Presented By O’Reilly and Cloudera
Make Data Work
21–22 May 2018: Training
22–24 May 2018: Tutorials & Conference
London, UK
Baiju Devani

Baiju Devani
Vice President, Enterprise Analytics, Aviva Canada

@baijudevani

Baiju Devani is vice president of enterprise analytics at Aviva Canada, where he leads a team of data scientists in application of analytics across all aspects of the insurance business, from core insurance activities, such as pricing and risk selection, to the development of cutting-edge robotic processes and the application of machine learning algorithms to areas such as claims processing and optimizing client acquisition. Previously, Baiju led the Analytics Group at IIROC, an entity overseeing Canadian equity and fixed-income markets, where he guided decision making in todays machine-driven (algorithmic) markets, embedded machine learning, and other algorithmic surveillance capabilities for market oversight and spearheaded IIROC’s primary research into market-structure issues and emerging technologies, such as blockchains; was part of the early team at fintech startup OANDA, which disrupted retail foreign-exchange markets, where he was responsible for building and leading the data engineering, data science, and growth teams; and founded Fstream, a SaaS provider for ingesting and analyzing high-frequency streaming data. Baiju holds both a BSc and MSc in computer science from Queen’s University. He developed his data chops working on large biological datasets as part of his graduate work and later at the Ontario Cancer Institute.

Sessions

12:0512:45 Wednesday, 23 May 2018
Data science and machine learning
Location: Capital Suite 10/11 Level: Intermediate
Secondary topics:  Financial Services
Baiju Devani (Aviva Canada), Étienne Chassé St-Laurent (Aviva Canada)
Risk-sharing pools allow insurers to get rid of risks they are forced to insure in highly regulated markets. Insurers thus cede both the risk and its premium. But are they ceding the right risk or simply giving up premium? Baiju Devani and Étienne Chassé St-Laurent share an applied machine learning approach that leverages an ensemble of models to gain a distinctive market advantage. Read more.