Subscribe to our Blog
- Data platforms can transform how insurers do business. Especially when augmented by advanced technologies, such as artificial intelligence (AI), machine learning, blockchain and advanced analytics.
- If insurers can master the art and science of data management they can generate a lot more value from their assets. They’ll also be able to increase returns on their investments in technology and expand their ability to use AI effectively.
- Underwriting leadership at a global insurer saw how automating the intake and classification of unstructured information via slips and schedules would pay off in many ways.
- By improving the flow of data, the lifeblood of the industry, insurers can rejuvenate the health of the entire business.
Data is the lifeblood of the insurance business. Financial services executives recognize the importance of unified data in managing risk and guiding strategy. However, only 38% of them are confident in their ability to make real-time, data-informed decisions.
Four out of ten financial services executives say that their data is siloed. Nearly two out of three executives (65%) say they need technology to better integrate data between disparate systems. In other words, insurers are not capitalising on the full potential of their data.
Indeed, insurers have many opportunities to mine their data for greater business value. The computing firepower, sophisticated toolsets and scalable platforms necessary to process and analyse enormous data volumes are commonly available.
Data platforms can transform how insurers do business. Especially when augmented by advanced technologies, such as artificial intelligence (AI), machine learning, blockchain and advanced analytics. However, the payoff from investing in these technologies hinges on solving the insurance industry’s fundamental data ingestion problem.
Mastering the art of data ingestion
Capturing unstructured data (e.g., content in emails and PDF proposals) requires onerous and time-consuming manual labour. That makes it harder and slower to integrate this data into processes that AI can automate and streamline. Beyond being inefficient, these processes make it more challenging to get the insights business leaders need to make informed decisions.
If insurers can master the art and science of data management they can generate a lot more value from their assets. They’ll also be able to increase returns on their investments in technology and expand their ability to use AI effectively. Moreover, they can accelerate and scale their digital transformation programs more broadly across the business.
Digital transformation requires a foundation of clean data on which insurers can unleash the power of data science and technology. In other words, smarter data ingestion is the first step in the journey of a 300-year-old industry becoming data-driven.
Consider how higher-quality data and fully transformed underwriting workflows can instil real-time decision making and risk selection much earlier in the trading lifecycle. By digitising previous contracts and proposals and integrating real-time feeds of relevant third-party data, skilled underwriters can apply their expertise to fuller and richer data sets much more quickly than before.
Exceptions are automatically routed to the right person for review in the step of the workflow. And no senior underwriters, actuaries or analysts are forced to do their own data entry. The risk selection process gets both shorter and more intelligent.
From today’s unstructured data to tomorrow’s high-value insights
This isn’t merely a futuristic concept. Leading carriers are already making it happen today. By taking advantage of technology like AI, carriers can move their attention away from basic tasks toward increasing their capacity, focusing on bigger volumes of transactions and other analytical activities that add more value.
Traditionally, carriers have committed resources to rekey the data received in paper and other analogue formats, which is a time-consuming and expensive workaround. It also increases the risk of manual error. But increasingly, underwriting leadership is noticing how automating the intake and classification of unstructured information via slips and schedules would pay off in many ways.
For example, a re-engineered workflow could collapse pre-risk, post-bind, and endorsement processes. Specifically, the time from submission of data to actionable insights can be cut from days to mere minutes. But automation can also support real-time decision-making and give underwriters new insight into exposures. Furthermore, the foundation of higher-quality data sets the stage for increased rigour in risk management, simplified reinsurance processes and enhanced claims administration.
Thus, the vision of straight-through processing in underwriting does not have to remain a pipe dream; it can be achieved. Intelligent automation can act as a starting point for broad-based transformation by scaling to deliver benefits across different lines of business and multiple geographic markets.