it, computing and communications alert (techvision)...convenience warrants better understanding of...
TRANSCRIPT
IT, Computing and Communications Alert
(TechVision)
March 18, 2016
D881-TV
Artificial Intelligence Empowering Digital Banking and
Finance Ecosystem
D881-TV 2
Contents
Section Slide Number
Impact of Artificial Intelligence on Banking and Financial Services 3
Artificial Intelligence Impacting Banking and Financial Services–Overview 4
Anti Fraud and Risk Monitor with Deep Learning Neural Networks 5
Machine Learning-based Financial Search Engine 6
Automated Big Data Finance Underwriting Model 7
Management Tool for Structured Financial Products 8
Artificial Intelligence-based Automated Banking Information Platform 9
Wearable Biometric Authentication Solution for Digital Payments 10
Eye-print-based Biometric Authentication Solution for Mobile Payments 11
Facial Recognition-based Digital Payment Solution 12
Strategic Perspectives 13
Industry Contacts 17
D881-TV 3
Impact of Artificial Intelligence on Banking and
Financial Services
D881-TV
Artificial Intelligence Impacting Banking and Financial Service–
Overview
Transformation
• In recent years, banking and finance is experiencing increasing usage of artificial
intelligence (AI) for improved business performance.
• Machine learning, Big Data and data science are all related to building components of AI
systems that feed data from users to the intelligence software. The competition among
financial service providers to reduce cost of services and to maximize customer
convenience warrants better understanding of user preferences and risk management.
Key Benefits
Boosts Productivity
Better
Knowledge
Absorption
Real-time
Feedback
System
Reduces
Cost
Enhanced
Engagement
Increased customized automation through machine learning and
pattern recognition could help financial organizations to offer
more personalized services in real-time at a much reduced cost
as compared to manual process management. Advances in
analytics algorithms and improvements in computational power
are enabling the development of a wide range of service
platforms for the banking and finance sector. Here are some
emerging application areas in banking and financial service
(BFS) that use AI.
Applications Areas
Smart Digital
Wallets
Insurance Decision
Making System
Risk Management
Advanced Biometric
Authentication
Automated
Financial Advisors Fraud Detection
Key Areas
Skymind Deeplearning4j Platform
Anti Fraud and Risk Monitor with Deep Learning Neural Networks Skymind, USA
Why do we need Deep Learning Anti Fraud and Risk Monitors ? On a daily basis, banks have to process millions of transactions, thus their compliance departments have to issue thousands of authorizations per second. During this process, the department is only spared a few milliseconds to analyse and judge whether the transaction is fraudulent or not.
While learning to model fraud, a small sample set from a tiny percentage of total transactions is used to analyse fraudulent materials. This occurrence leads to massive down sampling where 90% of the transactions are not sampled, thus, losing valuable information regarding the evolution of modern frauds.
Finance institutions face an immobile necessity issue where they need to guarantee their users and stakeholders a 99.99% server uptime which is difficult to produce because conventional systems are fragile and are not constantly updated, thus decreasing the reliability of their services.
Which solution can help??
Skymind, an anomaly detection framework for enterprise
service providers, is the supporting backbone for the open-
source framework Deeplearning4j, allowing use of deep
learning into e-commerce, finance and recommended systems.
Key
Technology
Capabilities
The Skymind Deeplearning4j Platform is a huge application enhancement because this innovation will boost the finance industry threat detection facility significantly as this self learning and constantly evolving application will combat fraudulent threats. With the current situation of malicious threats on the Internet, this application will have a great impact on the finance sector, thus increasing its demand in the near future.
Rapid Analysis of
Big Data
Continuous Deep
Learning
Analysis/Results
Cross Platform
Adaptive Framework
Key Benefits from Implementation
Short Term
(1-2 Years)
Medium Term
(3-4 years)
Long Term
(>5 years)
Market Opportunity
High High
Our Thoughts
Medium
The Skymind algorithm is one step ahead of fraudulent threats. The
integrated Deeplearning4j framework enables constant data analysis for
anomalies and also triggers automatic specific responses to disable any
fraudulent related activity.
The Deeplearning4j open-source framework uses the pattern analysing
methodology that is predicted using deep learning that can be used to
monitor patterns for stock-price action, the weather and remote sensor
outputs. The similar learning methodology of patterns runs through the
deep learning framework for high-end analysis using pattern records.
