On December 5th, Hyperscience joined InsurTechNYC at Rise New York for a discussion on “Magic Formulas for Proof of Concepts.” The panel featured insights from Hyperscience’s Zander Steele, InsurTech Hartford Hub’s Dawn LeBlanc, and Livegenic’s Olek Shestakov, who shared their thoughts on PoCs, having an end goal for testing & adoption, and who makes the best champion within an insurance company. Read on for key takeaways and soundbites from the evening.
Insurtech is here to stay.
Global investment in insurtechs shows no signs of slowing down, with a record $3.26 billion invested in insurtechs during the first three quarters of 2019 alone. As technology continues to redefine how the insurance industry collects and leverages data to assess risk, underwrite policies and manage claims, both incumbents and start-ups are eager to set themselves up for success and develop best practices for working with each other.
Whatever you call them, Proof of Concepts are necessary.
There’s a lot of hype out there around about AI and automation, and it’s critical for an organization to see for itself how technology performs in a real-world environment. This is especially true in a traditionally conservative, risk-averse industry like insurance. A well-defined PoC can serve as a powerful internal awareness and education tool, showing various stakeholders exactly how a solution works and can add value at an organization. As Zander pointed out during the panel, however, at Hyperscience we call them TVEs or technical validation events, for a very specific reason: “We look at it as a validation, not as a concept. We ensure business and technical alignment upfront…we frame it as ‘if we check these seven boxes, is there a path to doing business together?‘”
Determine “do not pass go” criteria.
Operationalizing cutting-edge technology like AI can be challenging for organizations whose traditional IT infrastructure cannot scale to take advantage of new data sources and whose internal data is locked in silos that are incompatible with each other. Before you begin, clearly outline the “non-negotiables” for new tech adoption – whether it’s data security, deployment requirements or the ability to integrate with existing systems – and make sure the system checks all the boxes.
It’s less about “does the tech work” and more about long-term adoption and utilization.
According to Accenture, eighty-four percent of executives believe they must leverage AI to achieve growth objectives, yet seventy-six percent say that they struggle when it comes to scaling it across the business. A successful PoC requires an end goal for testing and adoption, so start by clearly defining the problem your organization is trying to solve. (One panelist suggested “breaking it into food groups” – whether it’s improving customer experience or eliminating manual workflows and bottlenecks – and “matching problem statements with solutions.”) Who are the business stakeholders and what are the specs/criteria for success? The most successful organizations incorporate different departments and functions in this process (e.g. operations, IT, HR and communications), asking how a solution needs to perform across the business to add value. As one panelist shared with start-ups in the room, do not be afraid to ask a carrier/insurer “what does a positive outcome look like for you?” This is the start of a partnership, and both sides should be equally committed to examining and understanding current workflows and building future-state business processes.
“Our agents are our products.”
At the end of the day, technology is only as good as the people and processes that support it. Engage employees and end users in the evaluation in the process, and pilot the technology with a small group whenever possible to work through issues and to avoid large-scale problems during a company roll-out. Encourage your workforce to take ownership in the system’s overall success by regularly asking for feedback, and be sure to have a plan in place for addressing any questions, concerns or issues.
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