The insurance industry is undergoing a remarkable transformation worldwide with the adoption of newer technologies like artificial intelligence and machine learning. The Indian insurance industry is also going through an exceptional revolution driven by changing customer demands, tech advancements, and evolving regulations. Integrating advanced technologies like artificial intelligence is addressing some of the common challenges faced by the growing insurance industry in India. These include under-penetration, operational inefficiencies, and evolving customer needs, such as highly personalised policies. Read to learn how artificial intelligence is reshaping the insurance industry in India.
AI Integration and Transformation of the Indian Insurance Industry
Here are the areas in which AI is transforming the Indian insurance industry:
Automated KYC and documentation
Insurance companies have automated the process of customer onboarding by integrating AI into the system. AI-based optical character recognition (OCR) can scan KYC documents such as Aadhar cards and PAN cards to automate the process of KYC verification in no time. With instant verification and paperless documentation, client onboarding is almost instant, unlike the days of the onboarding process in the traditional insurance ecosystem.
Enhanced risk assessment
With AI, risk assessment methods have been enhanced in the insurance industry. Big data analytics and machine learning algorithms analyse large amounts of datasets and play a pivotal role in predicting the potential risks more precisely by identifying the patterns. Installation of tracker devices such as Blackbox and other telematic devices have helped insurance companies in the accurate risk assessment and come up with highly personalised insurance policies. These usage-based insurance policies are designed based on precise risk assessment, which facilitates transparent pricing.
Quick and hassle-free claim processing
AI has changed the way insurance companies process claims by enhancing speed and efficiency. Right from claim intimation, documentation, and damage assessment to payouts, most of the routine tasks are automated. For example, natural language processing (NLP) easily interprets and clearly understands the claimant’s language to automate the process of claim intimation and documentation guidance. Image recognition used in damage assessment significantly speeds up the process. Such automation in the claim process reduces the timeline between claim intimation and claim resolution. Leveraging AI in the insurance industry for claim processing not only improves speed and efficiency but also reduces human error and fraudulent claims. It also enhances customer experience and offers transparency.
Algorithm-based underwriting
AI-powered underwriting in the insurance sector uses machine learning algorithms to collect and analyse huge amounts of data. This includes data such as medical records, customer history, social behaviour and more for evaluating the risk level more precisely. Some of the examples of AI for insurance companies in underwriting include automated medical examination report (MER) checks. This system checks the accuracy of health information that can be used for insurance underwriting. Similarly, videography or video MER is also used as a valuable tool for underwriting. AI-powered underwriting systems can help insurance companies offer highly personalised insurance policies to their customers based on real-time data.
For example, health insurance policies issued by insurance companies with AI-powered underwriting processes reward the customer with a healthier lifestyle with a discounted premium. All this is done based on the real-time data.
Effective client support
Insurance companies are leveraging artificial intelligence to provide round-the-clock support to their client effectively. This includes virtual assistance and chatbots that assist clients 24/7 with policy selection, query resolution, claim assistance and more. Automation in the insurance industry reduces human intervention and provides customers with optimal satisfaction.
Going a step ahead, artificial intelligence can also predict customer behaviour and help insurance companies in client retention through predictive analysis.
Fraud detection and cybersecurity
AI is also effectively used by insurance companies in the detection and prevention of fraudulent activities in real-time. AI-driven cybersecurity tools are extremely valuable for insurance companies to protect their customer data from cyber threats.
Regulatory Challenges
Though insurance companies are rapidly adopting newer technologies like AI and machine learning, there are various regulatory challenges to navigate. Here are some of the challenges faced by the insurance companies:
- Adherence to the standards of the Information Technology (IT) Act and Digital Personal Data Protection Act (DPDPA) for customer data protection as AI-driven systems significantly rely on huge datasets.
- The Insurance Regulatory and Development Authority of India (IRDAI) has also set various guidelines for using AI and data security to secure customer data. Insurance companies must comply with these regulations to implement AI-driven systems in any area.
Conclusion
With the benefits and challenges, innovative AI-powered systems are the future trends in the insurance industry. Advanced technologies like AI and machine learning enhance customer experience, satisfaction, accuracy, transparency, and efficiency in the Indian insurance industry. Insurance companies must also navigate the complexities of regulatory challenges and ensure the ethical use of AI.
Frequently Asked Questions (FAQs)
How does AI help in insurance portfolio management?
Insurance companies use AI to analyse customer behaviour and market trends to allocate funds in market-linked insurance plans efficiently. This helps in effective portfolio management.
How does telematics auto insurance work?
Internet of Things (IoT) devices installed in the car collect and analyse the car’s usage data (including mileage, distance covered, speed, etc) and accordingly adjust the insurance premium.
