iVOD / 169896

Field Value
IVOD_ID 169896
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/169896
日期 2026-06-10
會議資料.會議代碼 委員會-11-5-20-18
會議資料.會議代碼:str 第11屆第5會期財政委員會第18次全體委員會議
會議資料.屆 11
會議資料.會期 5
會議資料.會次 18
會議資料.種類 委員會
會議資料.委員會代碼[0] 20
會議資料.委員會代碼:str[0] 財政委員會
會議資料.標題 第11屆第5會期財政委員會第18次全體委員會議
影片種類 Clip
開始時間 2026-06-10T09:33:22+08:00
結束時間 2026-06-10T09:44:16+08:00
影片長度 00:10:54
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/dee24285c0428ea5cb849592f909dcf021dd72608bfb9572a83ef3dae05f68236b54fa05dac5ead05ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 賴士葆
委員發言時間 09:33:22 - 09:44:16
會議時間 2026-06-10T09:00:00+08:00
會議名稱 立法院第11屆第5會期財政委員會第18次全體委員會議(事由:一、審查中華民國115年度中央政府總預算案附屬單位預算營業部分關於中央銀行(含中央造幣廠、中央印製廠)。(詢答及處理) 二、審查中華民國115年度中央政府總預算案附屬單位預算營業部分,關於財政部主管中國輸出入銀行、臺灣金融控股股份有限公司(含臺灣銀行股份有限公司、臺銀人壽保險股份有限公司、臺銀綜合證券股份有限公司)。(僅詢答) 【6月10日及11日兩天一次會】 【預算提案截止時間:第一案6月10日(三)上午10時,第二案6月10日(三)下午5時】)
transcript.pyannote[0].speaker SPEAKER_02
transcript.pyannote[0].start 3.72659375
transcript.pyannote[0].end 5.56596875
transcript.pyannote[1].speaker SPEAKER_02
transcript.pyannote[1].start 6.05534375
transcript.pyannote[1].end 9.83534375
transcript.pyannote[2].speaker SPEAKER_01
transcript.pyannote[2].start 9.83534375
transcript.pyannote[2].end 12.01221875
transcript.pyannote[3].speaker SPEAKER_01
transcript.pyannote[3].start 15.10034375
transcript.pyannote[3].end 16.01159375
transcript.pyannote[4].speaker SPEAKER_01
transcript.pyannote[4].start 16.55159375
transcript.pyannote[4].end 16.56846875
transcript.pyannote[5].speaker SPEAKER_02
transcript.pyannote[5].start 16.56846875
transcript.pyannote[5].end 18.07034375
transcript.pyannote[6].speaker SPEAKER_02
transcript.pyannote[6].start 18.39096875
transcript.pyannote[6].end 19.09971875
transcript.pyannote[7].speaker SPEAKER_02
transcript.pyannote[7].start 19.74096875
transcript.pyannote[7].end 22.32284375
transcript.pyannote[8].speaker SPEAKER_02
transcript.pyannote[8].start 22.98096875
transcript.pyannote[8].end 24.34784375
transcript.pyannote[9].speaker SPEAKER_02
transcript.pyannote[9].start 25.41096875
transcript.pyannote[9].end 25.74846875
transcript.pyannote[10].speaker SPEAKER_02
transcript.pyannote[10].start 25.90034375
transcript.pyannote[10].end 26.27159375
transcript.pyannote[11].speaker SPEAKER_02
transcript.pyannote[11].start 26.86221875
transcript.pyannote[11].end 29.14034375
transcript.pyannote[12].speaker SPEAKER_02
transcript.pyannote[12].start 29.61284375
transcript.pyannote[12].end 31.46909375
transcript.pyannote[13].speaker SPEAKER_02
transcript.pyannote[13].start 32.68409375
transcript.pyannote[13].end 35.46846875
transcript.pyannote[14].speaker SPEAKER_00
transcript.pyannote[14].start 36.17721875
transcript.pyannote[14].end 37.27409375
transcript.pyannote[15].speaker SPEAKER_02
transcript.pyannote[15].start 37.27409375
transcript.pyannote[15].end 37.30784375
transcript.pyannote[16].speaker SPEAKER_00
transcript.pyannote[16].start 37.30784375
transcript.pyannote[16].end 37.62846875
transcript.pyannote[17].speaker SPEAKER_02
transcript.pyannote[17].start 37.62846875
transcript.pyannote[17].end 37.64534375
transcript.pyannote[18].speaker SPEAKER_00
transcript.pyannote[18].start 37.64534375
transcript.pyannote[18].end 60.76409375
transcript.pyannote[19].speaker SPEAKER_02
