Knowledge Forum Session on Big Data & Analytics for Financial services
Details
Big data & Analytics is about getting right data in right format to the right user in the right time at the right cost with ultimate objective of growing money.
Financial services generates volumes of data with large velocity and veracity – satisfies all the 3 V’s which forms foundation of Big Data. Once large data is available, obviously to use the data meaningfully Data Analytics is required. At an executive level, data analytics helps in solving problems for fraud detection, competitive pricing, Risk Analysis, customer segmentation and building data insights to design providing products for customer. The data insight gives a good a good overview of the system, nature of work and helps to trigger innovative ideas for proactive problem solving.
Various statistical techniques are used to analyse the data and build data model. The techniques are Multiple regression, Logistics regression, Classification And Regression Tree (CART), Neural networks, Machine learning algorithms are typically use to build model that will help in decision making.
The session provides overview of Analytics, techniques that can be used for finance vertical, methodology (CRISP) used for Analytics project and 2 use cases – stock analysis & Customer segmentation.
Who Should Attend
Anyone who is interested in knowing how Analytics / Analytical techniques that can be applied in Financial services.
Speaker Profile
Ms. Anjali Mogre is working in Atos – Analytics Practice. She is mainly involved in Ticket analytics for various application maintenance projects. For finance domain, she has developed a few use cases that can be tried on data sets available with banks / stock market.
Anjali has Masters degree in Statistics and Certificate course in Data Science from Atos University. She also has certifications like PMI, Six Sigma, CSQA, CSPA etc.
Venue
CSI Club House, Floral Deck Plaza, MIDC, Near Sunrise Tower, Andheri East, Mumbai – 400093
This is a free event but everyone is expected to be on time
Knowledge Forum Session on Big Data & Analytics for Financial services