENGAGE WITH FELLOW PRACTITIONERS
AI CLINIC SESSION
CHALLENGE SUBMISSION
FACEBOOK.COM/KARACHIDOTAI
[ KARACHI AI ]

LESSONS LEARNED IN
Offline Experience

ANUM KAMRAN
Founder Buyon.pk & PEC
on
Importance of AI in E-Commerce
MEHSAM RAZA HEMANI
Founder Karachi.AI
on
Intuition of Ecommerce with AI
LESSONS LEARNED BY
USAMA NOMAN
Co-Founder Botsify
on
Botsifying E-Commerce

IMPORTANCE
OF AI IN
E-Commerce
[ KARACHI AI ]
BY: ANUM KAMRAN (Founder PEC)

BOTSIFYING
E-Commerce
[ KARACHI AI ]
BY: USAMA NOMAN (MS Comp Sci)

By Usama Noman
How Chatbot Can
Improve Ecommerce
Experience for Customers

Why Chatbots?
1- Business might be outsourcing their
customer chats to a agencies which
have pre-made scripts to answer from.
2- Or they have a small dedicated team
to answer customer questions.
Why not automate?
Customers already talking to your customer support agents 24/7.

What if it fails?
Or doesn’t answer a question correctly?

Get to know when your bot fails and
takeover chat seamlessly

How it’s better than a human?
1- Tone!
2- Purchases right from facebook chat window.
3- Accurate.
4- Fast

Tone & Presentation
1. The way customer representative present your
brand.
2. Emotions of customer representative.
3. The tone and the way he talks with your customers.
4. Training new customer agents.

Accurate
Mistakes happen!
But not very affordable in the ecommerce
industry. Price accuracy, delivery commitments,
package tracking, return policies.
All play an important role in customer care.

Fast
1. Customer chat is slow!
2. You need a team of 20 customer support
representative on a good weekend, but 2 on regular
one. How do you scale this?
3. What is expense to make the responses faster?

Purchases from App
Which is the one platform in the world with most customers?
Facebook.
Why not allow people to purchase produce while they are talking to your bot?

Future of
ECommerce
Experience

There is more!
How many times you come across following situations?
1- Replying customers when they ask price in your facebook post.
2- Alerting users for their package delivery?
3- Gathering feedback from customer?
4- Abandoned cart recovery.

Replying customers when they comment on your facebook post.

Alerting users for their package delivery?

Gathering feedback from customer?

How can I get one?
1- Sign up at botsify.com
2- Subscribe to your plan.
3- Create your bot
4- Launch
1- Help
2- Community
3- Youtube Channel
4- Email Support.

INTUITION OF
AI IN
E-Commerce
[ KARACHI AI ]
BY: MESUM RAZA HEMANI
(ACCA, IBM Cert, Coursera Mentor)

Harnessing the power
of AI in
E-COMMERCE
Presented By:
- Mesum Raza Hemani

The promising potential of Pakistan & E-Commerce
Our Presence and
Position
Our Progress and
Achievements
Our Bold
Startups

Why we have gathered to talk
about Artificial Intelligence?

Modes of Invasion for Artificial Intelligence
AI
Coordinators
Synthesizers
Companions
Diagnosticians
Transactors
Cyborgs

What's the intuition of AI to Ecommerce?
Bots & Virtual Assistant Computer Vision
Recommender Monitoring
Advance Analytics Anomaly Detection
Natural Linguistics Voice Engine

Intuition of
AI
in
Ecommerce
Reviews & RatingsDetect Fake ReviewsReact and Resolve

Improve discovery:
•NLP Searching
•Visual Searching
•Voice Searching
•Recommendations
•Remind Purchases
•Bot Best Friend

Improve discovery:
•NLP Searching
•Visual Searching
•Voice Searching
•Recommendations
•Remind Purchases
•Bot Best Friend
https://www.digitalcommerce360.com/2017/03/16/twiggle-unveils-search-
technology-allows-online-retail-company-take-e-commerce-giants/

Improve discovery:
•NLP Searching
•Visual Searching
•Voice Searching
•Recommendations
•Remind Purchases
•Bot Best Friend
https://medium.com/@Pinterest_Engineering/introducing-a-new-
way-to-visually-search-on-pinterest-67c8284b3684

Improve discovery:
•NLP Searching
•Visual Searching
•Voice Searching
•Recommendations
•Remind Purchases
•Bot Best Friend
https://techcrunch.com/2017/08/22/walmart-and-google-
partner-on-voice-based-shopping/

