Artificial intelligence – friend or foe to advisers?

At a recent event I heard someone say that insurance distribution must be the only industry that has taken technology to heart and made life more complicated.

In one way I understood what was being said – we nearly all use ‘tech’ to keep in contact with our clients via Contact Management Systems, we certainly use it to quote premiums in a way that suits regulation, and of course to source the literally thousands of mortgages available.

In some instances the tech usage can help (no re-keying, for example), but in some, it hinders, especially when different aspects of insurer’s products appear on comparison software - something which can hinder the compliance process, not help it.

While the majority of ‘paper’ has been taken away, some would say it has replaced one burden with another and not enhanced our roles as it may have done. Of course, each individual firm will have embraced tech in its own way and you can be the true judge of its efficiency within your own businesses.

So the next generation of tech is here and clearly here to stay in the form of Artificial Intelligence (AI) and we now should consider the pros and cons of this colossus of a worldwide phenomenon and how it might affect what we do on a daily basis in our insurance world. 

It will not surprise you to hear that different insurers appear to have latched on to its usage in hugely different ways, and probably with varying levels of investment.

It would be possible to write volumes and volumes on this subject and how it links to insurance, but let’s start by looking at what AI and Machine Learning (ML) can do for business to begin with. It can help to:
 

• Free up staff resources and have AI and ML perform repetitive tasks.
• Automate and improve complex, manual tasks with AI and ML.
• Impose air-tight security with AI and ML.
• Future-proof your business with AI-driven decision-making.

If we look at just one major aspect of life insurance, underwriting, AI is significantly impacting the life underwriting process in the insurance industry, enhancing efficiency, accuracy, and overall effectiveness. There are several ways in which it is doing this:
 

1. Data Analysis and Risk Assessment - Big Data Utilisation:

AI systems can analyse vast amounts of structured and unstructured data, including medical records, lifestyle information, and social media data, to assess an individual's risk profile more comprehensively. In addition, AI algorithms can predict potential health issues or mortality risks based on historical data, allowing underwriters to make more informed decisions.
 

2. Automated Underwriting:

AI enables the automation of routine underwriting tasks, such as data collection and risk assessment. This speeds up the underwriting process and reduces the need for manual intervention. Automated underwriting ensures a consistent and objective evaluation of applicants, minimising human bias and subjective judgment.
 

3. Enhanced Customer Interaction:

Chatbots and Virtual Assistants can interact with customers, collect relevant information, and answer queries. This improves the overall customer experience and accelerates the underwriting process by obtaining necessary details in real-time.
 

4. Personalised Underwriting and Pricing:

AI allows for more granular risk assessment by considering individual health data and lifestyle factors. This leads to more personalised underwriting and can support better pricing strategies. AI systems can also adapt pricing models based on changing risk factors, ensuring insurance premiums remain reflective of current risk profiles, something which past ‘actuarial tables’ have not been able to do.
 

5. Fraud Detection and Prevention:

AI algorithms can detect patterns indicative of fraudulent activities, helping underwriters identify potentially dishonest applications. AI tools can identify unusual patterns or discrepancies in application data, raising red flags for further investigation.
 

6. Continuous Monitoring and Adaptation:

AI can enable continuous monitoring of policyholders' health and lifestyle changes. This allows for dynamic risk assessment and adjustment of coverage and premiums over time.
 

7. Predictive Analytics:

AI-driven predictive analytics can assist underwriters in anticipating future health trends and risks, enabling proactive risk management strategies.
 

8. Efficient Workflow Management:

AI can prioritise underwriting tasks based on urgency, complexity, or other factors, optimising the workflow for underwriting teams. It can also assist in document analysis and extraction, reducing the time spent on paperwork and administrative tasks.
 

9. Compliance and Regulation:

AI systems can assist in ensuring underwriting processes adhere to regulatory requirements and compliance standards.

In summary, AI has the power to revolutionise life underwriting by automating processes, improving risk assessment accuracy, and providing valuable insights for more informed decision-making. This not only benefits insurance companies by increasing efficiency (and potentially taking cost out of the business) but also enhances the overall customer experience through faster and more personalised underwriting processes.

How it will affect all of us at an adviser level is up for debate but it is definitely coming and certainly something to keep an eye on when planning your own journey into greater tech usage.