Insurance has been the cornerstone of financial security for centuries now, and despite its enduring significance - the general insurance penetration rate in India remained at a mere 1% as of 2022. This low penetration rate is alarming, especially when compared to the global average of 7.23%; highlighting an urgent need and a tremendous opportunity for growth and innovation in our industry.
One promising avenue is the shift towards personalised insurance products. Today personalisation is no longer a luxury—it’s a necessity. As consumers become more accustomed to tailored experiences in their everyday lives, from personalised shopping recommendations to customised streaming services, they expect the same level of personalisation from their insurance providers. The insurance industry is embracing this challenge with cutting-edge InsurTech solutions, harnessing advanced data to create products meticulously designed to meet individual needs and preferences. Moreover, by forging alliances with ecosystem partners, insurers are reaching the right customers at the right time with the right insurance solutions; bringing peace of mind and a sense of security to millions of customers.
What Is Personalisation in Insurance and Why Is It Important?
Personalisation in insurance policies refers to the strategic customisation of insurance products and services to address the specific needs and preferences of individual customers. In contrast to traditional standardised services offered by insurers, personalised insurance utilises comprehensive data analytics, in-depth consumer insights, and cutting-edge technologies to develop policies uniquely tailored to each customer’s risk profile, behaviour and needs in real time.
The importance of personalisation in insurance cannot be overstated. First and foremost, it enhances customer satisfaction. When customers feel their specific circumstances are understood and addressed on a deeper level, they are more likely to develop a strong, positive relationship with their insurance providers. In turn, insurers tend to have higher conversion rates when customers are offered purchase options specifically designed for them — benefitting both the insurer and the insured.
The Global Insurance Consumer Study 2023 by Accenture provides compelling evidence of the market's readiness for personalisation. The study reveals that 58% of consumers express willingness to share substantial data in exchange for advice more relevant to their circumstances. Moreover, 60% indicate they would be willing to share significant data for expedited, streamlined services, such as insurance claim processing without the need for extensive application procedures. These statistics underscore a notable market openness towards personalisation, highlighting a whitespace ripe for disruption.
How is Data Driving Personalised Insurance Policies?
Modern insurers are pivoting from product-centric to customer-centric approaches, driven by advancements in data analytics — allowing them to harness and analyse diverse data types across an extensive range of sources.
By leveraging these data capabilities, insurers can now build a comprehensive and dynamic understanding of their customers; offering unprecedented levels of personalisation and engagement, the kind that goes beyond the basic service offerings and transactional exchanges.
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Following are the key data types enabling tailored insurance policies:
Demographic Data
Demographic data includes basic information about individuals such as age, gender, location, income level, and family status. This type of data provides a foundational understanding of the customer base, allowing insurers to offer policies that address the specific life stages and financial responsibilities of customers.
Behavioural Data
Behavioural data, captured through telematics devices, wearable technology, smart home devices, customer’s digital footprint and usage patterns provides insights into daily habits and lifestyle choices. This data is pivotal for understanding the behaviours that influence risk profiles; and tailoring policies for customers to encourage better choices.
Transactional Data
Transactional data includes information about a customer’s purchase history, claim records, and payment patterns. This data provides a detailed view of a customer’s financial behaviour and past interactions with insurance products, crucial for personalised policy development that rewards responsible customers with better terms and lower premiums.
Psychographic Data
Psychographic data encompasses lifestyle preferences, interests, and attitudes collected from surveys, interviews, social media interactions, and third-party data providers. This type of data enables insurers to offer policies that align heavily with customer values and lifestyles, fostering a more meaningful relationship with them.
Real-time Data
Real-time data, gathered from IoT devices, telematics, and other connected technologies, provides immediate insights into current conditions and behaviours. This data enables insurers to offer dynamic, real-time policy adjustments, making insurance more responsive and relevant to the customer's immediate needs.
Cross-Business Partnership Data
This includes insights gathered from partnering with cross-business entities such as fintech firms, e-commerce platforms, travel portals, and cab aggregators. These partnerships allow insurers to tap into a wealth of additional data points that would have not been accessible otherwise, enhancing their ability to offer highly relevant and timely insurance products and services.
The sheer volume, variety, and velocity of data available to insurers have transformed the way policies are created, priced, and managed. The following examples demonstrate how insurers are leveraging this data revolution to create truly personalised insurance products:
Personalised Health Insurance
Discovery Health's Vitality program in South Africa is a prime example of using behavioural data to personalise health insurance. This program tracks members' physical activities, diet, and preventive health measures through wearables and other technologies. By implementing advanced analytics on this comprehensive dataset, Discovery has created a value-driven model that incentivises healthier lifestyles through targeted discounts and rewards. This approach yields multiple benefits for insurers, including improved overall health outcomes, enhanced insurance product offerings, and measurable financial returns.
Personalised Life Insurance
Historically, risk assessment was done based on demographic data points such as age, risk location, pre-existing diseases (PEDs), and gender. This cohort-based pricing was, while widely used, prone to leakages. LifeScore Labs analyses diverse data that includes family history, clinical lab results, electronic health records (EHRs), genetic information, social habits, and environmental factors for accurate and personalised underwriting. This approach leads to fairer premiums, as individuals are charged rates that accurately reflect their risk rather than relying on generalised averages. Ultimately, this data-driven pricing strengthens the value proposition of life insurance for both insurers and customers, especially for those with lower risk profiles.