The compact deep learning models that are integrated into the Skymind
Deeplearning4j framework can highly assist low-memory devices, such as
smart mobile devices, tablets and wearables. These devices can understand
and interpret their surroundings, resulting in reduced errors in measured
parameters and data by the device.
AlphaSense Financial Search Engine
Machine Learning-based Financial Search AlphaSense, US
Why do we need Financial Search Engines?
Critical information is scattered all over the Internet in separate sources directed to separate audiences. Information that is necessary for any specific use can be found in multiple sources on the Internet with duplicated data sets rendering the information to be less reliable.
Scattered information causes many ambiguous and misleading situations, where the time used to search for particular information can be dragged to a very long and unproductive time period by the user.
The research process a user undergoes in order to analyse an industry, organization or market is very inefficient and painful as the user has to scheme through big piles of papers by manually going through each research paper using basic skills that is often filled with human errors. Which solution can help??
Key
Technology
Capabilities
Financial news and press releases are constantly being updated on the Internet. The AlphaSense Search Engine is a breakthrough application for the finance industry as this will allow bankers and financiers to immerse themselves in a new finance information portal that will allow its users to gain vast amounts of knowledge related to the finance sector. A positive feedback is expected from the users of this search engine as this innovation brings immense enhancement to the finance industry.
Sophisticated and
Efficient Features
Real time & Smart
Search Results
Large &
Continuously
Updated Database
Key Benefits from Implementation
Short Term (1-2 Years)
Medium Term (3-4 years)
Long Term (>5 years)
Market Opportunity
High High
Our Thoughts
Medium
AlphaSense also has an enhanced Smart Filtering and Alerting framework
that sends powerful email alerts related to the user’s search target and
documents related to their search scope. This framework uses advanced
tagging and relevance filtering functions that operate using machine learning
algorithms to quickly find the most suitable and related content on any topic,
company or industry.
The AlphaSense platforms unique One Search across all documents feature enables
the user to search for a keyword through SEC and global filings, broker research,
conference call transcripts, investor relations presentations, personal in-house content
and real-time news and press releases.
AlphaSense, launched in 2010, is a software technology
startup that serves the financial service industry globally.
AlphaSense applies high-end technology to assist
knowledge and investment professionals to find critical
information related to the finance industry.
The AlphaSense Search Engine is enhanced with the Intelligent Search
framework. This framework combines a number of different sources in a single
location. The framework has features that index every text line intelligently in
order to directly access keywords. The Smart Synonyms technology is
leveraged to enable synonym keyword searches that indefinitely extend the
search criteria based on the search scope.
Enterprise Gamification Platform
Automated Big Data Finance Underwriting Model ZestFinance, USA
Why do we need Financial Underwriting Model? In the Finance industry, traditional lenders have been using the same underwriting methods for the past 40 years. These methods are used to decide whether credit can be offered to the client or not. These methods are based on small assumptions that are vague and often unreliable.
Data on the internet is enormous and is categorized based on cultural, economical or societal context. Machines do not understand the complexity of these hybrid and complex data in a way that humans can naturally observe.
Financial advisors use similar methods to underwrite. These methods are either by using logistic regression, decision trees or combination of both. These methods often lead to incorrect decisions due to the imperfections of the offered models.
Which solution can help??
ZestFinance, formerly known as ZestCash, consisting of
former Google and Capital One employees, is a team of
mathematicians and computer scientists working on
helping credit lenders of all credit segments with a better
credit risk assessment of new potential borrowers.
Key
Technology
Capabilities
The financial underwriting methodology has been the same for a long time. ZestFinance has taken the initiative to bring a new order of underwriting methodologies in order to provide more trustable and accurate credit decisions. A positive feedback by 2017 is expected to drive this project to achieve its milestones and to provide a stable underwriting model for the financial industry.
Continuous
Learning
Framework
Accurate Analysis High ROI
Key Benefits from Implementation
Short Term (1-2 Years)
Medium Term (3-4 years)
Long Term (>5 years)
Market Opportunity
High High
Our Thoughts
Medium
The ZestFinance Model uses its machine learning and neural network
attributes to analyse large amounts of potential credit variables. These
variables range from financial information to technology usage. These
factors are taken into consideration as this will allow a better picture to
assess uncertain factors such as potential for fraud, the risk of default and
the growth of long-term client relationship. The underwriting model
provides high improvement up to 40% by using accurate credit decisions
that lead to increased availability of credit for borrowers and a high return
payment rate for lenders.
