Risk assessment is crucial for financial institutions, especially financial holding companies (FHCs), due to the inherent organizational complexity and systemic risks embedded in their interconnected structures. We propose a general and flexible disclosure-to-network framework that integrates topic modeling and network analysis to construct a risk-similarity financial network from firms' textual risk disclosures. The key idea is to convert unstructured narratives into firm-year risk representations and define inter-firm links based on similarity in disclosed risk exposures, yielding connectedness measures that are comparable across institutions and trackable over time. We employ Sentence Latent Dirichlet Allocation as a robust topic modeling approach on risk disclosure text in Chinese FHC annual reports from 2013 to 2020. We document a sustained rise in interconnectedness with spikes around the 2015-2016 market turmoil and later regulatory tightening. Banks are the most connected entities; subsidiaries are more interconnected than parents; and cross-sector subsidiary linkages are stronger within the same holding group. Higher connectedness is associated with lower profitability and higher bankruptcy risk, highlighting implications for systemic-risk monitoring.