Creating an Analytical Data Model for Banking Supervision

In banking supervision the emphasis has moved from scrutiny of financial statements at a point-in-time to being more analytical, e.g. observing differences over time, individual firms, and variables. But, complicating the analysis, the firms can submit data at different frequencies and their financial years do not always align with the calendar year. KNIME Analytics Platform is used to get the data on the same basis – for example to interpolate quarterly submissions into monthly, to calculate CYTD out of FYTD, to create rolling 12-month variables, and more. The KNIME workflow is deployed via KNIME Server, which pushes the prepared data to Tableau Server (using the native Tableau Integration), where it is underpinning standardized dashboards and enables supervisors to perform flexible ad-hoc analysis.

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Creating an Analytical Data Model for Banking Supervision

Perttu Heikki Korhonen from the Qatar Financial Centre Regulatory Authority (QFCRA) explains how his team built a solution for banking supervisors to analyze banking data more efficiently and effectively.

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