Monday 24 December 2018

#DialDforData: YES BANK’s Data Science Initiative Collaborates with 200 Data scientists to create 20+ data models in just 100 days.

Yes Bank Data Science DataThon IIT

Over the years, data has been an analytical tool to record and gather information from our surroundings to optimise our lives. The millennials would recall how we as society shifted from being predominantly ‘analog’ to ‘digital’ in just a few years. Today, thanks to technologies like the cloud and the algorithm-based infrastructure, data evangelists are talking about storing and analysing thousands of terabytes of data within a matter of minutes. This exponential growth of data is referred to as Big Data.

Big Data is our present and our future. In this age of information, data will fundamentally change the way businesses compete and operate. The analysis of this data could help businesses in making key management decisions which drive scalable transformation. Data scientists funnel vital data from terabytes of unstructured information to understand consumer buying patterns, likes and needs, and create scalable models which reduce systemic bottlenecks.

If data is a new oil then analysis is the refinery. The Internet of Things, Machine Learning, Predictive Analytics, Hadoop etc. are leading industrial trends which are shaping the data-driven economy.

Data Analytics: the next frontier.

The impact of data analytics will be beyond one sector, be it manufacturing, healthcare or finance. For instance, data science has today become a vital part of sports management industry. Each and every player of Indian Cricket Team is analysed on his current and past performance to predict behavioural patterns in an effort to rectify human error. BFSI firms are one of early pioneers to adapt data analytics.

With data science and analytics gaining importance across sectors, YES BANK reached out to the global developers, coders and data science community to work on Yes Bank’s data stacks. Datathon, an initiative of YES BANK is India’s first bank-led Datathon with a mantra of decode-derive-develop. Launched in September 2018, Yes Datathon has witnessed participation of over 6000 plus data scientists and engineers both from academia and corporate background. In a competitive selection, top 15 teams qualified for the Datathon Finale will be given 60 days to create working data models/prototypes which will be trained, tested and deployed by the Yes Bank.

The top teams include not only students from top technology institutes like IIT Bombay, IIT Madras, IIT Kharagpur and ISI Kolkata but also 150+ professionals from organizations like IBM, Walmart Labs, Oracle, Amazon Development Centre, TCS, Accenture and Infosys among others, who are taking on the challenge beyond their professional duties. A student team from University of Moratuwa, Sri Lanka presented their model at Yes Datathon finale held in Bengaluru.

Teams participating in Yes Datathon presented innovative models which were previously not thought-off. For instance, Team Data Pirates created an alternative method to credit score customers pooling in LinkedIn and external APIs. Team Greenity has developed an ML algorithm which analyses credit card history transactions to service customer better and predicting new target customers for YES BANK credit card.

Moving from buzz to biz

Artificial Intelligence has moved from buzz to biz. YES BANK has deployed AI based chatbot named Yes Robot to disseminate information about loan offerings to prospective customers. It currently helps users with instant 20+ banking services and 2,000+ banking queries. Next-gen technologies such as artificial intelligence, machine learning, natural language processing and bots enables YES BANK to serve their customers and clients with greater depth, sophistication and efficiency.

Yes Datathon is a part of a long-term strategy of Yes Bank of ‘becoming a technology company in the banking business’. Data scientists and engineers would have an experience of a lifetime handling 600 TB of anonymised data. Datathon provides a rare opportunity to build algorithms and data models on Terabytes of ‘real data’ in a deployment-ready environment. The collaboration between academia and corporate would deepen practical and technical know-how of future technology leaders and widen the data science ecosystem.

- Chaitanya Kulkarni.

1 comment:

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