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

  • -
    Xiang Yu Sentiment Analysis in Bangalore 2017

    Daily Trade Signals using Sentiment Analysis and Stochastic Dominance for Downside Risk Control

    Xiang Yu, Business Development Techno Executive, and Gautam Mitra, CEO/Director, OptiRisk Systems/UCL, UK

    We have created an innovative and dynamic trading strategy for equities, with a particular focus on controlling downside risk. The mathematical concept behind the approach is called stochastic dominance, where investment decisions are based on distributions rather than moments. A major contribution of news sentiment is in the prediction of future distributions. Regression analysis on news sentiment and regime switching models are employed to digest market moods and account for changing market situations.

    Speakers:

    Gautam Mitra

    Xiang Yu Sentiment Analysis in Bangalore 2017

    Xiang Yu

  • -

    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

  • -
    Richard Peterson Sentiment Analysis in Bangalore 2017

    Approaches to Market Forecasting with Media Sentiment Data

    Richard Peterson, CEO, MarketPsych Data, USA

    Dr. Peterson will describe the unique characteristics of media sentiment data and approaches to financial price prediction with this data. The basics of media sentiment data, various modeling approaches, and their results (including live trading results) will be described in this talk. Viewers will gain an understanding of real-world modeling tips and techniques when dealing with noisy and inconsistent data such as media sentiment streams.

    Speakers:
    Richard Peterson Sentiment Analysis in Bangalore 2017

    Richard Peterson

  • -

    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

  • -

    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

  • -

    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

  • -

    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

  • -
    Anders Bally Sentiment Analysis in Bangalore 2017

    Social Listening & Financial Crowd-Intelligence

    Anders Bally, CEO and Founder, Sentifi

    In the early 90’s, the majority of financial market participants used news mainly from services like Bloomberg and Reuters to inform themselves. 20 years later, they still do. During the same period, our society went through a communication paradigm shift. Today more than 2 billion people walk around with mobile devices and communicate what they see and think on social media. These billions of voices, when structured, can generate insights which can help investors make better investment decisions. This presentation will touch on how Sentifi structures and delivers these insights, providing an information advantage for media platforms globally.

    Speakers:
    Anders Bally Sentiment Analysis in Bangalore 2017

    Anders Bally

  • -

    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

  • -

    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

  • -

    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

  • -

    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

  • -

    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

Speakers

Anders Bally Sentiment Analysis in Bangalore 2017

Anders Bally

Sentifi

Ashok Banerjee

IIM Calcutta

Sankarshan Basu

Indian Institute of Management, Bangalore (IIMB), India

Humberto Brandão

Data scientist

Nishant Chandra

Data Science Leader, AIG Science

G.Sathis Kumar

Great Lakes Institute of Management

Gautam Mitra

OptiRisk Systems

Prithwiraj Mukherjee

Indian Institute of Management, Bangalore

Richard Peterson Sentiment Analysis in Bangalore 2017

Richard Peterson

MarketPsych, USA

Shweta Ramesh

senior data scientist at Mad Street Den

Hari Sankaranarayanan

Director – Engineering, Amadeus Software Labs India Pvt Ltd

Krishma Singla

IBM Global Business Services

Dr. Vijay Srinivas Agneeswaran

Senior Director of Technology, SapientRazorfish

Xiang Yu Sentiment Analysis in Bangalore 2017

Xiang Yu

OptiRisk Systems

Knowledge Partners

Supporting Bodies

Media Partners

Organised by

 
unicom-logo
 

Tickets

4 people attend for the price of 3

  • Use the coupon code "UNI443" when booking.

Academics and Start ups
Price per day

  • Super Early Bird until 19 January 2018 - 7500/per day
  • Early Bird until 9 February 2018 - 9000/per day
  • Standard Price - 10000/per day

Industry
Price per day

  • Super Early Bird until 19 January 2018 - 12000/per day
  • Early Bird until 9 February 2018 - 13500/per day
  • Standard Price - 15000/per day

Venue

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