Taking AI help for insurance and trading

Vijay C Roy

Chandigarh-based Nikunj Gupta, a mechanical engineer, wanted to buy an insurance policy but kept delaying it because of the time he would have to devote to figure out which policy suited him best. When a colleague mentioned about the chatbot or virtual assistant offered by insurance companies, he put it to use and after comparisons, bought a policy within a few minutes.

Similarly, Ludhiana-based Manpreet Sethi used to rely on research analysts and media coverage to make investment decisions in the stock market. Now, he gets artificial intelligence-based easy-to-read predictions for about 1,500 scrips, based on his risk profile, at the click of a mouse.

The Benefits

• “Using micro-data analytics, insurers are crafting tailor-made healthcare coverage, aligning with individuals’ financial capabilities and needs, especially for those residing in Tier 2, 3 cities, and beyond. Through data analytics and personalised tools, select insurers have rolled out cost-effective health insurance.”
  Layak Singh, co-founder and CEO of Artivatic.AI
• “Claims management is one of the popular use cases of AI right from intimation to claim settlement. Fraud detection estimation models facilitate the turnaround time by analysing data and identifying patterns to detect fraudulent claims.”
  Rajive Kumaraswami, MD & CEO, Magma HDI General Insurance
• “Data patterns can quickly and accurately identify fraudulent activities in the healthcare sector. AI algorithms can analyse patterns and anomalies in claims data and flag fraudulent transactions. Fraud is a consistent headache in the insurance industry and prevention can help insurers save money and ensure that premiums remain low for honest policyholders.”
  Brij Sharma, founder & chairman, MDIndia Health Insurance

AI is rapidly becoming the driving force behind data-driven decision-making, and the insurance and stock broking sectors are no exception.

In the insurance sector, chatbots and virtual assistants, powered by AI, understand natural language and provide personalised customer support, with timely information. These technologies can handle customer inquiries, process policy applications and offer recommendations tailored to individual needs. They are thus improving overall customer satisfaction.

In stock investment, AI is assisting customers by analysing stocks on various parameters and suggesting to buy or sell as per the customers’ profile.

Buying a policy

“AI can help in improving customer service using chatbots and virtual assistants that can stay in touch with the customer, help with claims and enable a speedy and effective response from the insurers,” says Brij Sharma, founder and chairman, MDIndia Health Insurance.

AI-driven comparison tools assist in evaluating different insurance options by highlighting key features, coverage details and pricing structures. These tools leverage AI to quickly process large amounts of data, empowering users to make informed decisions about the most suitable insurance options.

As high premium is considered one of the stumbling blocks, insurers have introduced customisation of policies. This ensures flexibility in choosing the coverage that suits financial planning. Thus, AI leverages the insights gained from data analysis to offer personalised policy recommendations to individuals. It can analyse vast amounts of data about policyholders, including their specific risk profile, demographics, past claim history, preferences, needs and the budget.

“Based on the data shared by customers, insurance brokers and companies generate options best suited for customer requirements, helping them make better decisions. This technology helps insurance brokers and companies in risk assessment and pricing, fraud detection, customer segmentation (demographics, behaviour, and preferences), and predictive modelling of claims, etc,” says Syed Meraj Naqvi, CEO and principal officer, Riskbirbal Insurance Brokers.

Customer support

AI has revolutionised the operational framework by refining processes, fostering efficiency, reducing costs, and providing better services for insurers and policyholders alike.

“AI-driven chatbots have been widely implemented, and they provide instant customer support by answering queries and providing guidance to users throughout the insurance life cycle. This significantly improves customer satisfaction and reduces the manual intervention and workload of service representatives by streamlining and refining the service delivery process,” says KV Dipu, senior president and head-operations and customer service, Bajaj Allianz General Insurance.

AI also plays a significant role in underwriting and risk assessment. AI algorithms help analyse vast amounts of data and assess risk more accurately. This helps in refining the products’ pricing more precisely and provides more competitive and tailored offerings, attracting a wider range of customers.

For example, the integration of telematics devices in vehicles and Internet of Things (IoT) devices, such as smart home sensors in home insurance, has been monumental. Real-time data on driving behaviours from the telematics device helps insurers offer usage-based insurance, where premiums are based on actual driving habits, promoting safer driving practices.

IoT devices in homes actively monitor risks like fire, theft or water damage, allowing insurers to offer more accurate pricing and proactive risk management.

“Dynamic underwriting, powered by AI algorithms, has redefined risk assessment, expediting processes and fortifying accuracy. In claims management, AI expedites the evaluation and settlement process, while AI-driven virtual assistants redefine customer interactions, ensuring a seamless and personalised experience,” says Anil Kumar Aggarwal, managing director and CEO of Shriram General Insurance.

Tech In Equity Market

Before the emergence of Internet and trading and investment apps, traders relied on analysts and media coverage to guide investment decisions.

Various tools, including charting libraries, have now become accessible to retail clients engaged in active trading. However, assessing the abundance of content, indicators, tools and trading knowledge requires a significant effort. “Considering these hindrances, we have introduced the first-ever AI-powered trading platform to offer predictions and signals for individual stocks. We have partnered with I Know First (IKF), which brings the power of predictive AI to the trading platform, enhancing the decision-making capabilities of traders. AI algorithms analyse historical patterns of around 1,500 scrips, market trends and other relevant data to predict the future performance of financial assets,” says Sarvjeet Singh Virk, co-founder, Shoonya.

The insights provided by AI empower short-term and long-term investors and retail traders to make informed decisions. They streamline the research process, enhance precision, identify trends, and reduce overhead expenses.

It not only predicts when to buy in the future, but also indicates when to sell stock in the existing portfolio.

Given the complexities of the capital market, AI-powered predictive tools primarily aim to augment human decision-making rather than replacing it. While algorithms rely heavily on market data and help eliminate biases and preconceptions, they may overlook elusive opportunities that only the human mind can recognise.