SELECT APPLICATION:
Risk & Compliance
Application:Business Insurance UnderwritingPersona:VP Marketing, VP UnderwritingCustomer:US Insurance Company
Customer Situation:Our client underwrites insurance for a company’s online presence. They required a global view of each business’s digital footprint to assess risk. Key insurance prospects needed to be identified based on their network configuration. They required an understanding of their existing customers’ risk profiles for underwriting assessment and rate setting.Solution:Profound first assigned domains to each customer record. From the domain, Profound appended DBI (Digital Business Intelligence) with an emphasis on DBI Density—the number of devices on the network, the strength of SSL certificates, email servers, e-commerce vendors, and more. By utilizing Domain Clustering we were also able to identify the number of domains associated with each customer to determine the full digital presence of the enterpriseResults:DBI allowed the customer to identify the most sophisticated networks, enabling them to realign underwriting rates and identify new customers to upsell. The client was also able to prioritize prospects based on identified installed technologies and improve rate settings.
Application:SMB Credit Loan Risk AssessmentPersona:CDO, VP Credit Risk, VP SalesCustomer:US Business Credit Risk Company
Customer Situation:Client needed to identify attributes that would assess and predict risk for companies applying for SMB loans. The attributes had to be actual, not modeled data. Client also required proxy data sources that backfill information gaps for incomplete or non-existent payment history.Solution:Profound appended Digital Business Intelligence with over 60 attributes to the SMB customer file and appended 1 year archive and current data to each matched customer record.Results:The customer’s analytics team identified 4 powerful, predictive attributes that positively predicted SMB loan risk. By tracking a company’s network configuration and installed IT over time, the client improved their credit decisioning.
Application:Current Portfolio Risk AssessmentPersona:SVP Sales, CMO, CDO, Market IntelligenceCustomer:Global Fortune 100 Hi-Tech Company
Customer Situation:Client has a large global portfolio of companies that purchase On-Prem hardware and services. They needed to identify customers who were moving to cloud applications to determine the risk associated with the existing revenue based on On-Prem networks.Solution:Profound appended Cloud Transformation Journey scores to each customer record. This resulted in a 75% match rate. Archive and current data was appended with quarterly updates to capture trends. This produced valuable insight for the client insight into cloud services adoption.Results:Client developed a sales strategy to better-understand customer cloud buying adoption Risk of Portfolio was established with greater insight into Cloud Migration. Targeted campaigns and customer engagement was designed to upsell and position accurate product solutions.