What trends can we expect for the analytics industry?

30 Nov 2020

Steve Petrevski. Image: Aon

Aon’s Steve Petrevski discusses how Covid-19 has affected the analytics industry and what trends he expects to follow the pandemic.

As the senior vice-president and general manager of Aon’s data and analytics services, Steve Petrevski is an analytics expert who is responsible for driving growth strategy through new capabilities that leverage emerging technologies for digital businesses.

“A key goal is developing Aon’s data and analytic services platform, which brings together data, technology, expertise and solutions in a single place,” he said.

“These solutions include new data-driven products, digital distribution, marketplaces to match risk with capital and analytics-as-a-service capabilities.”

Petrevski has also recently worked on the integration of CoverWallet, a digital insurance platform for SMEs that Aon acquired at the start of this year to enhance the way it engages with small and medium-sized businesses.

‘Product people, data scientists, digital marketing experts, data engineers and DevOps will all be in demand’

Outside of his role at Aon, Petrevski also serves as an adviser to a number of start-ups in the areas of security, fraud and analytics.

Some of the companies he has worked with include Nanowear, which is developing textile-based nanosensor technology with applications in the cardiac, neurological and diabetic monitoring markets; Feedzai, a data science company that detects fraud in omnichannel commerce using artificial intelligence; and ForgePoint Capital, a venture capital firm focused on early-stage companies in cybersecurity.

With his experience and expert insight into the analytics industry, Petrevski was a speaker at the Analytics Summit 2020 on 24 November. He spoke to Siliconrepublic.com about how Covid-19 has affected the analytics industry and what trends he expects to follow the pandemic.

“Covid-19 has seen a huge shift in the way we work and the analytics industry, like everyone else, has been hugely affected,” he said. “Remote connectivity provides so many benefits, and while we are seeing an acceleration in the adoption of digital, we need to evolve and create new technology for ‘permanent’ remote work – especially to optimise the product development process.

“The global pandemic crisis is also triggering another digital pivot – one that will see the insurtech space attracting renewed venture capital and corporate venture capital investment flows. The resulting solutions will help resolve the many dislocations created by the Covid-19 outbreak and will ultimately reimagine how consumers and businesses interact with risk transfer solutions.”

Future trends in analytics

The insurance industry in particular has a long history of analysing risk via actuaries or data scientists. However, Petrevski said the exponential growth of data and complex IT environments is driving a demand for data engineers that can create and maintain the necessary data pipelines.

“Product people, data scientists, digital marketing experts, data engineers and DevOps will all be in demand and need to come together to deliver,” he said.

Looking further ahead, he added that technologies such as blockchain and quantum computing will need to mature further before they can be widely adopted.

“Applications such as enhanced integrity and insurance certification validation have proven successful. However, there has yet to be a broader adoption of technologies such as blockchain across the industry that would be required to unlock the associated benefits,” he said.

“Of course, we should be embracing the next generation of technology: microprocessors and data management infrastructure software as we map the path for where our industry’s talent must focus for future innovation.”

The pandemic has shone a light on the importance of cybersecurity, and Petrevski also cautioned about the growth of cyberattacks when it comes to data analytics. He said that organisations need to take a proactive approach in protecting data and systems through cybersecurity and fraud risk assessments.

“As a result, we are seeing the emergence of cybersecurity analytics with an increased role for machine learning in security, to monitor networks and identify changes in use patterns or traffic that might indicate a threat.”

Jenny Darmody is the editor of Silicon Republic