Background

Artificial Intelligence is deemed to be the main driver of the 4th Industrial Revolution. Investment in AI has grown at a phenomenal rate with companies investing $26-39bn in 2016. Adoption in 2017, however, remains low. As a result, this has spurred companies from every industry to seize the trend and innovate – from virtual assistants to cyber security to fraud detection and much more. The majority of C-level executives have identified and agree that AI will have an impact on their industry. However, only 20% of C-level executives admit they have already adopted AI technology in their businesses, according to research conducted by McKinsey. So, there is plenty of scope for change and improvement. The Finance industry is anticipated to lead the way in adoption of AI with a significant projected increase in spending over the next three years.

Until recently, practitioners have faithfully relied upon neo-classical models to measure performance, whether it’s in financial organisations or marketing corporations. AI is the new technology that offers an automated solution to these processes. It has the capability to replicate cognitive decisions made by humans and also remove behavioural bias adherent to humans.

Machine learning and sentiment analysis are specific techniques that are applied in AI. These techniques are maturing and rapidly proving their value within businesses. In order to process and understand the masses of data out there, machine learning and sentiment analysis have become essential methods that open the gateway to data analytics. To keep up with the ever-expanding datasets, it is only natural that the techniques and methods with which to analyse them must also improve and update.

This conference will help you to demystify the buzz around AI and differentiate the reality from the hype. Learn about how you can benefit from the unprecedented progress in AI technologies at this conference. Participants will be presented with real insights on how they can exploit these technological advances for themselves and their companies.

Attend this event and earn GARP/CPD credit hours.

UNICOM has registered this program with GARP for Continuing Professional Development (CPD) credits. Attending this program qualifies for 14 GARP CPD credit hours. If you are a Certified Financial Risk Manager (FRM®), please record this activity in your Credit Tracker.

Topics Covered Include:

  • Fundamentals and applications of machine learning and deep learning
  • Pattern classifiers, Natural Language Processing (NLP) and AI applied to data, text, and multi-media
  • Sentiment scores combined with neo-classical models of finance
  • Financial analytics underpinned by qualitative and quantitative methods
  • Predictive and normative analysis applied to finance
  • Behavioural and cognitive science
  • The future of AI and its impact on industries

Why participate?

  • Hear from leading subject experts from UK, US, Europe and India/Hong Kong
  • Programme includes the latest state-of-the-art research, practical applications and case studies
  • Expect technical and in-depth presentations and discussions; we like to stimulate your brain cells!
  • Excellent networking opportunities throughout the days with all participants, including presenters, investors and exhibitors.


Programme

  • 09:00 -

    Welcome

  • 09:30 -

    Plenary session 1: Deep Learning-Based Search and Recommendation Systems Using TensorFlow

    Dr. Vijay Srinivas Agneeswaran, Senior Director of Technology, SapientRazorfish

    Recommendation systems are all around us. Ecommerce companies like Amazon recommend goods that we are likely to buy based on our past behavior. Netflix suggests what videos we should watch. Pandora even builds personalized music streams, based on what we are likely to listen to. Almost every website has a recommendation system based on user browsing history, past purchases, past searches, and preferences.

    It turns out most existing recommendation systems are based on three paradigms: collaborative filtering (CF) and its variants, content-based recommendation engines, and hybrid recommendation engines that combine content-based and CF or exploit more information about users in content-based recommendation. This presentation gives a start-of-art view of building deep learning-based recommendation and learning-to-rank systems using TensorFlow, including model management and scaling.

    Speakers:

    Dr. Vijay Srinivas Agneeswaran

  • 10:30 -

    Coffee

  • 11:00 -
    Anders Bally Sentiment Analysis in Bangalore 2017

    Finding Alpha Signals with Artificial Intelligence + Influencer Analysis + Big Data

    Anders Bally, CEO and Founder, Sentifi

    This presentation is about how new AI methodologies like Deep Learning, the maturing Big Data Technologies and the fast emerging Information Sharing Culture can help investors to more efficiently discover, monitor and potentially predict Asset Valuation Drivers.

