This article is by Bal Badhan, SSP Worldwide and tackles the tricky topic of insurance pricing;
The insurance industry has always been data-driven, but as the landscape evolves, so too must the tools and technologies used to remain competitive. One of the most transformative shifts on the horizon is the adoption of real-time pricing. This capability, powered by advanced data orchestration, enrichment and integration with multiple rating engines, promises to fundamentally change how insurers price their products, respond to market demands and improve customer satisfaction.
Traditionally, insurance pricing models have relied on static data, historical trends and infrequent updates. Pricing reviews and adjustments often happen on a quarterly or annual basis, which can lead to gaps between the premium offered and the risk profile or customer needs at any given moment. In an age where consumer expectations are set by digital giants that offer real-time personalisation, this lag in responsiveness can be a significant disadvantage for insurers.
For insurers, the challenge lies not just in staying competitive but in meeting regulatory demands, minimising risk and ensuring profitability – all while striving for customer loyalty and satisfaction. Fortunately, technology is enabling a path forward: Real-time insurance pricing powered by dynamic, data-driven processes.
What is real-time pricing?
Real-time pricing refers to the ability to calculate and offer premiums dynamically, based on the most current data available. This requires insurers to move away from legacy systems and embrace modern, flexible platforms that can pull from multiple sources of data in real-time, apply advanced algorithms and seamlessly integrate with rating engines.
A real-time quoting platform is an incredibly powerful enabler, providing high levels of self-sufficiency providing customers the ability to make immediate changes based on market events or a focused strategy at a fraction of effort and cost. A good quoting platform can generate more than 120 million quotes per annum.
At the heart of real-time pricing are three key components:
1. Data orchestration
To effectively enable real-time pricing, insurers must first have a robust data orchestration strategy in place. This involves the collection, organisation and management of data from a variety of sources. In the insurance context, this includes customer demographics, claims history, behavioural data, external market trends and even environmental factors.
Modern data orchestration platforms enable insurers to unify these diverse sources of information into a single, real-time view of the customer. This dynamic view is crucial for identifying pricing opportunities and tailoring offers to individual risk profiles.
For instance, a customer purchasing vehicle insurance may trigger data sources such as vehicle type, driving history, real-time traffic conditions, weather data and telematics information from connected devices in the car. When combined, these data points allow insurers to calculate a more accurate premium that reflects the real-time risk associated with that individual.
2. Data enrichment
While data orchestration focuses on unifying internal sources, data enrichment takes this one step further by incorporating external datasets to create a comprehensive view of customer risk. Insurers can leverage various third-party data providers to gain access to non-traditional data streams, such as:
· Telematics and IoT: For auto insurance, telematics devices provide real-time data on driving behaviour, enabling insurers to offer usage-based pricing models. Similarly, IoT devices in homes can provide real-time monitoring of risks like fire or flood.
· Social media and public records: Data from social media or public records can offer insights into life events (e.g. marriage, relocation) that may influence an individual’s risk profile or insurance needs.
· Climate and environmental data: For property insurance, integrating data on natural disaster trends or climate patterns helps insurers assess real-time risks for flooding, hurricanes or wildfires.
The ability to enrich internal data with external insights means insurers are no longer constrained by static risk models. Instead, they can offer pricing that reflects the true, real-time risk of any individual or asset.
Intelligent Quotes Hub has existing integrations across enrichment providers, software houses and specific customer brands that allow fast and easy integration opening up a wide array of data sources. Add to this the ability to assimilate and analyse data for gaining more market share, our solution plays a key part in our customer’s strategic plans.
3. Rating engines
The final piece of the puzzle is the integration of advanced rating engines. Rating engines are the computational tools that take in all the data, both internal and enriched external data, and apply algorithms to determine the most accurate price for insurance coverage.
In a real-time pricing environment, rating engines must be capable of processing complex datasets and returning quotes instantly. Advanced engines also allow insurers to simulate various risk scenarios, testing how changes in certain data points would affect pricing. These engines are often built on cloud-native platforms, which offer the scalability needed to handle high data volumes and complex pricing models in real time.
Moreover, these rating engines can support multi-variant pricing, which allows insurers to assess multiple factors simultaneously (e.g., driving history, location, telematics data) and produce personalised pricing that reflects a nuanced understanding of risk.
Transforming customer relationships
Real-time pricing isn’t just about operational efficiency; it fundamentally alters the relationship between insurers and their customers. With the ability to offer personalised pricing in real time, insurers can respond to customer needs with unprecedented speed and accuracy. This approach builds trust, as customers receive offers that reflect their true risk profile and needs, rather than a generalised, one-size-fits-all premium.
In turn, insurers can reduce churn by offering more competitive, flexible pricing that aligns with customer behaviour and preferences. Furthermore, the real-time insights gained from advanced data analytics allow insurers to develop more innovative products, such as usage-based insurance or on-demand coverage.
The road ahead: Challenges and opportunities
While the benefits of real-time pricing are clear, the road to adoption is not without challenges. Insurers must navigate the complexities of integrating new technologies with legacy systems, ensuring regulatory compliance and managing the sheer volume of data required for real-time analysis. Data security and privacy are also paramount, as the use of external data sources increases the risk of breaches.
However, for those who can successfully implement real-time pricing, the opportunities are immense. Insurers will be better equipped to respond to market changes, tailor their offerings to individual customers and ultimately gain a competitive edge in an increasingly digital landscape.
By embracing advanced data orchestration, enrichment and integration with rating engines, insurers can stay ahead of the curve, offering more competitive products and building stronger relationships with customers. As the industry continues to evolve, real-time pricing will be a critical tool in the ongoing transformation of insurance.
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Bal Badhan is a leading expert in insurance technology and data integration at SSP Worldwide, driving innovation in the digital transformation of the insurance sector.
About SSP
SSP Worldwide provides cutting-edge software solutions that support the entire general insurance value chain, from policy management to claims processing and real-time
pricing capability. Backed by Constellation Software and the Volaris Group, SSP has over 700 clients on six continents catering to more than 40 business classes.
For more information visit https://ssp-worldwide.com/.
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