Improve discovery:
•NLP Searching
•Visual Searching
•Voice Searching
•Recommendations
•Remind Purchases
•Bot Best Friend
https://www.popsci.com/amazon-view-history-improve-
recommendations#page-4

Improve discovery:
•NLP Searching
•Visual Searching
•Voice Searching
•Recommendations
•Remind Purchases
•Bot Best Friend
https://medium.com/gobeyond-ai/5-benefits-of-cart-
abandonment-notification-ad34abf968ae

Improve discovery:
•NLP Searching
•Visual Searching
•Voice Searching
•Recommendations
•Remind Purchases
•Bot Best Friend
https://futurism.com/ai-chatbot-meaningful-conversation/

Recreate Experience:
•Voice carting
•Basketer Bot
•Voice navigation
•Personalize Shelf
•Digital Recognition
•Omni channel push

•Voice carting
•Basketer Bot
•Voice navigation
http://www.easyask.com/mcommerce

•Voice carting
•Basketer Bot
•Voice navigation
https://shelf.ai/

•Voice carting
•Basketer Bot
•Voice navigation
https://digiday.com/marketing/5-campaigns-used-facial-
recognition-technology/

•Voice carting
•Basketer Bot
•Voice navigation
https://www.dynamicyield.com/personalization/

Evolve Efficiency:
•Predictive SCM
•Enhanced insights
•Automated Pricing
•Crunch Feedback
•Website Outlook

Evolve Efficiency:
•Predictive SCM
•Crunch Feedback
•Website Outlook
If residents of Des Moines, Iowa, buy a lot of scarves in January, a local
fulfillment center might fill up with a collection of scarves — but none would
be shipped until an actual order is received at Amazon’s home-based
shipping system. When an order is placed, the item would already be halfway
to its destination, cutting delivery time to as little as one day. It could be even
quicker, depending on the customer’s proximity to an Amazon distribution
center.
Prior Amazon activity,
- Time on site
- Duration of views
- Links clicked/hovered
- Shopping cart activity
- & wish lists.
http://www.predictiveanalyticsworld.com/patimes/amazo
n-knows-what-you-want-before-you-buy-it/3185/

Evolve Efficiency:
•Predictive SCM
•Crunch Feedback
•Website Outlook
https://www.salesforce.com/eu/products/einstein/overview/
https://www.thoughtspot.com/data-chief/5-ways-machine-learning-can-make-your-bi-better
OUTLIER .AI

Evolve Efficiency:
•Predictive SCM
•Crunch Feedback
•Website Outlook
http://www.personali.com/solutions/

Evolve Efficiency:
•Predictive SCM
•Crunch Feedback
•Website Outlook
https://blog.nabler.com/customer-sentiment-analysis-a-
crucial-need-in-e-commerce-data-initiatives/

Evolve Efficiency:
•Predictive SCM
•Crunch Feedback
•Website Outlook
https://choice.ai/ https://onlinesales.ai/revx/

Heroes using the
power of AI in
E-COMMERCE
Presented By:
- Mesum Raza Hemani

Case Studies: What Amazon Does?
Real-time Product Recommendations
The e-commerce giant provides unique,
personalized recommendations to each
customer. This bestows a shopping experience
in which the most relevant products are
displayed as per the user’s choice and taste in
real time.
Style recommendations
Amazon is taking certain special efforts to use AI to
improve its marketing reach in the fashion industry. In
April 2017, Amazon launched Echo Look, a voice-
controlled, hands-free camera that uses a combination
of human advice and machine learning to act as one’s
personal stylist and is powered by Alexa. Alexa is
amazon’s AI voice assistant.
Catalog Quality
Flaws in product catalog such as missing attributes of
the brand, color, or poor quality of images can have a
negative impact on the user experience. Amazon is
using AI-driven analytics and machine learning to
extract missing attribute information such as brand or
color details from the product titles and images to
keep their catalog clean & updated.
Battling fake reviews
Product reviews provide a great means to effective marketing.
Customer reviews can influence the shopper’s decision in both
ways. Since product reviews are considered extremely
important on e-commerce websites, fake feedbacks and reviews
can be posted to boost the product’s ratings and sale on the site.
To check this malpractice of proliferation of fake reviews,
Amazon released a machine-learning algorithm to selectively
filter authentic online feedbacks and product reviews.
Amazon also believes in its recommendation engine so much so that they intend on predictive deliveries to
customers who are likely to buy certain items at certain times before they even order the product.