transcript.pyannote[19].start 37.66221875
transcript.pyannote[19].end 38.08409375
transcript.pyannote[20].speaker SPEAKER_02
transcript.pyannote[20].start 61.18596875
transcript.pyannote[20].end 64.64534375
transcript.pyannote[21].speaker SPEAKER_02
transcript.pyannote[21].start 65.23596875
transcript.pyannote[21].end 66.28221875
transcript.pyannote[22].speaker SPEAKER_02
transcript.pyannote[22].start 66.58596875
transcript.pyannote[22].end 68.74596875
transcript.pyannote[23].speaker SPEAKER_02
transcript.pyannote[23].start 69.15096875
transcript.pyannote[23].end 70.24784375
transcript.pyannote[24].speaker SPEAKER_00
transcript.pyannote[24].start 70.24784375
transcript.pyannote[24].end 70.70346875
transcript.pyannote[25].speaker SPEAKER_02
transcript.pyannote[25].start 70.70346875
transcript.pyannote[25].end 70.72034375
transcript.pyannote[26].speaker SPEAKER_00
transcript.pyannote[26].start 71.17596875
transcript.pyannote[26].end 91.91534375
transcript.pyannote[27].speaker SPEAKER_02
transcript.pyannote[27].start 80.45721875
transcript.pyannote[27].end 80.86221875
transcript.pyannote[28].speaker SPEAKER_02
transcript.pyannote[28].start 90.26159375
transcript.pyannote[28].end 91.24034375
transcript.pyannote[29].speaker SPEAKER_02
transcript.pyannote[29].start 91.27409375
transcript.pyannote[29].end 91.79721875
transcript.pyannote[30].speaker SPEAKER_02
transcript.pyannote[30].start 91.91534375
transcript.pyannote[30].end 97.58534375
transcript.pyannote[31].speaker SPEAKER_00
transcript.pyannote[31].start 97.58534375
transcript.pyannote[31].end 97.75409375
transcript.pyannote[32].speaker SPEAKER_02
transcript.pyannote[32].start 97.75409375
transcript.pyannote[32].end 98.02409375
transcript.pyannote[33].speaker SPEAKER_00
transcript.pyannote[33].start 98.02409375
transcript.pyannote[33].end 98.37846875
transcript.pyannote[34].speaker SPEAKER_00
transcript.pyannote[34].start 98.53034375
transcript.pyannote[34].end 100.42034375
transcript.pyannote[35].speaker SPEAKER_00
transcript.pyannote[35].start 100.55534375
transcript.pyannote[35].end 109.90409375
transcript.pyannote[36].speaker SPEAKER_02
transcript.pyannote[36].start 103.20471875
transcript.pyannote[36].end 103.72784375
transcript.pyannote[37].speaker SPEAKER_02
transcript.pyannote[37].start 104.03159375
transcript.pyannote[37].end 104.72346875
transcript.pyannote[38].speaker SPEAKER_01
transcript.pyannote[38].start 105.02721875
transcript.pyannote[38].end 105.70221875
transcript.pyannote[39].speaker SPEAKER_01
transcript.pyannote[39].start 106.56284375
transcript.pyannote[39].end 106.57971875
transcript.pyannote[40].speaker SPEAKER_02
transcript.pyannote[40].start 106.57971875
transcript.pyannote[40].end 107.38971875
transcript.pyannote[41].speaker SPEAKER_02
transcript.pyannote[41].start 108.43596875
transcript.pyannote[41].end 116.08034375
transcript.pyannote[42].speaker SPEAKER_02
transcript.pyannote[42].start 116.53596875
transcript.pyannote[42].end 124.95659375
transcript.pyannote[43].speaker SPEAKER_02
transcript.pyannote[43].start 125.78346875
transcript.pyannote[43].end 126.59346875
transcript.pyannote[44].speaker SPEAKER_02
transcript.pyannote[44].start 127.03221875
transcript.pyannote[44].end 127.62284375
transcript.pyannote[45].speaker SPEAKER_02
