Personalisation is not a new concept. It dates back to the 1980s under the term ‘relationship marketing,’ coined by a marketing professor to describe strategies targeting specific customer groups based on their needs and preferences. Initially, this approach involved sending promotional catalogues and product-of-the-month goodies via mail. Over time, it evolved into targeted email campaigns, providing brands with a dynamic new way to engage customers and generate leads.
With the demise of the one-size-fits-all approach, the insurance industry has recognised the critical importance of personalised policies. Such tailored approaches help avoid incorrectly priced policies and missed financial opportunities. Big data is now revolutionising the insurance sector, enabling more precise and effective personalisation, thereby transforming how insurance companies operate and serve their clients.
What is Big Data in Insurance?
Big data refers to the enormous volumes of structured and unstructured data that can be analysed for insights. In the insurance industry, this data comes from various sources, including:
Telematics: Devices in cars that monitor driving behaviour.
Wearables: Health trackers providing data on physical activity and vital signs.
Social Media: Information on lifestyle and preferences.
IoT Devices: Sensors in homes and businesses that track usage and conditions.
Public Records: Financial histories, criminal records, and more.
How Insurers Use Big Data?
We’re living in a digital era where we’re churning out copious amounts of data every day. It is hard for organisations to analyse and interpret extensive data volume unless they adapt innovative tools like big data. While, traditional insurance policies often take a one-size-fits-all approach, leading to inefficiencies and customer dissatisfaction, big data allows insurers to move away from this model by tailoring policies to individual needs. Let us learn how:
Real-time intelligence: Big data gives insurers the power to sift through vast amounts of data to analyse and provide real-time insights quickly, allowing insurers to make prompt decisions and act on opportunities that emerge.
Improved decisions: Human beings are creatures of habit and follow patterns in decision-making. Big data unearths those old patterns, hidden trends and correlations, keeping a strategic approach when it comes to business decisions.
Cost savings: Big data analytics enables significant cost savings by revealing efficiencies and optimisations within business processes. By analysing vast datasets, organisations can identify and eliminate wasteful expenditures, streamline operations, and boost productivity.
Better customer experience: Personalised insurance policies significantly improve customer experience by aligning with individual needs and preferences. With big data, insurers can anticipate customer requirements and offer proactive solutions.
Enhanced risk assessment: Big data enhances the precision of risk assessment by providing insurers with comprehensive and detailed information about potential policyholders. Consequently, insurers can underwrite policies with greater accuracy, setting premiums that more accurately reflect the true level of risk.
Conclusion
Big data is undeniably transforming the insurance industry by enabling the creation of personalised policies that better match individual needs and behaviours. This shift not only benefits customers through tailored coverage and improved experiences but also helps insurers manage risks more effectively and operate more efficiently. As technology continues to evolve, the role of big data in insurance will only become more prominent, paving the way for a more responsive and customer-centric industry.
