Revolutionizing Insurance: How Aviva Utilized Hyperexponential’s Platform to Develop 20 Pricing Models in Record Time

In a remarkable achievement, Aviva Global Corporate and Specialty (GCS) has successfully leveraged Hyperexponential’s Pricing Decision Intelligence (PDI) platform, hx Renew, to expedite the creation of 20 new insurance pricing models in just nine months. This significant progress has transformed Aviva’s underwriters’ ability to generate new policies in under 10 minutes, a drastic improvement from the previous duration of over an hour.

Accelerating Model Creation with Hx Renew

Aviva’s utilization of hx Renew’s robust platform has proven instrumental in transforming the speed and efficiency of their insurance pricing model creation process. By adopting a modular approach and incorporating the power of Python, Aviva has streamlined their model creation process, freeing up actuaries to focus on higher-value tasks and in-depth business analysis.

The integration of hx Renew has enabled Aviva to overcome the limitations of using Excel spreadsheets for rating tools and pricing models. With hx Renew, Aviva has gained the capability to create, test, and refine pricing models at a rapid pace. This has not only accelerated the model creation process but has also improved accuracy and stability.

Streamlined Data Access and Processing

Hx Renew has also revolutionized Aviva’s access to data and data processing capabilities. With simplified data access and streamlined processes, Aviva has significantly reduced the time previously spent on data processing. This efficiency enhancement has facilitated more effective portfolio analysis, empowering Aviva to make data-driven decisions promptly.

Transition from Excel spreadsheets to hx Renew

Recognizing the need for rapid development and iteration of pricing models while maintaining accuracy and stability, Aviva sought external solutions and ultimately selected hx Renew. This transition from Excel spreadsheets to an intelligent and agile platform has proven essential for Aviva’s ability to meet the evolving business needs and stay ahead in the competitive insurance landscape.

Improved Decision-Making and Responsiveness

Shyam Bhayani, Head of Pricing in Aviva’s Global Corporate & Specialty team, enthuses about the impact of improved data analysis afforded by hx Renew. Bhayani states, “We’re able to quickly identify areas where the business isn’t performing and where decisions are needed simply because we have more data.” This enhanced decision-making capability has empowered Aviva to respond promptly to business needs and make more informed decisions.

Achievements and Future Prospects

Aviva’s ability to build 20 pricing models within a span of nine months is a testament to their commitment to innovation and efficiency. This remarkable feat highlights the transformative potential of utilizing intelligent platforms like hx Renew in the insurance industry.

Looking toward the future, the GCS team at Aviva has set their sights on unlocking the full value of hx Renew’s decision intelligence capabilities through wider systems integrations and the application of machine learning. These advancements will undoubtedly provide Aviva with a competitive edge, enabling them to further optimize their pricing strategies, enhance customer satisfaction, and drive business growth.

Aviva’s adoption of hx Renew has not only revolutionized their insurance pricing model creation process but has also enhanced their decision-making capabilities and responsiveness. By leveraging the power of hx Renew’s intelligent platform, Aviva has expedited the creation of pricing models, streamlined data access and processing, and made more informed and prompt business decisions. As Aviva continues to push the boundaries of innovation, their partnership with hx Renew sets the stage for a future marked by greater efficiency, accuracy, and business growth in the insurance industry.

Explore more

AI and Generative AI Transform Global Corporate Banking

The high-stakes world of global corporate finance has finally severed its ties to the sluggish, paper-heavy traditions of the past, replacing the clatter of manual data entry with the silent, lightning-fast processing of neural networks. While the industry once viewed artificial intelligence as a speculative luxury confined to the periphery of experimental “innovation labs,” it has now matured into the

Is Auditability the New Standard for Agentic AI in Finance?

The days when a financial analyst could be mesmerized by a chatbot simply generating a coherent market summary have vanished, replaced by a rigorous demand for structural transparency. As financial institutions pivot from experimental generative models to autonomous agents capable of managing liquidity and executing trades, the “wow factor” has been eclipsed by the cold reality of production-grade requirements. In

How to Bridge the Execution Gap in Customer Experience

The modern enterprise often functions like a sophisticated supercomputer that possesses every piece of relevant information about a customer yet remains fundamentally incapable of addressing a simple inquiry without requiring the individual to repeat their identity multiple times across different departments. This jarring reality highlights a systemic failure known as the execution gap—a void where multi-million dollar investments in marketing

Trend Analysis: AI Driven DevSecOps Orchestration

The velocity of software production has reached a point where human intervention is no longer the primary driver of development, but rather the most significant bottleneck in the security lifecycle. As generative tools produce massive volumes of functional code in seconds, the traditional manual review process has effectively crumbled under the weight of machine-generated output. This shift has created a

Navigating Kubernetes Complexity With FinOps and DevOps Culture

The rapid transition from static virtual machine environments to the fluid, containerized architecture of Kubernetes has effectively rewritten the rules of modern infrastructure management. While this shift has empowered engineering teams to deploy at an unprecedented velocity, it has simultaneously introduced a layer of financial complexity that traditional billing models are ill-equipped to handle. As organizations navigate the current landscape,