transcript.pyannote[45].start 128.12909375
transcript.pyannote[45].end 129.19221875
transcript.pyannote[46].speaker SPEAKER_02
transcript.pyannote[46].start 129.51284375
transcript.pyannote[46].end 130.91346875
transcript.pyannote[47].speaker SPEAKER_02
transcript.pyannote[47].start 131.57159375
transcript.pyannote[47].end 132.28034375
transcript.pyannote[48].speaker SPEAKER_02
transcript.pyannote[48].start 132.71909375
transcript.pyannote[48].end 134.18721875
transcript.pyannote[49].speaker SPEAKER_02
transcript.pyannote[49].start 134.52471875
transcript.pyannote[49].end 135.97596875
transcript.pyannote[50].speaker SPEAKER_02
transcript.pyannote[50].start 137.10659375
transcript.pyannote[50].end 138.42284375
transcript.pyannote[51].speaker SPEAKER_01
transcript.pyannote[51].start 139.80659375
transcript.pyannote[51].end 142.96221875
transcript.pyannote[52].speaker SPEAKER_02
transcript.pyannote[52].start 140.75159375
transcript.pyannote[52].end 141.12284375
transcript.pyannote[53].speaker SPEAKER_02
transcript.pyannote[53].start 143.75534375
transcript.pyannote[53].end 148.05846875
transcript.pyannote[54].speaker SPEAKER_01
transcript.pyannote[54].start 148.05846875
transcript.pyannote[54].end 148.07534375
transcript.pyannote[55].speaker SPEAKER_02
transcript.pyannote[55].start 148.07534375
transcript.pyannote[55].end 148.39596875
transcript.pyannote[56].speaker SPEAKER_01
transcript.pyannote[56].start 148.39596875
transcript.pyannote[56].end 149.22284375
transcript.pyannote[57].speaker SPEAKER_02
transcript.pyannote[57].start 149.22284375
transcript.pyannote[57].end 149.99909375
transcript.pyannote[58].speaker SPEAKER_01
transcript.pyannote[58].start 150.23534375
transcript.pyannote[58].end 150.50534375
transcript.pyannote[59].speaker SPEAKER_02
transcript.pyannote[59].start 151.07909375
transcript.pyannote[59].end 152.09159375
transcript.pyannote[60].speaker SPEAKER_01
transcript.pyannote[60].start 152.12534375
transcript.pyannote[60].end 154.01534375
transcript.pyannote[61].speaker SPEAKER_02
transcript.pyannote[61].start 153.47534375
transcript.pyannote[61].end 159.83721875
transcript.pyannote[62].speaker SPEAKER_01
transcript.pyannote[62].start 156.22596875
transcript.pyannote[62].end 156.46221875
transcript.pyannote[63].speaker SPEAKER_01
transcript.pyannote[63].start 159.88784375
transcript.pyannote[63].end 160.12409375
transcript.pyannote[64].speaker SPEAKER_02
transcript.pyannote[64].start 160.44471875
transcript.pyannote[64].end 162.16596875
transcript.pyannote[65].speaker SPEAKER_02
transcript.pyannote[65].start 162.63846875
transcript.pyannote[65].end 165.15284375
transcript.pyannote[66].speaker SPEAKER_01
transcript.pyannote[66].start 166.28346875
transcript.pyannote[66].end 177.96096875
transcript.pyannote[67].speaker SPEAKER_03
transcript.pyannote[67].start 173.18534375
transcript.pyannote[67].end 173.28659375
transcript.pyannote[68].speaker SPEAKER_02
transcript.pyannote[68].start 180.47534375
transcript.pyannote[68].end 183.90096875
transcript.pyannote[69].speaker SPEAKER_01
transcript.pyannote[69].start 181.94346875
transcript.pyannote[69].end 183.81659375
transcript.pyannote[70].speaker SPEAKER_01
transcript.pyannote[70].start 183.90096875
transcript.pyannote[70].end 184.05284375
