Automated Underwriting – What Does it Mean for the Future of Insurance?
According to data from Juniper Research, the global value of insurance premiums underwritten by artificial intelligence reached $1.3 billion in 2019. With predictions that this will grow to over $20 billion by 2025.
Recognising the potential benefits of AI and automation, the insurtech sector is rapidly advancing to meet the industry’s desire for better solutions. Developing advanced machine learning to work alongside underwriters, delivering more accurate, tailored policies.
So, what does automated underwriting look like? And how will the prospect of automated underwriting impact the future of insurance?
What is Automated Underwriting?
Automated underwriting, also known as Augmented Automated Underwriting (AAU) is a system delivering computer generated decisions.
Historically, the underwriting process has been and continues to be largely manual. With an automated system, an algorithm would extract information from the insurance application and apply machine learning and available data analysis to make a decision.
Automated underwriting algorithms can gather and assess data from both internal and external sources, including loss runs and claim history, to produce precise risk assessments and accurate recommendations for potential submissions and renewals. Decisions would occasionally be subject to manual review for quality assurance purposes.
Challenges Facing the Insurance Industry
Increased competition, changing data regulations and lower investment returns are all challenges faced by the industry in 2020. Companies like Amazon could soon start offering tailored insurance solutions to their customers. Their wealth of customer data puts them in a prime position to deliver the types of policies and service that appeals to today’s customer.
To maintain a competitive edge, firms must improve customer satisfaction, increase profits and pursue growth. While simultaneously cutting down on operational costs and improving accuracy in claims underwriting.
The insurance industry still relies heavily on manual work. Not to mention working with outdated systems and processes and inefficient legacy applications. Data processing is labour intensive, with vast amounts of data in multiple formats. Requiring more and more time and resources to manage and analyse effectively.
Uses & Advantages
One of the biggest pressures for insurance firms is improving their customer experience. By automating elements of underwriting, companies can streamline the client onboarding process. Instead of taking days or even weeks to reach a decision, a policy quote can be provided in minutes. Thus improving customer satisfaction and, hopefully, retention.
As well as increased customer satisfaction, the automation of menial, resource intensive or repetitive tasks frees up considerable time and resources for innovation and development. Products can be scaled and expanded into new markets. Firms can better understand and anticipate emerging risks and explore more lucrative opportunities for growth. Allowing greater productivity and enhanced efficiency throughout the industry. Such systems are immensely scalable and can integrate with existing interfaces, saving set up time.
In a process that relies so heavily on manual processing, accuracy is hard to guarantee. With manual hand offs, paperwork and data analysis, some human error is unavoidable. A paperless, automated system would help ensure greater accuracy and also reduce operational costs.
Underwriters deal with great swathes of data. An automated processing system can group data in ways that make it easier to spot patterns that aren’t immediately obvious. Making the underwriting decision making process more precise.
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Personalising the Insurance Industry
Modern insurance policies need to be tailored to each customer. The data processing potential of automated systems offers unrivalled opportunities for segregating customers by their behaviours, choices and other metrics. Allowing insurers to design better, more personalised policies and pricing strategies for insurance clients. This makes coverage more affordable, as well as making customers feel valued.
Predictive analytics used in automated underwriting takes some of the presumption out of the process. Vast datasets can be analysed, with algorithms able to take into account nuances and complexities, resulting in more meticulous risk assessments and policies that fit the customer.
How Will it Affect Jobs in the Industry?
In a 2017 report by McKinsey Global, it was calculated that by 2025, up to a quarter of the task force in both the insurance and finance industries may be consolidated or replaced by automation. These will mostly be the operational and administrative tasks that are repetitive and resource intensive.
Other reports have suggested that there will be new jobs created for marketing and sales support as well as analytics teams. The key for firms will be finding workers with more advanced software knowledge and analytical skills.
Reinventing the Wheel
By no means do experts suggest that automation will completely overhaul the systems as we know them. Instead, they put forth that new technologies such as automated underwriting can help businesses get the most out of their existing and emerging data and processes.
Not all processes need to be automated. Nor should they be. Only in the case that it will offer significant long term benefit or savings, should automation replace existing processes. The risk of over automation is not to be underestimated.
Many suggest a more hybrid approach. Such a process would assess each submission or renewal, using machine learning algorithms and predictive models to evaluate and price it accordingly. A rule based approach. The decision making itself would remain with manual underwriters, who set the rules for the system to adhere to.
Automation is helping companies meet growing and changing demands of their industry in 2020 and beyond. For the global insurance industry it promises $2.3 billion in cost savings over the coming years. In insurance underwriting, AAU can help shorten processing times, making systems more responsive and customer centric, and enhancing the way we manage and calculate risk. Ultimately, it can help firms deliver better solutions for their clients.
Automation isn’t going anywhere. For most sectors, it’s a choice between evolving or getting left behind.
So, when it comes to insurance, is it worth the risk?