data

I’m excited that the ski season is about to start where my family and I live in Northern California. I’m even more excited we’ve arrived at Banff, the second release in Guidewire’s bi-annual release cadence! In June we released Aspen, the most important release in Guidewire’s history, where we introduced Guidewire Cloud Platform and reimagined core platforms. ... Read More >
Despite the high-profile nature of cybercrime, risk transfer has barely scratched the surface of this peril, with cyber insurance accounting for approximately 0.3% of the global property and casualty market. What is holding insurers back from this potentially profitable market? ... Read More >
The first part in our series on taming the uncertainty of ransomware risk spotlighted a playbook approach to reduce the conceptual uncertainty surrounding ransomware risk. In this sequel, we drill down to offer a risk factor-based approach to help tame the empirical uncertainty surrounding this cyber risk. ... Read More >
It has been difficult for the insurance industry to formulate a proper vision for their use of predictive analytics. Executives who set their company’s direction tend not to understand the scope of what is possible and lack direct experience with the benefits and challenges. Conversely, those who do have more experience and understanding tend not to be in a position to establish a corporate-wide vision. ... Read More >
La version Aspen de Guidewire InsuranceSuite fait entrer les assureurs IARD dans une nouvelle dimension et leur permet d’atteindre une agilité jamais vue auparavant. Grâce à des solutions qui permettent une réelle autonomie aux utilisateurs métier, accélèrent le lancement de produits et facilitent la transformation numérique.... Read More >
Predictive analytics involves just that: prediction of the future. It is an inherently uncertain activity. While there are any number of metrics that can convince that a predictive model will indeed provide useful information, nothing proves the value to an organization as much as a verified success story. In addition, even good predictive models can begin to deteriorate over time as the data on which it is based gets older and older. A need exists to track this to know when to update a model. ... Read More >
Collecting and analyzing data does not provide business value. Improved business processes that are more accurate and efficient provide business value. Without embedding a predictive model into a relevant business process, all the work and cost put into predictive analytics will be for nothing. Yet the implementation of predictive models has been an afterthought for many insurers. ... Read More >
Business intelligence looks at historical data to provide information about a company’s operations and performance. This can provide valuable insight but has limitations for predicting the future. Simply looking at historical patterns does not tell us how much of what we see in the data is a reliable pattern that can be depended on to continue – what we will refer to as “Signal” – and how much is due to random chance or unknown variables – what we will refer to as “Noise”.  ... Read More >
Data is a purpose-driven asset. It is collected for specific reasons to meet specific needs. The structure of a given set of data is driven by the immediate purpose as well. Data models used to create efficient daily processing are not those used for efficient storing, and yet the structures which facilitate easy access for reporting and business intelligence are different. ... Read More >
At the time of this blog’s publication, Guidewire customers are processing tens of thousands of insurance claims for the devastating wildfires in California, Oregon, and Washington.  The claims are not just for homes and businesses destroyed, but also for smoke contamination, contents damage, and living expenses due to evacuation orders.  ... Read More >

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