The applications provide quick visual access to an always-updated stream of data: transaction information that can be explored by geography, time, single merchant, or merchant categories, while branch activities can always be analyzed by client type (branch client, bank client, non-client), by type of service (atm, desk, self service) and organized over time or by geographical aggregates. To allow a wide range of internal users to perform a complete and critical analysis of this data, Accurat designed a simple interface based on interactive maps, customizable timelines, and a list of suggested KPIs based on performance. The geographical exploration of credit and debit cards’ data allows for the visualization of information at different spatial granularities; starting from an overview of the entire country, users can navigate to more specific areas, down to the district level. During the navigation of the different geographical levels, transactions can be viewed as an aggregate for the selected area. With a similar logic, the selected time frame can be modified freely at any zoom level thanks to a standardized calendar, enhancing the analysis around the transactional data and enabling the visualization of day-to-day trends. At any time, the information visualized in the application can be filtered by merchant or client category. The color-coding and the additional information on the merchant’s ATECO code (the Italian ISIC code) help to group the data and allow exploration of the transactions at a specific geographical level (a specific city, for example) by comparing its product categories. To allow users to dive even deeper in the transactions dataset, Accurat imagined and designed a “Merchant Summary” section of the tool; this view collects all the useful data around a specific merchant (type of merchant, type of account, group that owns the merchant) and enables the comparison between its transactions and the ones performed on average at other merchants of the same brand or of the same product category. When exploring physical branch activity, instead, users of the application can easily compare traffic data between locations or over time and break it down by service or by customer segmentation, focusing on either absolute or percentage values to map the interactions between the bank and its customers.