Life Insurance and AI

The sudden boom of Artificial Intelligence (AI) technology has been changing life insurance into a more data focused and risk averse segment of Insurance. How can technology that powers virtual assistants, data processing mechanisms and various smart functions impact life insurance? The answer, it turns out, is both profound and far-reaching. From underwriting, broking to compliance, the introduction of widespread of AI technology into the life insurance sector is not a look into the future of the segment—it is our current reality. Those who leverage AI within life insurance are at a significant advantage.

AI innovation in life Insurance

Artificial Intelligence (AI) is reshaping life insurance by making it smarter, faster, and more personal.

Applying for life insurance and getting a policy tailored specifically to you within minutes, thanks to AI’s ability to quickly analyse medical histories and lifestyle habits. This technology allows insurers to assess risks with precision, ensuring a fair price for a tailored package. AI doesn’t just stop at underwriting, policy administration and compliance; it’s also integrated into customer service. With AI-driven chatbots and virtual assistants, your questions can be answered instantly, and claims can be processed with remarkable speed, often in real-time using an existing document database.

AI, with capabilities like machine learning, fuelled by the influx data, has started redefining life insurance. Customer profiling, policy pricing, claims processing and risk management—all crucial insurance aspects have AI’s footprint. A future where a life insurance application is processed, approved or denied almost instantaneously with AI, isn’t a far-off reality anymore.

How AI is transforming life insurance underwriting

A crucial transformation for life insurance is AI-powered underwriting. Traditionally, underwriting involved lengthy questionnaires and extensive medical exams, often resulting in long wait times for policy approval. With AI, this is changing dramatically. Advanced algorithms and machine learning models can now swiftly analyse vast amounts of data, including medical records, prescription histories, and even lifestyle information from wearable devices.

Companies like John Hancock have recently integrated AI into their sales process, enhancing their insurance buying process. John Hancock have also introduced eApp platform, according to McKinseyenabling end-to-end digital process across policies of all face values.

Prudential Financial have also integrated machine learning processing into their back-end databases, resulting in a 98-99% accuracy rate in forecast longevity.

Haven Life have integrated AI-powered technology to streamline their underwriting processes.

Through the uses of vector technology such as wearable fitness devices, these life insurance leaders are able to tailor premiums to individual health metrics. For example, Prudential Financial’s Fast Track platform utilises machine learning to analyse electronic health records, speeding up the underwriting process. Haven Life employs AI algorithms to instantly review applicants’ data, offering near-instant policy decisions. These innovations not only expedite the approval process but also ensure fairer and more accurate premium calculations, making life insurance more accessible and personalised than ever before.

How AI is transforming life insurance broking

AI is also making significant strides in transforming life insurance broking, enhancing the way brokers interact with clients and manage their portfolios. Traditionally, brokers relied heavily on manual processes and personal interactions to match clients with the right policies. However, AI is now enabling brokers to provide more precise and efficient services, ultimately benefiting both brokers and their clients.

One of the key areas where AI is making an impact is through advanced data analytics. AI systems can analyse vast amounts of data, including client demographics, health records, financial status, and even social media activity. This comprehensive data analysis allows brokers to gain deeper insights into their clients’ needs and preferences, enabling them to recommend the most suitable policies with greater accuracy. For instance, AI can identify patterns and trends that might not be immediately apparent to human brokers, ensuring that clients receive personalised advice that is tailored to their unique circumstances.

Additionally, AI-powered tools are streamlining the administrative tasks that brokers typically handle. Tasks such as policy comparison, quote generation, and paperwork management can be automated, freeing up brokers to focus on building stronger client relationships and providing strategic advice. This not only improves efficiency but also reduces the potential for human error, ensuring that clients receive accurate and timely information. One notable example is the Canadian Broker Network (CBN), which has implemented an AI-driven robot. This AI bot automates repetitive data entry tasks in broker management systems, drastically reducing the time spent on administrative work. By eliminating duplicate data entry, CBN brokers have reported productivity improvements of up to 800%, along with enhanced data accuracy and significant cost savings. This allows brokers to focus more on meaningful customer interactions and providing personalised advice (Insurance-Canada.ca).

AI-driven chatbots and virtual assistants are also enhancing client interactions. These tools can handle routine inquiries, provide instant quotes, and even guide clients through the initial stages of the policy selection process. By leveraging AI, brokers can ensure that clients receive immediate support and information, improving overall customer satisfaction and engagement.

