A holistic and persistent view of the customer

Ascent has created a platform that merges internal and external financial information into a holistic and persistent view of the customer: the Permissioned Data Core. The platform is available to financial institutions out-of-the-box, with virtually no IT resources required.

It enables intelligent analysis of customer information, as well as repurposing and secure sharing of subsets of data, both internally and externally, in service to the customer. At all times, data access and sharing are permissioned by the customer through a trusted relationship with their financial institution.

Three key aspects of how Ascent approaches data within the Permissioned Data Core include collecting and curating, validating and deduplication, and analyzing and predicting.

Collecting & Curating

Automated collection and curation of financial data from a vast host of APIs is the foundation of the Permissioned Data Core. This includes initial processing of the data and managing the storage of the data over time. Various techniques, including incremental updates and archiving, are used to ensure the efficient and consistent collection and storage of financial data over time as part of our cloud-native platform. Our implementation allows datafication of many verification processes, giving much faster and more accurate results than traditional methods.

Validating & Deduplication

Automating the validation of data and its deduplication is key to ensuring the integrity of the data that we store and use for verification processes. While our collection methods give us an advantage in the volume of data available, validating that data is key to turning the larger volume of data into a measure of confidence in a given data point. Furthermore, deduplication protects the system against accidental or malicious manipulation of data in order to falsely represent a customer’s information (assets or income for example). Together, these validation and deduplication algorithms provide measurable metrics on confidence in collected data, a key area to understand in verification processes.

Analyzing & Predicting

Process improvement through actionable analytics is another key area of the Permissioned Data Core. Data mining improves understanding of current client processes and why they fail when they do. Machine learning models can be trained on all of the data we’ve collected to create artificial intelligence that can act as early warning systems or predict outcomes on current or potential customers. Furthermore, data analysis allows us to understand customer needs better, and provides metrics on what customers want at different points in their life cycles. With access to holistic customer data, we can augment our client’s internal workflows with insights and recommendations.