machine learning - ncr...innovation conference 2017 machine learning raghu rajah vice president,...
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INNOVATION CONFERENCE 2017
MACHINE LEARNINGRaghu RajahVice President, Engineering & Product ManagementDigital Banking
Please use theInnovation ConferenceEvent App to check-in to this session S687
NCR Innovation Conference 2017: Confidential
1950s 1960s 1970s 1980s 1990s 2000s 2010
ARTIFICIAL
INTELLIGENCEMACHINE
LEARNINGDEEP
LEARNING
Divide this
Start training
Get better
Over many dimensions
Over manymachines
A quick example
Credit Scoring
State of the art solutions look beyond FICO/D&B scores, consumes multiple features, and manages a live credit decisioning process. Uses many traditional Data Science, AI and some deep learning techniques.
Fraud Detection
Contemporary systems use anomaly detection algorithms (some DL) on streaming data.
Anti-money laundering
Graph Analysis and traditional AI techniques are the common approaches in contemporary AML solutions.
Robo Advisors
Applies a wide variety of AI techniques from Monte-Carlo simulation to Deep Learning at various levels
Customer Engagement
Deep Learning techniques could analyze customer behavior to determine attrition risk, upsell/cross-sell opportunity, and effective engagement
Chatbots
State of the art chatbotsuse deep learning for NLP and use sequence to sequence models achieve performance
Challenges for ML in Financial Services
Learning algorithms tend to learn to discriminate, based on the patterns in data – some of which is actually illegal, other might be unethical.
Deep Learning solutions are very effective, but tend to operate like a black box. This might cause regulatory issues.
Learning Algorithms tend to require a lot of data, the right use of which has some open questions.
Regulatory environment might not be very friendly.
INNOVATION CONFERENCE 2017
THANK YOURaghu RajahVice President, Engineering & Product ManagementDigital Banking
Please use theInnovation ConferenceEvent App to check-in to this sessionNCR Innovation Conference 2017: Confidential
INNOVATION CONFERENCE 2017
BLOCKCHAINPatrick WatsonApplication Security Architect, NCR Corporation
Please use theInnovation ConferenceEvent App to check-in to this session S687NCR Innovation Conference 2017: Confidential
TRUSTBUTVERIFY
- THE BLOCKCHAIN WAY
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Trust Systems – An Example
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Physical Digital Blockchain
ACH ACH
NCR Innovation Conference 2017: Confidential
Public, Permissionless (Bitcoin)
Private, Permissioned (Real $)
Cryptocurrencies
Public
Creates new assets
Alternate Currencies can be:
Borderless
Low fee, enabling micropayments
Serve the unbanked
Bottom Line Apps
Private
Usually Tracks existing assets or processes
Reduces cost, delays:
Remittance
Clearing & Settlement
International Exchange
Risk Knowledge Sharing
Top Line Apps
Public or Private
New applications
New opportunities:
Smart Contracts
Data Hosting
IoT Swarms
Identity Management
Blockchain Applications
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Cryptocurrencies Bottom Line Apps Top Line Apps
Blockchain Applications
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How could this work anyway?
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3. Mined blocks of transactions are propagated to a
record of previous transactions – creating a
distributed database of permanent records
2. Miners verify transactions, put them into
blocks, then cryptographically harden the
records to make it immutable
Nonce, nonce,
nonce, c’mon
nonce!
yah baby!
It’s all
mine!
1. Person-to-person transaction
is initiated – to them, it looks
like any other app
$100 for
the bike
OK
Ethereum
Smart Contract
Auction House
A. Validate crypto & transaction details
B. Assemble transactions into blocks
C. Race to generate valid proof-of-
work/proof-of-stake.
D. Winner receives incentive
• Every full node has all data
• Bitcoin: pseudo-anonymous addresses,
but transfer amounts visible
• Ethereum: depends on contract’s code,
transaction details could be encrypted
or one-way hashed
Vs Traditional Applications
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VS: Goes through a centrally
control system
Nonce, nonce,
nonce, c’mon
nonce!
yah baby!
It’s all
mine!
VS: the intermediary (human/manual process,
network, processor, etc.)