    Speakers:
    Anders Bally Sentiment Analysis in Bangalore 2017

    Anders Bally

  • 11:45 -

    Prediction of Distress using Text of Corporate Filings

    Ashok Banerjee, Departmental Head of Finance and Control, Indian Institute of Management, Calcutta (IIMC), India

    Using the qualitative information present in corporate annual reports of companies registered and operating in India, we have systematically evaluated the language and content of annual reports, particularly text and observed that the negative sentiments in the qualitative information starts increasing approx. 3-4 years before the year of credit default event and remains very high after the credit default event. The finding is based on a text-based analytical model that evaluates three sections of a corporate annual report- Directors Report, Audit Report and Notes to Accounts.

    Speakers:

    Ashok Banerjee

  • 12:30 -

    Lunch

  • 13:30 -

    Panel – AI & ML for FinTech Start-ups

    Chaired by: Professor Ashok Banerjee

    Panellists: V.R. Govindrajan and Debasish Chakraborty, Perfios; Rajeev Agarwal, Innoviti

  • 14:15 -

    Plenary session 2: Humanized Machines: Use cases

    Mihir Punjabi, Principal Solutions Architect, and Sunil Kumar, Senior Consultant, Capgemini

    Speakers:

    Mihir Punjabi

    Sunil Kumar

  • 14:45 -

    Tea

  • 15:15 -

    Artificial Intelligence – The journey in a nutshell and what lies ahead

    Krishma Singla, Managing Consultant - Data Science and Cognitive Computing, Watson Cognitive Solutions, IBM Global Business Services

    Through use case examples, Krishma sums up the journey of Artificial and Augmented Intelligence to date, with particular focus on finance. She describes new developments in fintech and other related areas that demonstrate how the finance industry is evolving with AI and other modern technologies

    Speakers:

    Krishma Singla

  • 16:15 -

    The Indian Financial System: Development and Challenges

    Sankarshan Basu, Professor in the Finance and Accounting Area at the Indian Institute of Management, Bangalore (IIMB), India

    Technology has significantly altered the way the world has known finance over the years; this presentation gives an overview of new developments that have brought both challenges and benefits to the complexities of the Indian financial system.

    Speakers:

    Sankarshan Basu

  • 16:45 -

    Summary and close

  • 09:00 -

    Welcome

  • 09:15 -
    Xiang Yu Sentiment Analysis in Bangalore 2017

    Enhanced Trading Strategy using Sentiment and Technical Indicators

    Xiang Yu, Chief Business Development Officer, and Gautam Mitra, CEO/Director, OptiRisk Systems/UCL, UK

    We compute daily trade schedules using a time series of historical equity price data and applying the powerful mathematical concept of Stochastic Dominance. In contrast to classical mean-variance method this approach improves the tail risk as well as the upside of the return. In our recent research we have introduced and combined market sentiment indicators and technical indicators to construct enhanced RSI and momentum filters. These filters restrict the choice of asset universe for trading. Consistent performance improvement achieved in back-testing vindicates our approach.

    Speakers:

    Gautam Mitra

    Xiang Yu Sentiment Analysis in Bangalore 2017

    Xiang Yu

  • 10:00 -

    Hierarchical Natural Language Representation Using Deep Learning

    Nishant Chandra, Data Science Leader, AIG Science

    Deep learning has created a revolution in the natural language processing domain and corporations are leveraging it in various ways. The technology barrier is significantly reduced with open source technologies that are easy to configure and use. Several generic open source tools are available in machine learning, including deep learning, which can be customized for natural language processing. This presentation will help the audience to go beyond generic NLP problem solving by leveraging deep learning, customizing it for their industry. Specifically, they’ll learn that:

    ♦ Sentiment doesn’t have to be positive, negative or neutral but it can be extracted from the conversation
    ♦ Summarization doesn’t have to be entire document but only certain context
    ♦ Text classification doesn’t have to be exactly text/phrase/spelling based but can also include variation of acronym and synonym
    ♦ NLP can be applied broadly, and complex use cases can be built through intelligent iteration on simple examples.