Personalised Home Insurance
US-based Hippo Insurance uses real-time data from smart home devices to personalise home insurance policies. Sensors and devices that monitor for water leaks, smoke, and security breaches provide data that helps Hippo assess risk more accurately. Homeowners who use these devices can receive discounts on their premiums, and the real-time data enables quicker response times to potential issues, reducing the likelihood of claims. This proactive stance not only minimises property damage but also aligns the interests of the insurer and the insured, fostering a more collaborative and mutually beneficial relationship between them.
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Personalised Travel Insurance
InsureMyTrip, a US-based company, exemplifies the use of real-time data and advanced analytics to offer personalised travel insurance. Their SMART recommendation engine harnesses comprehensive customer data, including travel patterns, preferences, and historical claims information to identify specific risk factors and recommend targeted coverage options. For instance, it can suggest specialised protection for cruise travellers who have a higher likelihood of missing ship departures due to flight delays or connections. This level of personalisation addresses unique travel risks that standard policies might overlook. Additionally, the engine takes real-time weather conditions into account while recommending insurance policies automatically suggesting coverages for weather disruptions when needed. This removes the guesswork for travellers, making it easier for them to choose the right insurance plan and feel more confident in their travel insurance purchase decisions.
Personalised Auto Insurance
The US-based Allstate's Drivewise program uses telematics to collect data on driving behaviour, including speed, braking, and mileage; all while rewarding safe driving habits with discounts on premiums. This personalised auto insurance tailors premiums based on individual driving patterns, promoting safer driving and offering savings to conscientious drivers.
By leveraging data to drive innovation through hyper-personalisation, gamification, incentive-based buying and self-serving user experiences, insurers can not only better meet the specific needs of their customers; but also keep their tech-savvy consumers consistently engaged in a world where gaining customer loyalty is becoming increasingly difficult.
Getting Started with Personalised Insurance Policies
As consumer expectations evolve and data capabilities expand, insurers seek to leverage these opportunities effectively to create truly tailored policies. This transformation requires a strategic approach that combines technological innovation, data analytics, and a shift in organisational mindset.Â
Building a Robust Data Infrastructure
First and foremost, insurers must establish a sophisticated data infrastructure. The quality of insights and personalisation is only as good as the data collected, making it essential to ensure data accuracy, completeness, and relevance. This involves deploying scalable cloud computing solutions with advanced technologies such as big data analytics, artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) to enable the seamless collection, integration and analysis of data from diverse sources, including third-party partners, customer interactions, and social media. A robust infrastructure should not only process vast amounts of structured and unstructured data but also derive actionable insights with precision. This capability allows insurers to rapidly adapt and respond, facilitating the delivery of highly personalised insurance offerings.
Strategic Partnerships for Data and Analytics
Forming strategic partnerships is a key step in enhancing an insurer's data ecosystem and analytical capabilities. Collaborating with InsurTech companies in India, data aggregators, digital health platforms, and similar partners can provide access to diverse data points and advanced analytical tools. For instance, partnering with health apps and wearable tech companies allows health insurers to monitor lifestyle and health metrics, leading to more accurate risk assessments and personalised plans. Similarly, strategic alliances with automotive manufacturers and telematics providers can revolutionise auto insurance offerings with personalised coverage based on real-time driving data.
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Fostering a Culture of Innovation
Cultivating a culture of innovation within the industry in general, is paramount to continuously embrace new technologies and provide best-in-class experiences to our customers. By creating an environment that supports experimentation and agility, insurers can stay at the forefront of these cutting-edge technological advancements. Partnerships with leading InsurTech companies in India can keep insurers at an advantage by accelerating integration with state-of-the-art solutions and expertise, enabling insurers to meet and exceed customer expectations with speed and efficiency.
Prioritising Regulatory Compliance and Security
As insurers delve deeper into personalisation, navigating regulatory compliance and security is essential. Handling vast amounts of sensitive customer data requires adherence to strict data privacy regulations, transparent data practices and robust security measures implementation. Insurers should consistently collaborate with regulatory bodies and their InsurTech solutions partners to stay updated on compliance requirements, ensuring alignment with legal standards at all times.
The Future is Personal
As we look to the future, hyper-personalisation will become a key differentiator in the competitive insurance landscape. There are tremendous opportunities for insurers to grow by strengthening their digital core and fostering a culture of continuous reinvention. This involves seamlessly integrating functions and data across the entire value chain, while simultaneously exploring innovative operational methodologies. Insurers who proactively invest in cutting-edge InsurTech solutions and forward-thinking strategies will reap substantial benefits. Driven by advanced data analytics, insurers have the power to tailor policies and continually adapt them in real-time based on a customer's evolving needs and circumstances. When done right, this will not only forge stronger, more meaningful customer relationships but also establish new benchmarks for innovation and service excellence within the industry.
As the insurance landscape evolves, those companies that successfully navigate this transition towards personalisation and digital transformation will likely emerge as industry leaders, setting the pace for others to follow.
Bibliography:
https://www.irdai.gov.in/ (last accessed on August 6, 2024)
https://www.accenture.com/content/dam/accenture/final/industry/insurance/document/Accenture-Insurance-Consumer-Study-People-Before-Policies.pdf (last accessed on August 6, 2024)
https://technologymagazine.com/company-reports/vitality-using-technology-to-transform-health-insurance (last accessed on August 6, 2024)
https://www.lifescorelabs.com/predictive-analytics-in-life-insurance (last accessed on August 6, 2024)
https://www.prnewswire.com/news-releases/how-insuremytrip-is-disrupting-the-travel-insurance-industry-300855232.html (last accessed on August 6, 2024)
https://www.bankrate.com/insurance/car/allstate-drivewise/#what-is-allstate-drivewise (last accessed on August 6, 2024)
