ABBYY’s solution marketing manager for insurance Eileen Potter discusses how automation and artificial intelligence can support better insurance processes and outcomes

You may have noticed a renewed drive towards technology innovation in the insurance industry, including insurers digitising more of their underwriting processes.

The hardening market has made underwriting efficiency and profitability a top priority for insurers. They can no longer rely on investment income to balance disappointing outcomes and are now looking for better, more innovative technologies.

A report by Deloitte, published in February 2021, suggested that underwriters are likely to begin working with new sources of data and technology to help them make more strategic decisions.

However, improving underwriting processes is not a ‘once and done’ project. There are many moving parts and plenty of new data, from both internal and external sources, which will continue to accumulate and will need to be carefully evaluated.

Data: the key to smart underwriting

Every industry, including insurance, is embracing artificial intelligence (AI) technologies to gain better insights, make more informed decisions and get ahead of their competition. It’s the core of any organisation’s digital transformation.

Automation technology can reprogramme how simple tasks are done, including within underwriting.

However, McKinsey and Company’s Insurance 2030: The impact of AI on the future of insurance report, published in March 2021, said that advanced AI will lead the industry from its current state of “detect and repair” to “predict and prevent” and that this pace of change will accelerate as brokers, consumers, insurers and others become more skilled at using advanced technologies to enhance decision-making, productivity and more.

Eileen Potter jpg

Eileen Potter

The biggest areas where AI can impact underwriting is with data and decisioning. Human error causes about 20% of the inaccuracies in data collected by agents or entered by policyholders, according to case studies compiled by Tiger Analtyics.

With new deep learning techniques available today, AI is increasingly able to imitate the learning, reasoning, problem solving and decision-making that humans do.

Yet, the amount of comprehensive data needed for underwriting is frustrating and time-consuming, especially for commercial lines and life insurance.

Having access to and using accurate data can improve underwriting processes and facilitate decision-making of technology investments, helping insurers estimate premiums and predict product demands.

Overcoming underwriting challenges requires process intelligence

Despite all the work that carriers have done to automate underwriting - and the amount of money poured into systems - there are still many underwriting processes that are inefficient, with little effective automation.

Some of the most common challenges include evolving agent and customer needs, competitive pressure and the legacy technology and siloed platforms that insurers have.

Most organisations have a hard time figuring out how to get started with their automation initiatives - they need a way to map out what the possibilities look like. This is where process intelligence can come in.

By making a digital twin of your processes, process intelligence can then be used to enhance operational efficiency, thereby improving customer experience and future business outcomes. Briefly put, it can help insurers find crucial issues within their processes where automation can be applied, or areas where workers may need more training.

Ultimately, process intelligence is a data driven way to steer process improvement and to understand the best way to facilitate that improvement.

Typically, insurers have been limited by traditional process mining and business information tools that can only take a snapshot of pristine process schema from past data using discrete sources and data types.

While that data is better than none, it doesn’t fully analyse process effectiveness or provide a focused view that reveals how each process is performing over time and who touches it.

With so many moving parts and new data constantly rolling in, process intelligence can help monitor and optimise underwriting processes on an ongoing basis, improving process health in the long run.

Transforming the insurance underwriting process demands not just the right technology, but the right intelligence about the processes serving it.

Today’s automation advancements come with a wealth of benefits for the insurance industry – from faster risk analysis and real-time assessments, to better data insights and predictions for classification and evaluation – helping insurers refine their process efficiency and putting them in line with, or even ahead of, market leaders.