By Aditya Dadia
With its massive geographical size and constantly increasing economy, India is one of the most exciting markets for insurance products. Despite the constant rise in popularity and reach of insurance solutions even in the most remote parts of the country, there remains a significant gap as far as ‘adequate coverage’ is concerned. This applies to both commercial and personal insurance solutions.
One of the ways through which the legacy issues can be resolved is by data-driven integration. There are a few areas where data-driven integration has already demonstrated fair results. For instance, the use of data analytics has resulted in a whopping 80% increase in customer satisfaction and a 40% reduction in fraudulent claims.
From the perspective of commercial insurance, this integration helps to leverage advanced analytics, artificial intelligence, and big data to improve fundamental aspects including better decision-making, streamline operations, and improve customer engagement.
What is Data-Driven Integration?
Data-driven integration is something we can already feel in different aspects related with insurance services. From improved client onboarding, better customer support, and faster claims processing, the role of data and analytics has already improved the overall quality of customer service. In commercial insurance space, it refers to the strategic usage of technologies like artificial intelligence (AI), big data, and machine learning to analyse huge chunks of information and data. With advanced systems, it is easier to derive actionable insights from such data.
This implies that the legacy methods in commercial insurance that involved a significant level of slow manual work (which is prone to error), can be replaced by reliable and sophisticated systems. Various systems are automated such as risk assessment and claims processing. The quality of personalisation also improves.
Further, AI algorithms analyse patterns and predict outcomes, enabling insurers to offer tailored solutions and proactive services. The role of Big Data is also critical as it helps in taking a more focussed and comprehensive view of customer behaviours and patterns.
Impact on Commercial Insurers
Here is how the overall quality and coverage of commercial insurance services have improved due to data-driven integration:
- Improved Customer Engagement and Personalization: Based on the customer history and patterns, better product suggestions are provided. Since each business’s requirements differ, it is critical to tailor products and offer pricing as per their needs. As an insurance company comes with personalised offerings, it results in higher satisfaction and retention rates.
- Improved Claims Processing: Conventionally, claims processing includes several manual steps that are automated through analytics. Further, the entire process is streamlined, which results in quicker claims resolutions, greatly improving customer satisfaction and reducing administrative costs.
- Fraud Reduction and Risk Management: Since insurers leverage advanced analytics models based on Big Data, it is easier to analyse patterns that could indicate fraudulent activity, enhancing the ability to detect and prevent fraud. With such sophisticated systems in place, the overall quality of risk management improves.
Challenges and Considerations
Here are a few challenges which will affect the rapid adoption of latest technologies in the insurance sector:
- There needs to be more emphasis on data privacy since critical customer information can be at risk due to this integration.
- The entire process of combining the latest technologies with legacy systems can be costly and time-consuming.
- Adhering to evolving regulatory requirements demands constant vigilance and adaptability from insurers.
- There will be a massive demand for skilled professionals who can work simultaneously on conventional and modern systems.
Future Outlook
Data-driven integration has already started, and despite all the challenges (listed before), the technologies will further enhance personalisation and efficiency in insurance services. Regulators will need to play an active role as the customers will demand more transparency, especially related with data usage.
Overall, the demand and supply of commercial insurance shall be facilitated through these digital solutions. As India witnesses comprehensive growth in almost all core sectors, the critical value of insurance services and their quality will also rise. There is potential for significant growth in underpenetrated markets facilitated by digital platforms that make insurance more accessible.
Summing up
Data-driven integration in commercial insurance is not without challenges, such as data privacy, integrating the latest technologies, and meeting regulatory requirements. However, overcoming these challenges shall be important to ensure that the ongoing challenges in the sector are addressed and customers are offered better services. This can be possible only through AI and machine learning advancements that will further enhance service personalisation and operational efficiency.
(The author is Aditya Dadia, Founder, Alwrite, and the views expressed in this article are his own)