The underwriting model by ZestFinance is developed by combining highly
rated data modellers and top tier credit analysts in the finance field to
construct an efficient Big Data model that rapidly and continuously
improves the quality of underwriting for the finance industry.
Quotip Financial Management Platform
Management Tool for Structured Financial Products Quotip, Zurich
Why do we need Financial Management Tools? Digital technologies enhancing business propositions use many different tools and software that provide great improvisation in business analysis .These tools often require many separate authentication protocols and often cause human errors due to separate complex tools and different software output
Organizations handle their daily reports using multiple supporting tools. These tools allow organizations to compile term sheets and basic prospectus separately which can be a continuous troublesome process that decreases employee productivity.
Bankers and financiers rely on information from websites, portals and newspapers to be updated with latest market or industry news coverage. Most of this information is scattered on the Internet and browsing through separate information mediums is time consuming.
Which solution can help??
Quotip, a start-up in Zurich, is a financial technology
company that provides its users a comprehensive and
integrated sequel of services in three main areas that
are Find, Quote and Report.
Key
Technology
Capabilities
With the rapid growth in Big Data affecting the Finance industry, this positive venture will allow many opportunities for massive finance related content management. Quotip has developed a platform that enables a user-friendly environment for wealth managers to find, price, settle and monitor structured products easily, thus an increase in demand for this application in the finance industry will revolutionize the Financial Products Management services.
Precise Smart Data
Analysis
Automated
Management
Reducing Back-
Office Cost
Key Benefits from Implementation
Short Term (1-2 Years)
Medium Term (3-4 years)
Long Term (>5 years)
Market Opportunity
High High
Our Thoughts
Medium
The Quotip Platform is designed with an idea generator framework that is easy
to use. This tool offers complete and spontaneous scenarios of investment
opportunities that are based on predominant market conditions. Modern
machine learning techniques contributed to this framework that allows
indicative pricing capabilities without relying on any sell-side infrastructure.
Quotip used an innovative step to provide its users with full and flexible
overviews for each initiated request by merging the possibility of receiving
manual and automated quotes from within the same workflow. This price
discovery framework assures its users the best execution with a precise
request-for-quote process.
The settlement and clearing technology integrated into Quotip allows massive
reductions in settlement time, mitigation of associated risks and dramatically
reduced back-office cost. On the other hand, the Quotip monitoring and
reporting functionality complies with the latest regulatory requirements of the
financial industry. A customizable notification system integrated into the
platform allows improved client specific experience.
FinGenius Platform
Artificial Intelligence-based Automated Banking Information Platform FinGenius Limited, UK
Why do we need Automated Banking Information Platforms? Banks’ customers find it difficult to communicate with their banks when they require specific information about their finances. Online self-service interfaces are populated with too much information, often failing to answer customers’ specific queries.
Contact center-based assistance is time consuming. Customers are required to provide their details repeatedly to obtain personal financial information, which has a negative impact on customer experience. Customers today demand prompt personalized experience.
New bank employees, on the other hand, find it difficult to obtain domain-specific information about the banks. This makes onboarding processes difficult and time consuming as employees need to go through detailed databases to find the required information.
Which solution can help??
The FinGenius Platform is an AI-based intelligent and
automated banking information solution that significantly
reduces the complexities of obtaining banking
information for customers and employees.
Key
Technology
Capabilities
The FinGenius Platform seems to be a notable innovation to facilitate self-service banking information access with a personalized experience. The integration of NLP and machine learning empowering the solution with human-like intelligence is a key step forward. The capability of the platform to learn with experience and achieve higher accuracy over time will be a key point of interest for banks to automate information sharing.
High Integration
Potential
Personalized User
Experience
Real-Time Accurate
Information
Key Benefits from Implementation
Short Term (1-2 Years)
Medium Term (3-4 years)
Long Term (>5 years)
Market Opportunity
High High
Our Thoughts
Medium
The solution leverages proprietary Natural Language Processing (NLP)
algorithms to understand customer or employee queries in the form of
spoken questions. The algorithms are intelligent enough to understand
different languages and abbreviations and can distinguish between spoken
accents to deliver highly accurate speech recognition in real time.
The Fingenius Platform is powered by proprietary machine learning
algorithms that allow it to perform highly accurate information retrieval.
The capability of these smart algorithms to explore huge volumes of
complex data and deliver contextual outputs with human-like reasoning
gives a human touch to the interaction platform.
