With the ongoing development of our EiB Insurance Analytics solution, which provides automated premiums and claims management information (MI) for MGAs, Insurers and Brokers, we have recognised a trend in the challenges faced across the sector with regards to the issue of data quality.
With this in mind, a few months ago we commissioned a report exploring the impact of data quality in the insurance industry, the role of automation in addressing this issue, and the future of underwriting. Indeed, much of the recent rhetoric surrounding this topic, has shown that a significant proportion of underwriters admit to delivering inaccurate MI on the back of bad data quality.
A 2017 EMEA Insurance data analytics study by Deloitte, discovered that only 40% of respondents found their data quality to be sufficient for trusted insights to be generated, and for an equal proportion, their data was undefined and of very poor quality.
This report seeks to explore the role of the underwriter as the insurance industry undergoes a major digital transformation amidst the InsurTech revolution, and discusses the future long-term impacts and strategies that can be brought by embracing automation.
Several experts from across the InsurTech and insurance analytics space contributed their opinions to the report, include Robin Patterson, Performance Analytics Manager at Charles Taylor, Nick Pester, Head of Insurance & InsurTech at Capital Law LLP, and Stephen Goldstein, Founder of Daily Fintech.
