By Gallagher Bassett — Sponsored content | 1 May 2019
  • Claims
  • Insurance Broking
  • General Insurance
  • Risk Management
Gallagher Bassett

As insurers continue to be challenged by rapidly changing customer expectations, many are looking towards utilising virtual assistants or human-assisted artificial intelligence (AI). 

By integrating more advanced automation into the communication channels we are able to respond to customers more efficiently and effectively. 

Gaining a deeper understanding of customers

As organisations embrace the power of Machine Learning (ML), the virtual assistants will continue to improve. 

A key benefit of utilising machine learning is that it can be effectively applied across unstructured, semi-structured and structured datasets. 

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.

Speech and sentiment analysis has expanded in use with the technologies becoming 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. 

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.


Data has always had a central role in the claims management process and today insurers have more access than ever before. 

It’s collected from a wide range of sources, such as voice analytics, social media activity, wearables, telematics and connected sensors. Machines are required to process this abundance of information and return analytical insights.

According to Accenture (2018), the majority of companies in the insurance industry process only 10–15 per cent of data they have access to. 

This largely comprises 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.

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. 

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.


Robotic process automation (RPA) and ML technologies are increasingly becoming a reality, but how does this impact claims management? Claims functions are often viewed as one of the most manual, labour-intensive parts of an insurance business. 

For example, amongst other tasks, RPA and ML currently provides insurers with the capability to automate claim registration, liability determination, policy administration and invoicing. 

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.

Automation, Ai and ML is a present force driving the Insurance Industry. 

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.

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