transcript.pyannote[71].speaker SPEAKER_02
transcript.pyannote[71].start 184.05284375
transcript.pyannote[71].end 186.56721875
transcript.pyannote[72].speaker SPEAKER_01
transcript.pyannote[72].start 184.60971875
transcript.pyannote[72].end 189.23346875
transcript.pyannote[73].speaker SPEAKER_02
transcript.pyannote[73].start 188.54159375
transcript.pyannote[73].end 188.76096875
transcript.pyannote[74].speaker SPEAKER_02
transcript.pyannote[74].start 189.04784375
transcript.pyannote[74].end 198.05909375
transcript.pyannote[75].speaker SPEAKER_03
transcript.pyannote[75].start 198.05909375
transcript.pyannote[75].end 198.31221875
transcript.pyannote[76].speaker SPEAKER_02
transcript.pyannote[76].start 198.31221875
transcript.pyannote[76].end 198.39659375
transcript.pyannote[77].speaker SPEAKER_02
transcript.pyannote[77].start 198.54846875
transcript.pyannote[77].end 200.62409375
transcript.pyannote[78].speaker SPEAKER_03
transcript.pyannote[78].start 200.62409375
transcript.pyannote[78].end 200.99534375
transcript.pyannote[79].speaker SPEAKER_02
transcript.pyannote[79].start 200.99534375
transcript.pyannote[79].end 202.56471875
transcript.pyannote[80].speaker SPEAKER_02
transcript.pyannote[80].start 202.88534375
transcript.pyannote[80].end 203.15534375
transcript.pyannote[81].speaker SPEAKER_02
transcript.pyannote[81].start 203.18909375
transcript.pyannote[81].end 203.22284375
transcript.pyannote[82].speaker SPEAKER_02
transcript.pyannote[82].start 203.32409375
transcript.pyannote[82].end 205.36596875
transcript.pyannote[83].speaker SPEAKER_02
transcript.pyannote[83].start 206.32784375
transcript.pyannote[83].end 207.94784375
transcript.pyannote[84].speaker SPEAKER_01
transcript.pyannote[84].start 208.11659375
transcript.pyannote[84].end 208.13346875
transcript.pyannote[85].speaker SPEAKER_02
transcript.pyannote[85].start 208.13346875
transcript.pyannote[85].end 209.53409375
transcript.pyannote[86].speaker SPEAKER_01
transcript.pyannote[86].start 209.19659375
transcript.pyannote[86].end 209.24721875
transcript.pyannote[87].speaker SPEAKER_01
transcript.pyannote[87].start 209.53409375
transcript.pyannote[87].end 209.55096875
transcript.pyannote[88].speaker SPEAKER_01
transcript.pyannote[88].start 209.85471875
transcript.pyannote[88].end 209.97284375
transcript.pyannote[89].speaker SPEAKER_02
transcript.pyannote[89].start 210.98534375
transcript.pyannote[89].end 211.33971875
transcript.pyannote[90].speaker SPEAKER_02
transcript.pyannote[90].start 211.57596875
transcript.pyannote[90].end 212.38596875
transcript.pyannote[91].speaker SPEAKER_01
transcript.pyannote[91].start 212.38596875
transcript.pyannote[91].end 234.61034375
transcript.pyannote[92].speaker SPEAKER_01
transcript.pyannote[92].start 235.35284375
transcript.pyannote[92].end 236.34846875
transcript.pyannote[93].speaker SPEAKER_01
transcript.pyannote[93].start 236.51721875
transcript.pyannote[93].end 236.53409375
transcript.pyannote[94].speaker SPEAKER_02
transcript.pyannote[94].start 236.53409375
transcript.pyannote[94].end 238.37346875
transcript.pyannote[95].speaker SPEAKER_02
transcript.pyannote[95].start 239.97659375
transcript.pyannote[95].end 242.45721875
transcript.pyannote[96].speaker SPEAKER_01
transcript.pyannote[96].start 242.45721875
transcript.pyannote[96].end 272.78159375
