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Case Study: SAS Containerisation Enables Percayso Inform to Improve Data Enrichment for the Insurance Industry

Critical implementation of SAS software to support Percayso Inform in realising its goal of delivering enriched data for customers in the insurance industry. This is developed using bespoke data modelling of customer profiles and insurance data.

SAS containerisation crop

About Percayso Inform

Percayso Inform is a start-up service provider with big ambitions. This boutique services the insurance and personal finance industry, enriching their data to enhance critical customer insights. Percayso Inform identifies correlations between individual customer profiles and insurance data. This involves consented, public and private data. The B2B arm of the business combines credit bureau data with information from other financial products, such as mortgages, credit cards, loans, etc, to provide the next level of insights to brokers and insurance companies. This helps these businesses to make the best choices for them. For example, this may be better identifying those individuals who are least likely to default on payment, or those who are most likely to become a loyal customer.

The majority of Percayso Inform’s business infrastructure is hosted in the cloud to reduce the requirement for physical hardware. This reflects their ethos of being a “green business” with a minimised hardware footprint.

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As a new business, Percayso Inform was using a range of software, file formats and programming languages to store and process its data. This included Microsoft Office and Google Cloud products and CSV and flat files. The team started out using R Studio to conduct its analysis and modelling, however, the models created did not perform anywhere near well enough. The complexity of the analysis being undertaken by Percayso Inform demanded more sophisticated platform capabilities than those R Studio could offer.

Percayso Inform needed greater confidence in the value of the insights being produced. As such, the decision was made to migrate future modelling to SAS.


Percayso Inform wanted a software solution that could model large amounts of data from disparate sources. Such modelling would be conducted with the aim of proving a causal link between bureau data and individuals’ behaviour. The output generated should summarise insights for any individual at any stage in their journey with a financial services provider, whether they are requesting a quote; making a mid-term adjustment; cancelling a contract or making a claim.

Any solution must be containerised to ensure Percayso Inform can continue to pursue its goal of being a “green” business. Amadeus worked with the business to identify the appropriate software and set-up required for an environment that would best serve the business and allow them to achieve their objectives.

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Having successfully completed this project, Percayso Inform has the capabilities to deliver fully bespoke data enrichment to its customers, in turn enabling them to better assess risk and more effectively service their customers. Ultimately, this information ensured Percayso Inform’s financial services customers could reduce losses and make better-informed decisions regarding individual customers.

Resulting decisions and insight include customer behaviour (such as understanding how to covert new customers to loyal customers), data segmentation, credit risk decisions and the identification of differences between key groups of customers. This enables the insurers and brokers to reduce claims, win better business, retain customers more profitably and drive down loss ratios.

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