The solution has high integration potential and can seamlessly co-exist with
existing infrastructure such as communication channels, customer relationship
management (CRM) and so on. Additionally, the flexibility of the platform to be
deployed either on the cloud or on premise depending on information
sensitivity and requirements ensures optimum security of confidential data.
Nymi Band
Wearable Biometric Authentication Solution for Digital Payments Nymi Inc., Canada
Why do we need Wearable Biometric Authentication for Digital Payments? With the steep decline in the use of payment instruments, such as cheques and cash, digital payment technologies are rendering more secure, flexible and convenient methods for cashless financial transactions.
Assuring security in digital payments has been the biggest challenge faced by solution providers, payment authentication being the most significant one. Incidences of false authentication and abuse of digital payments are growing exponentially.
Traditional card and personal identification number (PIN)-based authentication methods are prone to forgery. Legacy biometric approaches such as fingerprint recognition are also found to be unsafe as they can be easily replicated.
Which solution can help??
The Nymi Band is a wearable wristband that uses multi-
factor authentication. The solution leverages advanced
AI technology to facilitate contactless secure digital
payments.
Key
Technology
Capabilities
The Nymi Band is a promising innovation, making digital payments more secure. The innovative approach of using continuous heart signals as an authentication modality largely minimizes the complexities involved in providing authentication information every time a transaction is made. The solution, by virtue of its advanced HeartID technology and easy integration capabilities, has the potential to become an authentication standard for contactless payments.
Robust biometric
security
Contactless
payments
High user
convenience
Key Benefits from Implementation
Short Term (1-2 Years)
Medium Term (3-4 years)
Long Term (>5 years)
Market Opportunity
High High
Our Thoughts
Medium
The solution consists of an electronics module, namely, Nymi Core. It
leverages an electrocardiogram (ECG) sensor containing two electrodes
that capture ECG data of the user wearing it. The band continues to identify
the user and authenticate payments only till the time it can sense the user
by obtaining the ECG data.
Leverages proprietary HeartID technology to identify individual users
through heartbeat authentication. The technology has been developed
using high-grade proprietary signal processing and machine learning
algorithms for accurately identifying a user through the ECG data
patterns. This unique approach dispenses with the need for repeatedly
collecting biometric data for multiple transactions.
The Nymi Band uses Bluetooth 4.0 Low Energy (BLE) radio to perform
wireless communication with point-of-sale (POS) devices for transactions. The
Nymi Companion Application (NCA), linked with the band and digital payment
cards or accounts, serves as an interface for user enrollment and to facilitate
authentication for payments.
Eyeprint ID
Eye-print-based Biometric Authentication Solution for Mobile Payments EyeVerify Inc., USA
Why do we need Mobile Biometric Authentication? Mobile payments are gaining rapid popularity globally. However, significant security concerns have restrained large-scale adoption of mobile payment solutions. Confidential banking credentials stored on devices are vulnerable to cyber theft.
Usage of personal identification numbers (PINs) or one-time-passwords (OTPs) involves complex procedures and makes mobile payments lengthy. This negatively impacts user experience.
Touch-based mobile biometric solutions, such as on-device fingerprint scanning are often inaccurate. The sensors often become non-responsive due to the accumulation of dirt. Additionally, fingerprints can be easily duplicated to gain unauthorized access.
Which solution can help??
The Eyeprint ID is an innovative mobile biometric
authentication solution for digital payments. It does not
require any additional expensive embedded sensors and
uses optical biometrics using photographs of eyes..
Key
Technology
Capabilities
The Eyeprint ID solution is a major step forward toward enabling secure biometric authentication for mobile payments even with budget camera phones. The capability of the innovative proprietary backend technology, powered by machine learning, to offer real- time optical biometric authentication, along with FIDO certification, will be key factors toward making it a preferred choice among mobile payment solution providers by 2016.
Real-time
authentication Affordable biometrics
Secure mobile
payments
Key Benefits from Implementation
Short Term (1-2 Years)
Medium Term (3-4 years)
Long Term (>5 years)
Market Opportunity
High High
Our Thoughts
Medium
• Eyeprint ID is a software-only optical biometric solution. It leverages a
patented biometric technology that uses proprietary machine learning
algorithms to identify users with respect to patterns of eye veins.
Additionally, the solution uses information from selfie photographs. It
also evaluates the micro features in the eye and its surroundings.
The technology has the capability to transform the eye prints into high
entropy encryption keys to facilitate secure biometric authentication.
