Analytics In Market

Analytics In Market

Program Details

Date & Time
7th July 2018 – 9:00 am to 5:00 pm

The Leela, Mumbai - 400059, India

Topics covered

  • Role of Business Intelligence in Decision Making

    Business Intelligence helps extract critical information from vast amount of (unstructured) data and transform them into actionable information. This leads to informed strategic decisions, improved operational efficiency and higher business productivity. This also helps in easier access of information that leads to quicker decisions generating competitive advantage. The data sources are, but not limited to, interactions with customers in the form of voice calls, chat interactions, emails etc.; and the online customer experience. Analyzing this leads to improving conversion rates and hence increases return on investment.

  • Use of AI in Finance & Business

    Artificial Intelligence (AI) and Machine Learning are being rapidly adopted for a range of applications in the financial services industry. Financial institutions and vendors are using AI and Machine Learning methods to assess credit quality, to price and market insurance contracts, and to automate client interaction. Institutions are optimizing scarce capital with AI and Machine Learning techniques, as well as back-testing models and analyzing the market impact of trading large positions. Hedge funds, broker-dealers, and other firms are using AI and Machine Learning to find signals for higher (and uncorrelated) returns and optimize trading execution. Both public and private sector institutions may use these technologies for regulatory compliance, surveillance, data quality assessment, and fraud detection

  • NLP for Strategic Decision Making

    With the huge growth of textual data, Natural Language Processing is one of the key technologies for decision making and better understanding of business needs. Most common examples are tailor made chat bots, social media analytics (Twitter, Facebook), automatic summarization, classification and clustering of text data as per specific business requirement. The session on NLP for business decision making will focus on this

  • Data Science for Finance

    There has been an explosion in the velocity, variety and volume of financial data. Social media activity, mobile interactions, server logs, real-time market feeds, customer service records, transaction details, information from existing databases - there’s no end to the flood. To make sense of these giant data sets, companies are increasingly turning to data scientists for answers. The activities include:

    • Capturing and Analyzing new sources of data, building predictive models and simulations of market events
    • Using technologies such as Hadoop, NoSQL and Storm to tap into non-traditional data sets (e.g., geolocation, sentiment data) and integrate them with more traditional numbers (e.g., trade data)
    • Capturing and Analyzing new sources of data, building predictive models and simulations of market events

  • Case Studies



Role of Business Intelligence in Decision Making
Data Science for Finance
Uses of AI in Finance & Business

Case Studies

Skymet Presentation on Weather Forecasting
AI Based Investment Portfolio
Business & Softech Solutions Raoson
Uses of AI in Finance & Business
Use of AI in Business & Finance


Possible Date

July 2019

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