UNLEASH THE POWER OF ECOSYSTEM THINKING
Cross-enterprise data analytics can generate new insight into customer behaviour, leading to unprecedented selling opportunities and de-risked business decisions. This is especially true when combining such information as identity, location history, spending habits, social media, etc. for an all-encompassing view. Can it be done with complete privacy and confidentiality?
Exchanging data about customers is often under purview of highly punitive privacy-protecting regulations. Data leaks are frequent. Moreover, customer information often serves as the basis for competitive advantages that companies would not want to share.
“New approaches to computation, such that would maintain confidentiality, are necessary to uncover new capabilities and find the right balance between confidentiality, security, and adherence to regulations.” – Gartner
DGT Network uses privacy enhancing technologies (PET) to facilitate anonymous exchanges of information and availability of insight without revealing the sensitive data underneath to any party. DGT’s algorithm combines SMPC, k-Anonymity, ML-Based Anonymity, ZKP and other methods to ensure the privacy, confidentiality, and utility of data as per the requirements of consumers, enterprises, and regulators.
Some examples:
• Marketing attribution – multi-company insight based on sensitive customer data for unprecedented analysis of purchase patterns and cross-selling opportunities without breaking privacy or confidentiality. Ex. Linking identity to location, spending, social media activity.
• Business intelligence products – AI-powered SME decision recommendations based on purchase patterns, social media, location, spending, etc. Ex. AI-based recommendations of success likeliness based on location on where to open a store.
• Credit scoring data ecosystem – data-enriched view for more accurate decisions and reduction of risk as compared to traditional rudimentary formulas based on the few factors known. Ex. Lending, insurance, health reward ecosystems, etc.