Moreover, predictive analytics powered by AI can help brokers anticipate market trends and client needs. By analysing historical data and current market conditions, AI can provide brokers with forecasts and insights that inform their advice and strategy. This proactive approach allows brokers to stay ahead of industry changes and offer clients forward-thinking solutions.

Data-driven insights and compliance

Ensuring Compliance with AI and Data Analytics

Navigating regulatory compliance is a significant challenge in the insurance industry, particularly with the introduction of AI and big data. Insurers must ensure that their AI models and data processing methods adhere to strict regulatory standards to avoid legal pitfalls and maintain customer trust. AI can aid in this by automating compliance checks and ensuring that data usage is transparent and ethical.

Regulatory bodies are increasingly focusing on the transparency and fairness of AI algorithms. For instance, regulations may require insurers to explain how their AI models make decisions, ensuring that these processes are free from bias and discrimination (https://www.v7labs.com/blog/ai-insurance)(https://www.mckinsey.com/industries/financial-services/our-insights/insurance-2030-the-impact-of-ai-on-the-future-of-insurance). This is where AI-powered compliance tools come in. They can monitor and audit the decision-making processes, ensuring that all actions comply with regulatory requirements and are traceable.

Beyond insurance-specific processes: AI’s broader impacts on life insurance

Artificial Intelligence (AI) is not only transforming core insurance processes such as underwriting, broking, and compliance but also significantly impacting broader aspects of the life insurance industry. These broader impacts are enhancing customer experience, fostering innovation in product development, and improving operational efficiencies.

Enhanced Customer Experience

AI is fundamentally changing how life insurers interact with their customers. Personalised communication and instant support are now possible through AI-powered chatbots and virtual assistants. These tools provide immediate responses to customer queries, guide them through policy selections, and even assist in filing claims. For instance, Accenture highlights that insurers using AI for customer interactions can achieve higher satisfaction rates and efficiency by enabling contactless and digital policy issuance, which became particularly valuable during the COVID-19 pandemic. This shift towards a more personalised and efficient service leads to higher customer satisfaction and loyalty (https://insuranceblog.accenture.com/ai-driven-customer-experience-smart-move-for-life-insurers) (https://insurtechdigital.com/articles/using-ai-to-improve-the-insurance-experience-for-good).

Innovative Product Development

AI is driving innovation in life insurance product development by enabling insurers to create more customised and flexible products. Usage-based insurance (UBI) is a prime example, where premiums are adjusted based on real-time data collected from policyholders. For instance, Fujitsu’s AI solutions have been utilised to create highly personalised insurance offers that align closely with individual customer needs, leveraging data from various sources to craft bespoke sales offers and embedded insurance options. This approach not only aligns the product with individual needs but also promotes healthier lifestyles among policyholders (https://insurtechdigital.com/articles/ai-in-insurtech-evolving-the-customer-experience).

Risk Management and Predictive Analytics

AI enhances risk management through advanced predictive analytics. Insurers can analyse large datasets to identify emerging risks, forecast future trends, and make informed decisions. Predictive analytics can also help in anticipating customer needs and behaviours, allowing insurers to offer proactive solutions and tailored advice. This data-driven approach to risk management not only improves the insurer’s ability to mitigate risks but also enhances the overall resilience and agility of the organisation.

Data Security and Privacy

With the increasing reliance on data, AI also plays a crucial role in ensuring data security and privacy. AI-driven cybersecurity solutions can detect and respond to threats in real-time, protecting sensitive customer information from breaches. Furthermore, AI can help insurers comply with data protection regulations by automating compliance checks and ensuring that data usage policies are adhered to consistently.

Integration of AI into life insurance

AI in life insurance is a game-changer, although the next bottleneck is integrating AI technology into a fragmented IT system. Simpli Automation, with its expertise in Robotic Process Automation (RPA) and AI, plays a role in this transition. Our Digital worker Karina is able to automate repetitive tasks like data entry and claims processing, significantly reduces manual workload and errors.

Simpli’s capabilities to integrate new AI tools with legacy systems allows for life insurance professionals to use the capabilities of various artificial intelligence tools with agility, without disrupting their current operations.

To learn more, get in touch with one of our leaders or join Karina’s waitlist here.

Michael McGurn (CEO & Founder) – mick@simpliautomation.com

Allan Murego (Head of Partnerships) – allan@simpliautomation.com

Ilya Laptev (Head of Growth) – ilya@simpliautomation.com