    Speakers:

    Nishant Chandra

  • 10:45 -

    Coffee

  • 11:15 -

    Machine Learning Applied to Distributed Ledgers for Predicting Digital Gold Prices

    P. Baba Gnanakumar, Financial Analytics

    The regulation on cryptocurrencies and surging price of Gold has pushed investors towards digital gold. This calls for a prolific blockchain to establish the trading platform of digital gold. This presentation uses machine learning algorithms to identify the distributed networks needed to build such a blockchain. Supervised learning algorithms are used to forecast Indian gold prices, incorporating various data sources and foreign currencies such as US Dollar and Euro.

    Speakers:

    Baba Gnanakumar

  • 12:00 -

    The Introduction of Humanoid Robots in The Banking Sector: an analysis of the customer acceptance using the technology acceptance model

    D. Divya Prabha, Associate Professor, KV Institute of Management and Information Studies

    The proliferation of robotics has tremendously benefitted numerous fields all over the world and the banking sector is no exception to this. Robotic technology has modified the pattern of banking services, opening a new avenue of self-service banking. Financial services have already started applying robotics. While it’s still early days for most banks with this technology, humanoid robots are employed in certain banks like City Union Bank, Canara Bank, etc, where they mainly serve as information kiosks and basic customer assistants. If this initiative proves successful, they are likely to be integrated with core banking systems in the future.

    The success of adoption of any new technology depends on the customer acceptance and use. This paper analyses the acceptance of humanoid robots in the banking sector by the customers using the attributes of Technology Acceptance Model (TAM) like perceived usefulness, perceived ease of use and perceived enjoyment.

    Speakers:

    D. Divya Prabha

  • 12:45 -

    Lunch

  • 13:45 -

    Panel: How AI & ML are impacting Markets – threats & opportunities

    Chaired by: Prithwiraj Mukherjee, IIMB

    Panellists: Evelyn Immanuel, Aindra Systems; Pradeepta Mishra, Lymbyc;Shweta Ramesh, Mad Street Den

  • 14:30 -
    Richard Peterson Sentiment Analysis in Bangalore 2017

    Plenary Session 3: Blowing Bubbles: Quantifying How News, Social Media, and Contagion Effects Drive Speculative Manias

    Richard Peterson, CEO, MarketPsych Data, USA

    In this talk Dr. Richard Peterson describes how media analytics are providing new insights into the origins and topping process of asset price bubbles. Examples from price bubbles including the China Composite, cryptocurrencies, housing, and many others will be explored. Recent mathematical models of bubble price action will be augmented with sentiment analysis. Attendees will leave with new models for identifying and taking advantage of speculative manias and panics.

    Speakers:
    Richard Peterson Sentiment Analysis in Bangalore 2017

    Richard Peterson

  • 15:15 -

    Tea

  • 15:45 -

    Why algorithmic trading in the real world is so different to academic experiments

    Humberto Brandão, Data scientist

    It is not difficult to find academic papers showing how to make money easily using algorithmic trading, which includes graphs, statistical tests, etc. However, in real markets, the majority of them cannot be replicated. In this presentation, I will discuss some reasons for this problem and try to explain how to improve validation processes before applying an algotrader in real stock exchanges.

    Speakers:

    Humberto Brandão

  • 16:30 -

    Sentiment Analysis to Optimize your Hedge Fund Strategy using Python

    Arunabha Majumdar, Senior Data Scientist, Eclerx

    A primer on analysing the mood of traders using tweets through Psychsignal and StockTwits and exploring a few back-testing capabilities. It is assumed that the audience has a preliminary knowledge of the common libraries in python and has familiarity to basic statistical concepts. The presentation introduces the Psychsignal tool and creates a dummy Stock universe. It also touches upon on how pairs trading works with a very simple implementation of the Basic Pairs trading algorithm.