The machine learning algorithms allow the solution to identify the
scleral vasculature as well as ocular and periocular micro-features,
which collectively are unique for every human being.
The solution has successfully obtained the Fast IDentity Online (FIDO)
certification which makes it seamlessly interoperable with other innovations.
Additionally, the solution ensures absolute security and reliability of user eye
prints from being stolen as each print is scrambled and encrypted locally on
device. Even if the device is lost or stolen, the prints cannot be abused.
Uniqul
Facial Recognition-based Digital Payment Solution Uniqul Oy, Finland
Why do we need Facial Recognition-based Digital Payment ? Most solutions enabling point-of-sale (POS) digital payment require additional hardware resources, such as cards, tags, smartphones, tablets, and laptops. This makes it essential for the user to carry some devices each time he or she plans to make digital payments.
In the POS digital payments space, most payment solutions focus on conveniently delivering speedy payments. However, security, which is a major concern in any financial transaction, has not been given equal importance, leading to frequent breaches.
The conventional POS digital payment solutions use cards or mobile-based technologies. These solutions are less secure as the chance of theft or abuse of cards or mobile devices exists, which leads to fraudulent payments.
Which solution can help??
Uniqul is an innovative POS digital payment solution that
leverages facial recognition technology to enable secure
payments without the need for any additional hardware
resources.
Key
Technology
Capabilities
Uniqul’s solution, by virtue of its unique facial recognition technology and cloud-based encrypted payment processing, delivers freedom to the user to make secure, fast, and convenient payments by using just his/her face only. The solution is expected to gain rapid popularity in the world of cashless, cardless, touchless payments and secure digital payments by 2016.
Faster payments High accuracy Cashless, cardless,
touchless payments
Key Benefits from Implementation
Short Term (1-2 Years)
Medium Term (3-4 years)
Long Term (>5 years)
Market Opportunity
High High
Our Thoughts
Medium
Uniqul focuses on leveraging biometrics for authentication to authenticate
and enable payment. It uses highly efficient proprietary facial recognition
technology, coupled with proprietary algorithms. The facial recognition
algorithms, based on machine learning, are even capable of distinguishing
between identical twins in real time.
The solution is capable of completing a transaction in less than 5
seconds, in contrast to competing solutions, which usually require more
than 15 seconds to carry out the payment transaction. Additionally, the
military-grade facial-recognition algorithms are efficient enough to
identify users even from a distance, ensuring superfast transactions.
Uniqul’s POS digital payment solution leverages efficient proprietary
encryption techniques developed by vastly experienced in-house security-
technology developers to maintain customers’ financial details, which adds to
the solution’s security aspects. This enhances the reliability, as customers
confidential financial information, linked to the Unique account, stays safe.
D881-TV 13
Strategic Perspectives
14 D881-TV
Key Industry Initiatives
Multi-national banks like Standard Bank, Barclays and Australian Bank ANZ are testing one of the most
advanced artificial intelligence machines–IBM’s Watson–to provide services such as money transfers,
handling customer queries, customer behavior understanding and so on.
The Bank of Tokyo-Mitsubishi has recently employed Nao (a programmable 58cm mini-robot) to
perform reception duties for visitors. The multi-lingual robot deals with requests mainly from foreigners
and offers prerecorded responses for their requests. This robot has been implemented mainly to
improve convenience and increase engagement with customers.
UBS AG, the Switzerland-based financial service company, is working in collaboration with the
Singapore-based pattern detection technology developer Sqreem Technologies Pte. Ltd., to develop a
system that can deliver personalized investment advice to the key clients of the bank.
PayPal, the digital payment handling platform is using deep learning and artificial intelligence
approaches to track its customers activities online. AI helps to improve the cyber security capability of
the platform and enable better fraud detection.
15 D881-TV
Key Patents-World
No. Patent No. Publication Date Title Assignee
1 WO2015036642A1 03-19-2015 Mobile payment system and method based
on a single use token
Pomo Posibilidades S.A.
The invention relates to a mobile payment system and method, said system comprising: a mobile device (4) having an application for generating
tokens according to an item of temporal data that determines the expiration date of the token, a user password and a secret number stored in the
mobile device; and a point-of-sale terminal (5) of a business (1), for receiving the token, user identification data and the amount of the purchase,
and for sending (108) said information to a server (8). The server (8): accesses a user database (6) to validate the token and retrieve bank
information to carry out the payment; accesses a business database (7) to retrieve bank information in order to credit the business (1); and
sends the payment order to a payment gateway (9).