Case Studies: What Amazon Does?
Real-time Product Recommendations
- User’s demographics
- Item’s Features
- Users History
- Item Popularity
Style recommendations
Number of factors, Amazon explains,
including how the clothes fit, what colors
look best on you, how they’re styled, and
what’s on trend.
Catalog Quality
- Crowd Sourcing Corrections
- Generate New Attributes based on Customer Prefab
- Using Computer Vision to Detect Details
- Encouraging strict Catalogue Quality Policy
Battling fake reviews
- Similar keywords in multiple reviews
- Reviews that are too un-specifically positive (helpful)
- Lots of reviews in a short time frame
- Vine Customer Review of Free Product.
What is required to do so? .. What are we missing? Or Lack of Innovation?

Case Studies: What EBAY Does?
Shopbots and Shop the Room
The innovative app is powered by AI-driven data analytics and
can be accessed through the Facebook messenger platform as
well. eBay ShopBot lets users interact with a chatbot using a text
message, or through the speech, or an image.
Shop the Room, allows the users to hover over products shown
on each room image which is then followed by eBay displaying
a similar product on a pop-up window.
Image Search and Find It
The company launched two apps – Image Search and
Find It On eBay. Image Search is an app that matches a
user’s photo of any item to visually comparable listings
of over a billion products featured on the website.
Alternatively, a user can use any photo on their social
media account or from a web browser to search for
similar products using Find It On eBay.
Two out of six of eBay’s acquisitions in 2016 were companies that were built on AI-driven platforms
namely Salespredict and Expertmaker. The company believes that the acquisitions’ predictive analytics
and machine learning capabilities will help the company strengthen its structured data.

Case Studies: What EBAY Does?
Shopbots and Shop the Room
- Start Logging Customer Chats and Interactions
- Look out for common flows of conversation and map it
- Test a humanly walkthroughs | Try & Fail & Learn.
Image Search and Find It
- Use Computer Vision (DL) to Find Similar Images
- Fast ranking with Latest Technology Stack
- Envisioning Offline Retail Experience to map online
What is required to do so? .. What are we missing? Or Lack of Innovation?

Case Studies: Indian market players?
Ola Play
Ola has been using AI & Analytics to battle the various
attempts of fraud. The Ola driver community has
gained a reputation for finding loop holes & hacks to
meet their incentives or to simply just cheat the system
– with the help of tech as well as support from
authorities, Ola has been making great advancements
in identifying & preventing such incidents.
Myntra
Artie- Online fashion retailer Myntra is using
futuristic technologies like data analytics and artificial
intelligence (AI) to help its designers leap ahead in the
fashion scenario. The AI-fuelled tools help designers
come up with fresh, trendsetting, patterns and styles
that can attract buyers and boost sales for apparel
makers.
Zivame
AI-driven product
recommendations
on a number of
other channels to
find and
communicate the
most relevant
product to each
customer.
CaratLane
Introduced the world’s first virtual 3D jewelry try-on app to address the customers’ concerns for
a tactile, ‘look and feel’ experience before buying any product online. The app uses facial
recognition and 3D imaging technologies to provide a virtual, yet a vividly realistic, try-on
experience.
Combining omni-channel personalized recommendations with tech that allows the users to get a
good idea of how the products are likely to look and feel on them, Caratlane is likely to have a
positive impact on how online jewlery shopping is perceived & consequently boost their
customery satisfaction & sales.
Indian Pakistani
Markets are Similar to each other with both booming in E-Commerce

PayTm
“Charumitra Pujari, chief technology officer, Paytm, revealed that “every pixel”—each icon,
product row, column — on Paytm’s homepage is personalized and reordered differently for
each of its 225 million users. She further explained that with AI as a foundation, the platform
makes 20,000 recommendations per second—each of them in under 20 milliseconds.
Furthermore, the platform also crafts promotions for the consistent buyers by putting machine
learning to use. However, these promotions are created only when Paytm detects an intent to
buy.
Pujari quoted, “If you wanted to buy a ceiling fan, which is not promoted on (the) home page,
once you started looking, in real time, we can pick up your request and kind of put together a
promotion for you.” She further added, “If you’re just browsing, looking at ten different
products, I won’t create the promotion.
Additionally, Paytm is now beginning to offer lending services and credit cards to customers.
But, to gauge how much a user can borrow, the company has employed machine learning
again, “capturing signals from the mobile app to find out who you are and what credit you
should be eligible for,” Pujari said. ”

ShoppersStop
Major step towards the more innovative developments in AI at Shopper’s
Stop, the e-commerce player has attempted the inception of Magic Mirror.
The augmented reality-based dressing room – Magic Mirror – is an AI-
powered intelligent photo-booth that allows the customers to select, view, and
try-on the apparels and accessories virtually. This not only offers a hassle-free
magical shopping experience to the customers, but assists them in matching
and styling themselves, without having to match and try the products in real.
With the recent steps that the company has taken in the field of data analytics,
AI, and Machine Learning, the company aims to achieve a minimum 15%
revenue through digital touch points and 10% sales through the online
channels by 2020, as revealed by Govind Shrikhande, MD, Shopper’s Stop.

