Capping off an exciting 24-hours of continuous solution development, EY, the leading global professional services organization, announced the winners of the second edition of the EY Hackathon in India. The first-of-its-kind Intelligent Automation hackathon saw over 100 developers, coders, UI/UX experts and chartered accountants teaming up to develop intelligent automation applications for critical businesses.
The hackathon challenged the teams to develop innovative digital prototypes to help simplify business functions such as tax, compliance and supply chain, among others, with the use of disruptive technologies such as Robotics Process Automation, Machine learning, Natural language Generation and Natural language Processing.
The participants worked in a 24-hour sprint-like challenge to build prototypes for a selection of unique use cases while benefitting from mentorship, technology stacks and cloud infrastructure from EY, and it’s Alliance Partners - Automation Anywhere, IBM and Microsoft. Two winning prototypes were awarded on the basis of their uniqueness, scalability and their applicability in business situations.
Farokh Balsara, Partner & Markets leader, EY India, said:
“Emerging digital technologies are at the forefront of the many transformational changes which we are witnessing in India today. With our series of EY Hackathons, we are attempting to bring together diverse talent communities to collaborate in solving some of the big present-day business issues that organisations face while undergoing this transformation.”
Team ‘Ignited Minds’ comprising of four engineering students from University School of Information & Communication Technology, developed a Contract Reader Tool involving a bot that performs contract completeness check, extraction of relevant clauses, performs applicability checks and subsequently shares the result report.
Team ‘Spurs’ which included one engineering student from University School of Information & Communication Technology and three EY professionals (Two Chartered Accountants and one engineer) won the tax use case challenge. The four-member team built a model that predicts the most likely rate of TDS applicable on a particular transaction by reading keywords from the invoice or purchase order and mapping them against the programmed rate master.