    Speakers:

    Arunabha Majumdar

  • 17:00 -

    Summary and close

  • 09:00 -

    Welcome

  • 09:30 -

    Plenary session 1: Deep Learning-Based Search and Recommendation Systems Using TensorFlow

    Dr. Vijay Srinivas Agneeswaran, Senior Director of Technology, SapientRazorfish

    Recommendation systems are all around us. Ecommerce companies like Amazon recommend goods that we are likely to buy based on our past behavior. Netflix suggests what videos we should watch. Pandora even builds personalized music streams, based on what we are likely to listen to. Almost every website has a recommendation system based on user browsing history, past purchases, past searches, and preferences.

    It turns out most existing recommendation systems are based on three paradigms: collaborative filtering (CF) and its variants, content-based recommendation engines, and hybrid recommendation engines that combine content-based and CF or exploit more information about users in content-based recommendation. This presentation gives a start-of-art view of building deep learning-based recommendation and learning-to-rank systems using TensorFlow, including model management and scaling.

    Speakers:

    Dr. Vijay Srinivas Agneeswaran

  • 10:30 -

    Coffee

  • 11:00 -

    Humanized Machines

    Mihir Punjabi, Principal Solutions Architect, and Sunil Kumar, Senior Consultant, Capgemini

    The most natural form of communication via which Humans interact are Vision, Voice and Text. These communication mechanisms can be extended to machines to achieve a “Natural Digital Experience”.

    Imagine machines being able to respond to your voice, body language, etc. just like a human would respond. This is already being made possible with Digital Assistants like Alexa, Siri, etc. and Deep Learning algorithms.

    The session will cover –

    ♦ Natural Digital Experience (NDE)
    ♦ Few use cases of NDE
    ♦ Architecture and Demo of NDE POC
    ♦ NDE frameworks and tools
    ♦ Complete autonomy – can machines collaborate directly with other machines?

    The session will start with Human Machine Interface (HMI) experience and end with thoughts on autonomous M2M experience – is the future about machines autonomously collaborating with each other directly just like humans? [H2M – M2M]

    Speakers:

    Mihir Punjabi

    Sunil Kumar

  • 11:45 -

    Chatbot – Contextual journey into the travel planning

    Hari Sankaranarayanan, Director – Engineering, Amadeus Software Labs India Pvt Ltd.

    Travel planning is always interesting and exciting yet matching everyone taste, preferences and approach for travel planning is a challenge. We have lot of chatbots in the marketplace now and the question is how contextual they are. Can they understand the traveler, location, interest and converse naturally like a real travel agents. In this session we will discuss the contextual issues that can make the bot more interesting or uninteresting. We will review some of the existing airline bots and how they use NLP, disambiguation and ontology of travel domain to the full use. We will discuss the trends, advancements and gaps on travel domain chatbots.

    Speakers:

    Hari Sankaranarayanan

  • 12:30 -

    Lunch

  • 13:30 -

    Panel – AI & ML for FinTech Start-ups

    Chaired by: Professor Ashok Banerjee

    Panellists: V.R. Govindrajan and Debasish Chakraborty, Perfios; Rajeev Agarwal, Innoviti

  • 14:15 -

    Plenary session 2: Humanized Machines: Use cases

    Mihir Punjabi, Principal Solutions Architect, and Sunil Kumar, Senior Consultant, Capgemini

  • 14:45 -

    Tea

  • 15:15 -

    Transforming Healthcare in India with Analytics, Machine Learning and Artificial Intelligence

    Vikram Venkateswaran, Founder and Chief Editor of Healthcare India

    The backbone of this healthcare transformation is patient data. Hospitals across India have had access to patient data for a while. What has changed today is the availability of tools and powerful computing that is helping hospitals make most of the data. In this session Dr Vikram Venkateswaran looks at case studies on how leading hospitals in India are now using advanced technologies like Analytics, Machine Learning and Artificial Intelligence to improve care outcomes.

