"Dramatic changes" reshaping claims space

"Dramatic changes" reshaping claims space | Insurance Business

"Dramatic changes" reshaping claims space

There’s no doubt technology is revolutionising the world of insurance, leading to improvements and advancements right across the board – but with new developments coming faster and more frequently than ever before, keeping up to date has become a daunting task.

However, for Sameer Oghanna (pictured) – head of automation, AI and analytics at Gallagher Bassett – that’s just part of his daily job. In fact, Oghanna is charged with driving automation, harnessing AI and embedding machine learning within the major third-party claims administrator.

According to Oghanna, there are several key areas in which technology is driving change within the claims space – and while they may bring challenges, they open up significant opportunity too.

“Dramatic changes are reshaping the insurance industry, largely driven by technology,” says Oghanna. “These changes provide opportunities for the insurance industry to become more customer-centric, improve pricing and create operational efficiencies.”

Of course, with so much changing and even more at stake, even the biggest players in the insurance value chain sometimes question where their focus should be.

According to Oghanna, one of the most common areas of application will be around virtual assistants or human-assisted AI, as organisations fight to keep up with rapidly changing customer expectations.

“By integrating more advanced automation into the communication channels we are able to respond to customers more efficiently and effectively,” says Oghanna, who adds that, as organisations embrace the power of machine learning, these virtual assistants will only continue to improve.

“A key benefit of utilising machine learning is that it can be effectively applied across unstructured, semi-structured and structured datasets,” says Oghanna. “This allows it to be used throughout the whole value chain. Insurers can therefore gain a deeper understanding of claims behaviour, risk, customers, and do so with greater predictive accuracy.”

Oghanna also says that speech and sentiment analysis has expanded in use as the technologies become more available and scalable at a lower price point.

“This trend will continue and give greater insight into what our customers are asking, how they are feeling and what we can do to improve our communication styles,” says Oghanna.

“Imagine a world where it is possible to match the personality of your claim consultants with the personality type of the customer. Machine learning is making this a reality.”

However, it’s not just AI that’s being used to improve customer outcomes – Oghanna says the industry is making better use of data too. Again, this trend is one that is set to continue.

“Data has always had a central role in the claims management process and today insurers have more access than ever before,” he says. “It’s collected from a wide range of sources, such as voice analytics, social media activity, wearables, telematics and connected sensors.”

While machines can be used to process this abundance of information and return analytical insights, it seems there is still some significant room for improvement across the board.

In fact, according to a 2018 Accenture study, the majority of companies in the insurance industry process only 10-15% of data they have access to, which is largely comprised of structured data housed in traditional databases.

“Therefore, a significant opportunity arises for organisations to unlock insights from their unstructured data (voice and sentiment analytics, medical text, clickstream) and leverage it throughout the insurance value chain,” says Oghanna.

“There are many potential applications of machine learning in claims management, ranging from the ability to better understand premium leakage and risk appetite, to expense management, litigation and fraud identification,” he continues.

“Augmented intelligence, more specifically intelligence automation (IA), is about using these technologies to support humans making decisions – ‘simple’ decisions are trusted to automation, ‘complex’ decisions become augmented.”

Finally, Oghanna says automating the claims process will be a key area of focus moving forward – largely because claims functions are often viewed as one of the most manual, labour-intensive parts of an insurance business.

“For example, among other tasks, robotic process automation and machine learning currently provides insurers with the capability to automate claim registration, liability determination, policy administration and invoicing,” says Oghanna.

“By automating the low-level administrative tasks, RPA has afforded employees additional scope to focus on improved customer service, complex tasks, and greater overall outcomes for our clients.”

The impact all three areas – automation, AI and machine learning – are set to have on the wider insurance space simply can’t be understated, says Oghanna.

“Over the coming years, as all industries gravitate towards the fourth industrial revolution, organisations need to embrace, refine and expand upon the AI reality or risk falling behind,” he says.