transcript.pyannote[97].speaker SPEAKER_00
transcript.pyannote[97].start 256.64909375
transcript.pyannote[97].end 256.66596875
transcript.pyannote[98].speaker SPEAKER_03
transcript.pyannote[98].start 256.66596875
transcript.pyannote[98].end 257.12159375
transcript.pyannote[99].speaker SPEAKER_00
transcript.pyannote[99].start 257.12159375
transcript.pyannote[99].end 257.57721875
transcript.pyannote[100].speaker SPEAKER_02
transcript.pyannote[100].start 271.78596875
transcript.pyannote[100].end 272.27534375
transcript.pyannote[101].speaker SPEAKER_02
transcript.pyannote[101].start 272.78159375
transcript.pyannote[101].end 273.64221875
transcript.pyannote[102].speaker SPEAKER_02
transcript.pyannote[102].start 273.89534375
transcript.pyannote[102].end 276.73034375
transcript.pyannote[103].speaker SPEAKER_02
transcript.pyannote[103].start 276.96659375
transcript.pyannote[103].end 279.37971875
transcript.pyannote[104].speaker SPEAKER_02
transcript.pyannote[104].start 279.95346875
transcript.pyannote[104].end 288.62721875
transcript.pyannote[105].speaker SPEAKER_02
transcript.pyannote[105].start 288.86346875
transcript.pyannote[105].end 289.26846875
transcript.pyannote[106].speaker SPEAKER_02
transcript.pyannote[106].start 289.48784375
transcript.pyannote[106].end 291.42846875
transcript.pyannote[107].speaker SPEAKER_02
transcript.pyannote[107].start 292.18784375
transcript.pyannote[107].end 293.01471875
transcript.pyannote[108].speaker SPEAKER_02
transcript.pyannote[108].start 293.43659375
transcript.pyannote[108].end 293.82471875
transcript.pyannote[109].speaker SPEAKER_02
transcript.pyannote[109].start 294.43221875
transcript.pyannote[109].end 297.62159375
transcript.pyannote[110].speaker SPEAKER_03
transcript.pyannote[110].start 297.75659375
transcript.pyannote[110].end 298.07721875
transcript.pyannote[111].speaker SPEAKER_02
transcript.pyannote[111].start 298.07721875
transcript.pyannote[111].end 300.59159375
transcript.pyannote[112].speaker SPEAKER_03
transcript.pyannote[112].start 300.59159375
transcript.pyannote[112].end 300.97971875
transcript.pyannote[113].speaker SPEAKER_02
transcript.pyannote[113].start 301.58721875
transcript.pyannote[113].end 302.14409375
transcript.pyannote[114].speaker SPEAKER_02
transcript.pyannote[114].start 302.63346875
transcript.pyannote[114].end 307.51034375
transcript.pyannote[115].speaker SPEAKER_03
transcript.pyannote[115].start 307.51034375
transcript.pyannote[115].end 308.05034375
transcript.pyannote[116].speaker SPEAKER_02
transcript.pyannote[116].start 307.98284375
transcript.pyannote[116].end 309.72096875
transcript.pyannote[117].speaker SPEAKER_02
transcript.pyannote[117].start 309.99096875
transcript.pyannote[117].end 312.43784375
transcript.pyannote[118].speaker SPEAKER_02
transcript.pyannote[118].start 312.45471875
transcript.pyannote[118].end 315.03659375
transcript.pyannote[119].speaker SPEAKER_03
transcript.pyannote[119].start 315.05346875
transcript.pyannote[119].end 315.55971875
transcript.pyannote[120].speaker SPEAKER_02
transcript.pyannote[120].start 315.55971875
transcript.pyannote[120].end 326.24159375
transcript.pyannote[121].speaker SPEAKER_03
transcript.pyannote[121].start 320.26784375
transcript.pyannote[121].end 320.52096875
