Under　the　influence　of　COVID-19,　although　upstream　small-　and　medium-sized　enterprises　(SMEs)　in　construction　industry　chain　suffer　from　high　operating　costs　and　tight　cash　flow　problems,　their　financing　demands　are　even　stronger.　As　an　electronic　and　platform-based　comprehensive　service,　online　supply　chain　finance　can　ease　the　financing　problems　of　SMEs　in　the　construction　industry.　However,　it　has　become　an　important　issue　for　financial　institutions　to　effectively　assess　the　credit　risk　in　the　process　of　online　supply　chain　financing.　In　this　paper,　an　online　supply　chain　risk　assessment　method,　which　is　based　on　a　hybrid　model　chain,　including　eXtreme　Gradient　Boosting　(XGBoost),　Synthetic　Minority　Oversampling　TEchnique　for　Nominal　and　Continuous　(SMOTENC),　and　Random　Forest　(RF),　is　proposed　to　identify　and　control　the　credit　risk　of　financial　institutions.　Specifically,　we　establish　the　financial　credit　risk　assessment　system　with　respect　to　the　characteristics　of　financing　enterprises　in　the　construction　industry　supply　chain,　including　the　status　of　financing　enterprises,　the　status　of　core　enterprises,　the　operating　status　of　the　supply　chain,　and　the　status　of　assets　under　financing.　On　the　basis　of　the　system,　the　best　index　number　of　the　assessment　system　and　the　minority　samples　are　obtained　by　the　XGBoost　algorithm　and　the　SMOTENC　algorithm,　respectively.　The　classification　method　based　on　RF　is　applied　to　judge　the　credit　risk　of　financing　enterprises　in　the　supply　chain　of　construction　industry.　In　the　simulation　stage,　we　take　upstream　SMEs　in　the　supply　chain　of　construction　industry　in　China　as　an　example　for　empirical　analysis　to　validate　the　effectiveness　of　our　proposed　method.　The　credit　risk　assessment　method　proposed　in　this　paper　has　better　performance　than　the　commonly　used　ones　in　the　academic　field　with　an　average　improvement　on　assessment　accuracy　for　6.39%　and　an　average　increase　of　Area　Under　Curve　for　6.95%.　Our　study　provides　meaningful　exploration　on　the　fund　monitoring　system　of　the　financing　service　platform　to　improve　financing　efficiency　and　risk　management　level.