AI in Insurance – The Rise of Machines

Artificial Intelligence (AI) and Robotics were once thought to be nothing more than imaginary concepts brought to life by science fiction movies such as Terminator and iRobot.  A world in which computers learnt to think for themselves making decisions without human intervention.

In fact, away from Hollywood entertainment, AI has been on the rise for some time especially in industries which generate a lot of data.

PwC classifies AI as the second machine age, the first being the Industrial Revolution which ‘saw the automation of physical work’ whereas now we see ‘increasing augmentation and automation of manual and cognitive work’.

Awareness has moved on considerably thanks to the rise of the digitally connected world, where the vast quantities of structured and unstructured data generated from text, videos, audio etc. provide the fuel for AI development. The need to be able to quickly process and combine data sources to generate action has seen it applied to everyday tasks, where it is quicker and more efficient than its human alternative.

The rules based system components of AI are a natural fit for underwriting given the structured nature of the questions and answers required.

Software developments and computing power has meant the same intelligent automation can now be applied to through algorithms to all data types, even an individual’s behavior patterns including deviations from the norm.

Natural Language Processing (NLP) has been brought to the masses thanks to technologies such as Siri, but insurance companies are beginning to see the value in monitoring social media to cross reference with claims notifications. This type of machine learning can be applied to recognize patterns to predict fraud and likely future behavior.

IBM’s ‘Watson’ is one such data analytics processor that uses NLP to recognize human speech using advanced analytics to predict and problem solve. Capable of processing millions of documents and reading 800 million pages of data per second, it is easy to see the appeal of using such a platform to manage and process this amount of unstructured data.

Another use of AI in insurance is to automate back-office tasks through a concept of ‘Autonomics’. This software is used in high volume, rules-based work and once programmed can replicate decision making processes and apply them quicker and more efficiently than human operators. Insurers would benefit from automating these routine tasks but many are yet to even begin reviewing their processes simply because their legacy systems are complex transactional platforms which are simply unable to integrate with and make use of these technologies.

Robotic Process Automation or RPA combines all these elements and enables humans to configure the technology or ‘robot’ in order to collect data, recognize patterns and learn from them in order to apply and adapt to new situations. By mimicking human behaviors, the robots are able to not only perform the tasks but also optimize them.

An Accenture report found for insurers across personal and commercial lines, RPA pilots have successfully reduced processing times from 40-80% while improving quality, auditability and better managing operational risk.

In their ‘Robotic Process Automation in Insurance’ report, Celent outlined a concept which they called the ‘Aware Machine’ which outlined how intelligent platform capabilities work together to process tasks. These technologies do need input from humans in order to automate such tasks, and as systems are updated and changed, just like humans, the robots using them need to be re-trained so there is a continuing human component involved.

While there is arguably a need for companies to develop an RPA plan, they do also need to have the correct technology systems in place to integrate these new platforms into their business processes.

With RPA uptake still in its relative infancy, Celent suggests ‘now is the time to experiment with the technology to perform proof of concept experiments’, this way insurers can learn how to gain maximum benefit from these platforms.

KPMG believes that core systems need to be in place in order to utilize the new wave of technologies stating ‘Organizations will have to spend money through technology investments to save money through systems that are more cost-effective’.

The potential value that AI can bring to an organization when used properly remains its key attraction. Celent argues ‘RPA is a tool that belongs in the toolbox and can solve some specific problems, particularly around legacy systems’.

Of the same opinion, Deloitte also argues if insurers want to see the true benefits of AI, ‘legacy systems needs to be overhauled and or replaced’.

What is clear, is AI has evolved, is evolving and is here to stay; to be factored into future planning in order for companies to remain competitive.

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