transcript.pyannote[122].speaker SPEAKER_01
transcript.pyannote[122].start 327.06846875
transcript.pyannote[122].end 328.03034375
transcript.pyannote[123].speaker SPEAKER_01
transcript.pyannote[123].start 328.95846875
transcript.pyannote[123].end 329.05971875
transcript.pyannote[124].speaker SPEAKER_01
transcript.pyannote[124].start 330.02159375
transcript.pyannote[124].end 355.77284375
transcript.pyannote[125].speaker SPEAKER_03
transcript.pyannote[125].start 345.24284375
transcript.pyannote[125].end 345.32721875
transcript.pyannote[126].speaker SPEAKER_00
transcript.pyannote[126].start 345.32721875
transcript.pyannote[126].end 345.61409375
transcript.pyannote[127].speaker SPEAKER_03
transcript.pyannote[127].start 355.77284375
transcript.pyannote[127].end 355.85721875
transcript.pyannote[128].speaker SPEAKER_01
transcript.pyannote[128].start 356.24534375
transcript.pyannote[128].end 366.77534375
transcript.pyannote[129].speaker SPEAKER_03
transcript.pyannote[129].start 360.49784375
transcript.pyannote[129].end 360.97034375
transcript.pyannote[130].speaker SPEAKER_02
transcript.pyannote[130].start 360.97034375
transcript.pyannote[130].end 361.47659375
transcript.pyannote[131].speaker SPEAKER_03
transcript.pyannote[131].start 361.47659375
transcript.pyannote[131].end 361.54409375
transcript.pyannote[132].speaker SPEAKER_02
transcript.pyannote[132].start 361.54409375
transcript.pyannote[132].end 362.01659375
transcript.pyannote[133].speaker SPEAKER_03
transcript.pyannote[133].start 365.03721875
transcript.pyannote[133].end 365.72909375
transcript.pyannote[134].speaker SPEAKER_01
transcript.pyannote[134].start 367.09596875
transcript.pyannote[134].end 378.73971875
transcript.pyannote[135].speaker SPEAKER_02
transcript.pyannote[135].start 371.26409375
transcript.pyannote[135].end 371.38221875
transcript.pyannote[136].speaker SPEAKER_02
transcript.pyannote[136].start 373.67721875
transcript.pyannote[136].end 374.62221875
transcript.pyannote[137].speaker SPEAKER_00
transcript.pyannote[137].start 375.21284375
transcript.pyannote[137].end 375.29721875
transcript.pyannote[138].speaker SPEAKER_02
transcript.pyannote[138].start 375.29721875
transcript.pyannote[138].end 375.97221875
transcript.pyannote[139].speaker SPEAKER_00
transcript.pyannote[139].start 375.97221875
transcript.pyannote[139].end 376.32659375
transcript.pyannote[140].speaker SPEAKER_01
transcript.pyannote[140].start 379.34721875
transcript.pyannote[140].end 397.97721875
transcript.pyannote[141].speaker SPEAKER_02
transcript.pyannote[141].start 397.18409375
transcript.pyannote[141].end 399.98534375
transcript.pyannote[142].speaker SPEAKER_01
transcript.pyannote[142].start 397.99409375
transcript.pyannote[142].end 398.06159375
transcript.pyannote[143].speaker SPEAKER_02
transcript.pyannote[143].start 400.23846875
transcript.pyannote[143].end 401.23409375
transcript.pyannote[144].speaker SPEAKER_02
transcript.pyannote[144].start 401.74034375
transcript.pyannote[144].end 404.74409375
transcript.pyannote[145].speaker SPEAKER_03
transcript.pyannote[145].start 404.74409375
transcript.pyannote[145].end 405.09846875
transcript.pyannote[146].speaker SPEAKER_02
transcript.pyannote[146].start 405.09846875
transcript.pyannote[146].end 408.99659375
transcript.pyannote[147].speaker SPEAKER_02