NearBuy
Nearbuy, initiated the process of reaching out to each its customers through
emails that contained the product recommendations relevant to their unique
taste or preference. Each time a customer would click on a product, he would
be re-directed to the corresponding offer page on the website.
They achieved impressive results that could be quantified by the virtue of AI
that was linked all through the process. Nearbuy observed an overall increase
in the click-to-open-ratio (CTOR) by 35.7%, in response to the email
notifications that were communicated to the customers. As a response to the
app notifications, an overall increase of 51.6% was achieved in the revenue
generated.

Flipkart
Has unveiled Mira, an AI-based conversational search experience, which
allows the firm to talk to its users as they look for the required products. Mira,
guides and assists the consumers in shopping by suggesting the shopping
ideas, offers, and recommendations relevant to them.
Vikram Sharma, the Director of Product at Flipkart, elucidates, “We have
machine learning based techniques to (predict) the content the customer is
most likely going to click on, Based on the past history of consumer behavior,
which the firm continues to collect throughout its decade-long presence in
India, the AI-led techniques help the firm to identify various other detailed
elements such as age, gender, geographical location, preferences, and trends to
name a few. By further understanding the intricate details of each customer,
the AI and ML powered algorithms trigger the right set of personalized
product recommendations, which are then communicated to each unique
customer effectively across different channels.”

Many more
to learn
from..
https://www.cbinsights.com/research/ai-retail-smart-shop-startups/

What's required to prepare for and utilize AI power?
1. Vision
2. Research
3. Data
4. Algorithms
How to execute into AI?

1. Vision
2. Research
3. Data
4. Algorithms

1. Vision
2. Research
3. Data
4. Algorithms
NEW ASSETS
ROA | RETURN ON ALGORITHM

Gracias!
Connect with Me
•LinkedIn @
• www.linkedin.com/in/mesumrazahemani
•Email:
•mesumraza786@Hotmail.com
Thankyou

Artificial intelligence is all about technology,
what we do is all about people. We want
everyone to discover the possibilities of
artificial intelligence and have access to
tools and knowledge of applying it in
business. We want the global influencers in
the applied AI field to share their lessons
learned so we can learn from the best.
Ultimately, we want to enable more people
to apply AI and to connect & collaborate in
the field to leverage it's potential.
PEER-TO-PEER NETWORKING
CONNECT BASED ON DATA SCIENCE BRANCH
MACHINE LEARNING
NATURAL LANGUAGE PROCESSING
COMPUTER VISION
… ANY OTHER BRANCH
FEEDBACK SUBMISSION
FACEBOOK.COM/KARACHIDOTAI

WELCOME TO
IS AI AWARENESS YOUR NEXT GOAL?
SEE YOU AGAIN NEXT TIME
IN JUNE 2018
THANKS FOR JOINING!
Event
Highlights

WELCOME TO
IN JUNE 2018
THANKS FOR JOINING!
Event Co-
Host
Learning Photography
Sponsors &
Supporters
Giveaways

WELCOME TO
Connect Us
Facebook: KarachiDotAI
LinkedIn: Karachi.AI
IN JUNE 2018
THANKS FOR JOINING!
Learn with Us
www.bit.ly/karachidotai
Join Us
Facebook Groups
KarachiDotAI

Karachi.AI Meetup # 2: Artificial Intelligence in Finance/Accounting and Disrupting E-Commerce with AI

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Similar to Karachi.AI Meetup # 2: Artificial Intelligence in Finance/Accounting and Disrupting E-Commerce with AI

Similar to Karachi.AI Meetup # 2: Artificial Intelligence in Finance/Accounting and Disrupting E-Commerce with AI (20)

Recently uploaded

Recently uploaded (20)

Karachi.AI Meetup # 2: Artificial Intelligence in Finance/Accounting and Disrupting E-Commerce with AI

Editor's Notes