Global Insurance carriers often grapple with the ability to address product pricing in small markets. The data challenge ranges from gathering data from multiple omni-channel sources, to a lack of a conformed data in the data warehouse. Moreover, the growing number of disparate new data sources, including large amounts of web data, make it difficult to remain nimble--a challenge compounded by the limited financial and staffing resources.
Enter Promethium. The California based software firm has cracked the code on quickly and effectively making the data available in an analytics environment. Using advanced AI, Machine Learning, and Natural Language Processing (NLP), Promethium eliminates the current pain and cost of BI and Analytics solutions, allowing you to start by asking the question you most care to answer.
Large companies face slow time-to-market for innovation
While insurance carriers are faced with significant competition across all domains, the pressure in the P&C Auto and Home consumer markets is particularly intense, largely due to nimble InsurTechs who provide the coverage needed at reasonable premiums. As this competitive pressure propagates, large carriers are faced with the need to create better products for their existing customers and prospects, which have not only the needed coverage but also the possibility of additional riders. Calculating risk models at product innovation time requires that actuaries analyze data from multiple, disparate internal and external sources.
These distributed sources may not have all the data conformed in a data warehouse, making the amount of preparation required prior to analysis tremendous--this is especially true in smaller markets. As a result, established carriers are at a disadvantage in terms of time-to-market for new innovations and products.
The difficulty of dynamic pricing
Moreover, the imperative for insurance carriers to adapt to the new technological, market-driven and consumer complexities with near-real time dynamic pricing is a critical success factor for several reasons. In addition to new entrants bringing better and more focused propositions, as well as technology disruptors that enable new pricing models, companies face growing demand for price and value transparency, a more informed consumer population, and regulatory pressures that impact profitability.
Removing the manual labor from actuarial analysis
Companies are faced with a world of options for solving these problems with technology, from creating data marts to bringing the data into Excel. However, most require a continuous sourcing that often impairs the need to nimbly adapt to competitive pressures.
There is a nimble alternative: Promethium. Using advanced AI, Machine Learning, and Natural Language Processing (NLP), Promethium eliminates the current pain and cost of BI and Analytics solutions. The power that this solution gives Actuaries is significant.
Over the years, the experience of “crunching” the data for review experience was lengthy, frustrating and resource intensive. Promethium allows users to not merely locate the right data, but get full answers to questions posed in plain language.
Ask a question in plain English and it automatically locates the necessary data across multiple systems and databases it, determines its quality, and ensures governance. Once the right data sources have been located, it generates a SQL statement that will assemble the data across multiple databases, data lakes, marts and warehouses. This nearly eliminates the manual labor associated with analyzing and governing data, reducing the time it takes to answer a question from months to minutes.
By using Promethium, carriers’ product innovation teams will be able to more effectively and timely review data from sales engines, address price optimization, and determine pricing for new products.