transcript.pyannote[147].start 410.26221875
transcript.pyannote[147].end 411.29159375
transcript.pyannote[148].speaker SPEAKER_01
transcript.pyannote[148].start 412.06784375
transcript.pyannote[148].end 414.10971875
transcript.pyannote[149].speaker SPEAKER_02
transcript.pyannote[149].start 414.10971875
transcript.pyannote[149].end 414.68346875
transcript.pyannote[150].speaker SPEAKER_01
transcript.pyannote[150].start 414.68346875
transcript.pyannote[150].end 428.28471875
transcript.pyannote[151].speaker SPEAKER_02
transcript.pyannote[151].start 428.28471875
transcript.pyannote[151].end 429.17909375
transcript.pyannote[152].speaker SPEAKER_02
transcript.pyannote[152].start 429.87096875
transcript.pyannote[152].end 432.52034375
transcript.pyannote[153].speaker SPEAKER_01
transcript.pyannote[153].start 431.69346875
transcript.pyannote[153].end 431.72721875
transcript.pyannote[154].speaker SPEAKER_01
transcript.pyannote[154].start 431.74409375
transcript.pyannote[154].end 432.33471875
transcript.pyannote[155].speaker SPEAKER_01
transcript.pyannote[155].start 432.52034375
transcript.pyannote[155].end 432.85784375
transcript.pyannote[156].speaker SPEAKER_02
transcript.pyannote[156].start 432.85784375
transcript.pyannote[156].end 439.52346875
transcript.pyannote[157].speaker SPEAKER_02
transcript.pyannote[157].start 439.70909375
transcript.pyannote[157].end 446.49284375
transcript.pyannote[158].speaker SPEAKER_01
transcript.pyannote[158].start 446.79659375
transcript.pyannote[158].end 472.86846875
transcript.pyannote[159].speaker SPEAKER_02
transcript.pyannote[159].start 450.08721875
transcript.pyannote[159].end 450.99846875
transcript.pyannote[160].speaker SPEAKER_03
transcript.pyannote[160].start 457.83284375
transcript.pyannote[160].end 457.96784375
transcript.pyannote[161].speaker SPEAKER_00
transcript.pyannote[161].start 457.96784375
transcript.pyannote[161].end 458.20409375
transcript.pyannote[162].speaker SPEAKER_02
transcript.pyannote[162].start 468.58221875
transcript.pyannote[162].end 469.81409375
transcript.pyannote[163].speaker SPEAKER_02
transcript.pyannote[163].start 471.55221875
transcript.pyannote[163].end 475.31534375
transcript.pyannote[164].speaker SPEAKER_01
transcript.pyannote[164].start 473.64471875
transcript.pyannote[164].end 474.80909375
transcript.pyannote[165].speaker SPEAKER_01
transcript.pyannote[165].start 475.31534375
transcript.pyannote[165].end 479.26409375
transcript.pyannote[166].speaker SPEAKER_02
transcript.pyannote[166].start 479.11221875
transcript.pyannote[166].end 481.25534375
transcript.pyannote[167].speaker SPEAKER_01
transcript.pyannote[167].start 480.24284375
transcript.pyannote[167].end 488.95034375
transcript.pyannote[168].speaker SPEAKER_02
transcript.pyannote[168].start 486.94221875
transcript.pyannote[168].end 487.78596875
transcript.pyannote[169].speaker SPEAKER_01
transcript.pyannote[169].start 489.54096875
transcript.pyannote[169].end 490.03034375
transcript.pyannote[170].speaker SPEAKER_01
transcript.pyannote[170].start 490.48596875
transcript.pyannote[170].end 509.77409375
transcript.pyannote[171].speaker SPEAKER_02
transcript.pyannote[171].start 491.61659375
transcript.pyannote[171].end 492.02159375
transcript.pyannote[172].speaker SPEAKER_02