    Speakers:

    Vikram Venkateswaran

  • 15:45 -

    Personalising Communications for the Complex Consumer

    Vedha Ponnappan, Doctoral Student, Indian Institute of Management Bangalore

    Engaging with consumers on a one-to-one basis is always a challenge to the marketer. Recent advances in technology and data handling ability enable marketers to “personalize” the communications, recommendations and offers based on the past and current buying behaviour of consumers. This research talk focuses on targeting when the consumer is a household with multiple underlying demands.

    Speakers:

    Vedha Ponnappan

  • 16:15 -

    The Future of AI and its Impact on Industries

    Karma Bhutia, Founder & CEO of iShippo.com

    The rise of Artificial Intelligence could lead to an increase in unemployment rates. Automation and Robots will have taken over most jobs in future leaving humanity facing its 'biggest challenge ever' to find meaning in life when work will no longer necessary. Humanity’s march into an automation/robot-dependent society is alarming.

    To answer that question; we have to delve into the evolution of the Industrial Era, the dawn of Industry 4.0 & the hyper automated mass production.

    Speakers:

    Karma Bhutia

  • 16:45 -

    Summary and close

  • 09:00 -

    Welcome

  • 09:15 -

    From Problems to Products

    Harinarayanan KK, Computer Vision Researcher, and Evelyn Immanuel, Project Manager, Aindra Systems

    Challenges involved in converting research problems and solutions to consumer products for medical diagnosis. This presentation covers a use case on our Point of Care Device 'CervAstra' for the screening of Cervical Cancer.

    Speakers:

    Evelyn Immanuel

    Harinarayanan KK

  • 10:00 -

    Controlled Experiments and Impact Measurement - A few practical approaches

    Shweta Ramesh, senior data scientist at Mad Street Den

    With the online retail industry constantly evolving to meet customer needs, being able to run controlled experiments quickly has become imperative. While the standard A/B tests are still the preferred way, alternatives that are faster and practical for industry use are being explored. These include multi-armed bandit based A/B tests, impact measurement through structured equation modeling, using synthetic controls for experiments, etc. In this talk, we compare and evaluate bandit based A/B tests against standard A/B tests with results from real-world simulations; and discuss models to measure impact when it is not feasible to hold out a control group.

    Speakers:

    Shweta Ramesh

  • 10:45 -

    Coffee

  • 11:15 -

    Application of NLP and ML in Building AI Solutions

    Pradeepta Mishra, Lead, Data Science and Machine Learning Practice, Lymbyc

    Many organizations now recognize the power of artificial intelligence in understanding their data and information, and hence how artificial intelligence can help them re-design their business strategy. There is a constant need for upgrading existing applications and/OR developing new applications that understands the end users’ activities better and in an efficient manner, so that business strategy can be formed to make the user experience better, make profitable business moves etc. Natural language understanding is a must in building AI solutions, therefore machine learning, deep learning are constantly evolving as a framework for understanding natural language. In this talk, Pradeepta shares various designs/frameworks that can sit on top of applications, using deep learning, and machine learning and natural language processing.

    Speakers:

    Pradeepta Mishra

  • 12:00 -

    Seeding Criteria on Social Networks

    Prithwiraj Mukherjee, Indian Institute of Management, Bangalore

    Seeding, or providing free samples of a product, is a popular way of speeding up sales by marketers. Seeding also has its limitations, as a free sample could be expensive, as well as represent a lost sale. Previous work on seeding of markets with new products has typically focused on seeding at time t=0, based on assumed knowledge of diffusion model parameters. We build on this work to explore the possibility of seeding later on, either because the diffusion parameters may not be properly known, or to investigate if multiple seeds could be more beneficial than a single seed. We also present results from agent-based simulations to identify whom to target on social networks.