Remittance
Service
Provider
Insurer
Notary
Loan agent
VS: silo-d databases where records can be
modified
$100 for
the bike
OK
3. Mined blocks of transactions are propagated to a
record of previous transactions – creating a
distributed database of permanent records
2. Miners verify transactions, put them into
blocks, then cryptographically harden the
records to make it immutable
1. Person-to-person transaction
is initiated – to them, it looks
like any other app
INNOVATION CONFERENCE 2017
THANK YOUPatrick WatsonApplication Security Architect, NCR Corporation
Please use theInnovation ConferenceEvent App to check-in to this sessionNCR Innovation Conference 2017: Confidential
INNOVATION CONFERENCE 2017
FINTECH SPEED DATING - IOTGirish Narang
Chief Architect, Digital Banking
Please use theInnovation ConferenceEvent App to check-in to this session S687NCR Innovation Conference 2017: Confidential
IoT
27NCR Innovation Conference 2017: Confidential
The Internet of Things (IoT) is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction.
Things communicating with other things via the internet, without human
interaction.
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High Growth
7 Devices per
human on the
planet - 2020
Connectivity Cheap Hardware Data Storage Customer Delight
Enabling Forces
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$1
Health Energy Insurance/Finance Retail
Common Use Cases
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Car Insurance
Voice
Banking
In-branch
Location
Beacons
Voice
Ordering
Thermostats
Lighting
Heart Monitors
BMI Monitors
Mobile
Shopper
Why is it important for FIs?
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New Digital Channel
Desktop, Mobile and now Smart Watches,
Amazon Echo etc
Increased Engagement
Personalized experience yields 20x engagement
Offer more personalized products
Car insurance by the mile
Variable risk based mortgage
Edge Devices Branch Transformation Smart Gateway Analytics
NCR investing in the full ecosystem
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33NCR Innovation Conference 2017: Confidential
Demo – Smart Piggy LightLow Balance
INNOVATION CONFERENCE 2017
THANK YOUGirish Narang
Chief Architect, Digital Banking
Please use theInnovation ConferenceEvent App to check-in to this sessionNCR Innovation Conference 2017: Confidential
INNOVATION CONFERENCE 2017
COMPUTER VISION Shuki LichtChief Enterprise Architect, Software Solutions, NCR
Please use theInnovation ConferenceEvent App to check-in to this session S687
NCR Innovation Conference 2017: Confidential
FUTURE FRICTIONLESS CHECKOUT CONCEPT
Ann is identified as she enters the store to pick up a her lunch.
As she picks up items from the shelf they are automatically added to her virtual basket.
Using her phone she can see the price of the items in her basket and be reminded that the store is offering a personalized meal deal promotion.
She picks up the rest of her meal and sees that the discount has already been applied.
As she exits the store, Ann is charged on her preferred debit card by simply walking out.
A receipt of the transaction is sent to her digital wallet to give her a record of the purchase.
check-in
check-out
Real-Time Recommendati
on
ItemDetection
ShopperLocation
NCR Confidential
ShopperLocation
ItemLocation
Shopper
TrackingShelf
VisionShelf
Sensors
Shoppers ItemsVirtualBasket
Store HUB Controller
InventoryCheck-inCheck-out
Retail One
Order Service
TDMService
PromotionService
CustomerService
LocationService
InventoryService
Store IoT
Restful / real-time
90 DAY BLUE PRINT
NCR Confidential
Mobile
ShopperStore
Manager
BeaconsBiometric
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Face Recognition
Behavior Biometrics
QR Code
Voice Biometrics
Additional Sensors
RFID
BLE
BIOMETRIC EDGE TECHNOLOGY
NCR STORE VISION
REAL-TIME - SHOPPER LOCATION, BASKET AND PHYSICAL INVENTORY
Shopper Tracking
Shopper Check-in
Shelf
VisionShelf
Sensors
https://www.dropbox.com/s/cbo06gqeeodjhhu/Synergy%20Vision%20Store%202017.mp4?dl=0
https://www.dropbox.com/s/7scb99eim9elzyy/synergy2017_2.mp4?dl=0
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SYNERGY 2017 - VIDEOS
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DI INSIGHTS WITH VISION
INNOVATION CONFERENCE 2017
THANK YOU
NCR Innovation Conference 2017: Confidential