Nobody is unaware of the recent tech revolutions shaping industries. The pace it’s been advancing opens new gateways for opportunities and reevaluation. Like every major industry, insurance is also eagerly looking to adopt GenAI to advance its business processes and leverage its vast amount of data to generate insights. However, the implementation requires major changes in management practices and data readiness. 

Globally, AI is revolutionising the insurance industry by helping them improve their decision-making capabilities, streamlining operations and deeper insights into customer behaviour and risk management. However, in India, we need to overcome some challenges in terms of technology, culture and regulatory hurdles.

India’s insurance market is the 10th largest in the world with total premium volumes and 2nd largest in emerging markets. This indicates there is an increase in demand for insurance growth but the number of the population covered under life insurance is not much. So, what can be done? There is a need to expand insurance penetration irrespective of geographical location and solutions catering to all segments of society. This is where AI and technology can help bridge the gap by enabling insurers to reach more effectively and serve the diverse population of India. 

Here, we will try to highlight how GenAI and ML can reshape the insurance industry and move from traditional practices to a technology-driven strategic advantage.

1.Risk Assessment- AI can be a great add-on to the current risk assessment process. Its ability to analyse vast amounts of data can lead to better predictions and assessment of potential risks. It can provide a near real-time experience helping insurers with precise and personalised policies and offerings. 

According to a KPMG report, companies using AI for risk assessment have a 25% increase in the accuracy of their risk prediction.

2. Claim Automation- Claim processing powered by AI can provide faster resolution and increased efficiency. According to a McKinsey report, AI could cut the time for claim processing by 30% ensuring quick settlements and reduced administrative burdens. Traditionally the claim process follows steps like– claim filing, document review, and manual assessment which AI can automate by extracting information from claims, assessing damage and calculating payouts. So, the tasks that could take weeks to finish can be completed within a few days.

3. Fraud Detection and Prevention- AI can also be very helpful in identifying frauds which is one of the significant concerns in the insurance industry.  Currently, Fintech and insurtech are two sectors that use AI for fraud detection where algorithms help them identify patterns and irregularities in the claim data and prevent potential threats. The traditional ways of fraud detection can be time-consuming and ineffective. Besides, it also helps reduce the cost of fraud detection for insurance companies and enables them to take preventive measures to save time and resources. Forbes reports that AI systems can improve fraud detection accuracy by more than 50% compared to traditional methods.

4. Virtual Assistants and Chatbots- Another use case for AI can be its capability to engage with customers 24/7, handling basic day-to-day queries and freeing up agents’ time for other tasks. 

84% of companies believe that AI chatbots will become more important for communication between a customer and business.  

Chatbots and virtual assistants can escalate the process of getting the right solutions. They can be trained to answer common questions of customers like policy updates, claim filing, making changes in the coverage, etc, without a human agent intervention. This capability will not only help improve customer experience but also reduce frustration.

5. Personalised Product Offerings- AI can help create a tailored insurance plan by leveraging analytics to meet each customer’s needs. Accenture report says, over 80% of consumers are willing to share their personal data with their insurer in exchange for personalised services. Insurance companies can analyse data from sources like customer behaviour, preferences and past claims to offer products tailored to their unique needs. Providing this level of personalisation was not possible before but implementing AI in a conversational form can bring numerous benefits to the insurance industry.

Challenges and Ethical Considerations:

Data Privacy and Security- One of the very uncompromised aspects for Insurance companies is data privacy and security. As they are entrusted with an abundance of data, storing and processing this data using artificial intelligence would require the implementation of stringent security measures. Organisations that will be able to uphold the high standards of data security and privacy will achieve greater ROI while maintaining customer trust.

Addressing Bias in AI- As training data comes from various sources, there can be certain prejudices related to culture, history, and society. Hence, it is important to ensure and overcome such biases for equal and fair outcomes. To address such concerns a thorough audit, implementation of diverse mindsets and utilising tools for bias detection can enhance reputation and compliance with ethical standards.

Conclusion

Implementation of GenAI in the insurance value chain offers benefits to both insurer and policyholder. AI can redefine risk assessment, underwriting, claim management and tailored marketing campaigns to deliver superior customer experience. 

Get in touch with us at marketing@salespanda.com to know more about the GenAI upgrades we are doing for sales and marketing.

Tagged AI in Insurance