2 WO2008075151A2 06-26-2008 Transaction system and method Fundamo Proprietary Ltd
Rensburg Johannes Janse
Van, Cornilius Johannes
Badenhorst
A transaction system and method is provided in which a plurality of participating system members each has access to a communications device
(2, 3, 4, 5) so as to operatively communicate via an associated network with a computerized server (1 ) in order to instruct the initiation or
conduct of a transaction, typically a financial transaction, by operation of the computerized server consequent on data inputted by a particular
system member. The system includes at least one data base in which there is retained data relating to at least some possible or previous
transactions or both that may be conducted by the particular system member.; Selection means are provided for selecting one of said possible or
previous transactions that best represents data inputted in respect of any particular target transaction on the basis of artificial intelligence such
that data inputted in different ways or with different degrees of accuracy can result in the same target transaction being selected by the selection
means. The selected transaction is communicated to the particular system member whose confirmation is required of the correctness or
otherwise of the selected target transaction.
16 D881-TV
Key Patents–United States
No. Patent No. Publication Date Title Assignee
1 US20100191634A1 07-29-2010 Financial transaction monitoring Bank of America Corp.
Embodiments of the present invention provide systems and methods for monitoring financial transactions. For example, in one embodiment a
system includes a communication interface configured to receive information about each transaction of a plurality of transactions. The system
includes a memory device having a plurality of keywords and an artificial intelligence application stored therein, the plurality of keywords being
associated with a plurality of entities whose transactions are to be specially handled. The system further includes a processor configured to
identify a first group of transactions from the plurality of transactions where the information about each transaction of the first group of
transactions includes at least one of the plurality of keywords. The processor is further configured to then use the artificial intelligence application
to determine that one or more transactions in the first group of transactions are associated with one or more of the plurality of entities.
2 US7319992B2 01-15-2008 Method and apparatus for delivering a virtual reality
environment
Mission Corp.
Described is a method and apparatus for generating a customized dynamic virtual reality environment. The dynamic virtual reality environment
communicates with a participant via a virtual personal assistant utilizing an input/output arrangement. The virtual personal assistant engages the
participant in a natural language conversation to obtain the participant's preferences and personal information. The virtual personal assistant
utilizes an artificial intelligence engine to recognize a plurality of natural languages. Information obtained from the conversation may be translated
into a request for information, services or products. The virtual personal assistant may retrieve any of these from a plurality of remote servers via
a communications network and present the data to the participant. Information obtained from the conversation may be used to evolve both the
virtual reality environment and the virtual personal assistant. Both are continuously learning and adapting to the participant and become more
personalize following every use.
17 D881-TV
Industry Contacts
Ruslan Pisarenko, CEO & CTO , UNIQUL Oy,
Pasilanraitio 9, Helsinki, 00240, Finland.
Phone: +358-45-3144033
E-mail: [email protected]
URL: http://uniqul.com
Jack Kokko CEO, Alphasense,
One Sansome Street, Suite 3500 San Francisco,
CA 94104
Phone: 415-738-8090
E-mail: [email protected]
URL: https://www.alpha-sense.com
Douglas Clark Merill CEO, ZestFinance,
6636 Hollywood Blvd, Los Angeles, CA 90028
Phone: 323-450-3000
E-mail: [email protected]
URL: http://www.zestfinance.com/
Dmitry Aksenov, Founder & CEO, FinGenius
Limited,
1 Canada Square, London, UK
Phone: +44-20-7666-3202
E-mail: [email protected]
URL: www.fingenius.com
Tinna Hung, Director of Marketing, EyeVerify Inc.,
1712 Main Street, 5th Floor, Kansas City, MO 64108
Phone: +1-913-200-2344
E-mail: [email protected]
URL: www.eyeverify.com
David Buehlmann, Business Development,
Quotip,
Hagenholzstrasse 83b 8050 Zurich, Switzerland
Phone: +41-44-586-30-60
E-mail: [email protected],
URL: http://quotip.com/
Jeffrey Fenton , Marketing Manager, Nymi Inc.,
82 Peter St #500, Toronto, ON M5V 2G5, Canada
Phone: +1-416-977-3042
E-mail: [email protected]
URL: https://nymi.com/
Adam Gibson CEO, Skymind,
44 Tehama St, San Francisco, CA, 94105.
Phone: +1-406-668-1184
E-mail: [email protected]
URL: http://www.skymind.io