    Speakers:

    Prithwiraj Mukherjee

  • 12:45 -

    Lunch

  • 13:45 -

    Panel: How AI & ML are impacting Markets – threats & opportunities

    Chaired by: Prithwiraj Mukherjee, IIMB

    Panellists: Evelyn Immanuel, Aindra Systems; Pradeepta Mishra, Lymbyc; Shweta Ramesh, Mad Street Den

  • 14:30 -
    Richard Peterson Sentiment Analysis in Bangalore 2017

    Plenary Session 3: Blowing Bubbles: Quantifying How News, Social Media, and Contagion Effects Drive Speculative Manias

    Richard Peterson, CEO, MarketPsych Data, USA

    In this talk Dr. Richard Peterson describes how media analytics are providing new insights into the origins and topping process of asset price bubbles. Examples from price bubbles including the China Composite, cryptocurrencies, housing, and many others will be explored. Recent mathematical models of bubble price action will be augmented with sentiment analysis. Attendees will leave with new models for identifying and taking advantage of speculative manias and panics.

    Speakers:
    Richard Peterson Sentiment Analysis in Bangalore 2017

    Richard Peterson

  • 15:15 -

    Tea

  • 15:45 -

    Future of Evidence-based Public Policy in India: Promises and Perils

    Dr.G.Sathis Kumar, Great Lakes Institute of Management

    Use of Big Data and analytics for public policy is no longer a theoretical debate but is now in the early stages of a practical implementation. In a country like India, with its 1.3 billion people spawning enormous amounts of data every day, there is a unique opportunity to use Big Data Analytics to control the data behemoth and tame it for the country’s benefit. The presentation will investigate the deeper into various issues around the role of Big Data in Government schemes and projects like the Digital India, the UID Scheme (Aadhar), Electronic Transactions Aggregation and Analysis Layer (e-TALL) and the Smart Cities Mission.

    Speakers:

    G.Sathis Kumar

  • 16:30 -

    Consumers' Market and Convolution Neural Network

    Shabbir Tayabali, Senior Manager - Analytics, Oracle

    Convolutional Neural Networks (CNNs) are powerful models that achieve impressive results for image classification. This presentation aims to touch the fundamentals of the CNN. It further explains briefly the overall generic architecture of a CNN and its practical applications.

    The presenter aims to demonstrate a practical use case of CNN in the area of facial recognition.

    Speakers:

    Shabbir Tayabali

  • 17:00 -

    Summary and close

Speakers

Anders Bally Sentiment Analysis in Bangalore 2017

Anders Bally

Sentifi

Ashok Banerjee

IIM Calcutta

Sankarshan Basu

Indian Institute of Management, Bangalore (IIMB), India

Karma Bhutia

iShippo.com

Humberto Brandão

Federal University of Alfenas (Brazil)

Nishant Chandra

AIG Science

Baba Gnanakumar

School of Management, Kristu Jayanti College

Evelyn Immanuel

Aindra Systems

Harinarayanan KK

Aindra Systems

G.Sathis Kumar

Great Lakes Institute of Management

Sunil Kumar

Capgemini

Arunabha Majumdar

Eclerx

Pradeepta Mishra

Lymbyc

Gautam Mitra

OptiRisk Systems

Prithwiraj Mukherjee

Indian Institute of Management, Bangalore

Richard Peterson Sentiment Analysis in Bangalore 2017

Richard Peterson

MarketPsych, USA

Vedha Ponnappan

Indian Institute of Management Bangalore

D. Divya Prabha

KV Institute of Management and Information Studies

Mihir Punjabi

Capgemini

Shweta Ramesh

Mad Street Den

Hari Sankaranarayanan

Amadeus Software Labs India Pvt Ltd

Krishma Singla

IBM Global Business Services

Dr. Vijay Srinivas Agneeswaran

SapientRazorfish

Shabbir Tayabali

Oracle

Vikram Venkateswaran

Healthcare India

Xiang Yu Sentiment Analysis in Bangalore 2017

Xiang Yu

OptiRisk Systems

Knowledge Partners

Supporting Bodies

Media Partners

 

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Tickets

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  • Super Early Bird until 19 January 2018 - 7500+GST/per day
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Venue

  • IIM Bangalore, Bannerghatta Road, Bilekahalli, Bengaluru, Karnataka 560076
  • +44 (0) 1895 256 484
  • info@unicom.co.uk
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