transcript.pyannote[172].start 498.87284375
transcript.pyannote[172].end 501.01596875
transcript.pyannote[173].speaker SPEAKER_02
transcript.pyannote[173].start 501.30284375
transcript.pyannote[173].end 502.41659375
transcript.pyannote[174].speaker SPEAKER_01
transcript.pyannote[174].start 509.99346875
transcript.pyannote[174].end 510.02721875
transcript.pyannote[175].speaker SPEAKER_02
transcript.pyannote[175].start 510.02721875
transcript.pyannote[175].end 510.14534375
transcript.pyannote[176].speaker SPEAKER_01
transcript.pyannote[176].start 510.34784375
transcript.pyannote[176].end 510.36471875
transcript.pyannote[177].speaker SPEAKER_02
transcript.pyannote[177].start 510.36471875
transcript.pyannote[177].end 510.38159375
transcript.pyannote[178].speaker SPEAKER_01
transcript.pyannote[178].start 510.38159375
transcript.pyannote[178].end 511.71471875
transcript.pyannote[179].speaker SPEAKER_02
transcript.pyannote[179].start 511.71471875
transcript.pyannote[179].end 511.95096875
transcript.pyannote[180].speaker SPEAKER_01
transcript.pyannote[180].start 511.95096875
transcript.pyannote[180].end 511.96784375
transcript.pyannote[181].speaker SPEAKER_02
transcript.pyannote[181].start 511.96784375
transcript.pyannote[181].end 522.54846875
transcript.pyannote[182].speaker SPEAKER_02
transcript.pyannote[182].start 522.90284375
transcript.pyannote[182].end 524.70846875
transcript.pyannote[183].speaker SPEAKER_02
transcript.pyannote[183].start 525.09659375
transcript.pyannote[183].end 525.48471875
transcript.pyannote[184].speaker SPEAKER_02
transcript.pyannote[184].start 525.75471875
transcript.pyannote[184].end 527.49284375
transcript.pyannote[185].speaker SPEAKER_02
transcript.pyannote[185].start 527.74596875
transcript.pyannote[185].end 528.77534375
transcript.pyannote[186].speaker SPEAKER_02
transcript.pyannote[186].start 529.46721875
transcript.pyannote[186].end 530.80034375
transcript.pyannote[187].speaker SPEAKER_02
transcript.pyannote[187].start 531.23909375
transcript.pyannote[187].end 532.58909375
transcript.pyannote[188].speaker SPEAKER_02
transcript.pyannote[188].start 532.77471875
transcript.pyannote[188].end 535.94721875
transcript.pyannote[189].speaker SPEAKER_01
transcript.pyannote[189].start 536.20034375
transcript.pyannote[189].end 536.45346875
transcript.pyannote[190].speaker SPEAKER_02
transcript.pyannote[190].start 537.49971875
transcript.pyannote[190].end 538.64721875
transcript.pyannote[191].speaker SPEAKER_01
transcript.pyannote[191].start 539.01846875
transcript.pyannote[191].end 539.25471875
transcript.pyannote[192].speaker SPEAKER_02
transcript.pyannote[192].start 540.30096875
transcript.pyannote[192].end 540.33471875
transcript.pyannote[193].speaker SPEAKER_01
transcript.pyannote[193].start 540.33471875
transcript.pyannote[193].end 565.07346875
transcript.pyannote[194].speaker SPEAKER_02
transcript.pyannote[194].start 563.94284375
transcript.pyannote[194].end 567.28409375
transcript.pyannote[195].speaker SPEAKER_02
transcript.pyannote[195].start 567.65534375
transcript.pyannote[195].end 569.57909375
transcript.pyannote[196].speaker SPEAKER_01
transcript.pyannote[196].start 569.57909375
transcript.pyannote[196].end 570.28784375
transcript.pyannote[197].speaker SPEAKER_02
transcript.pyannote[197].start 570.28784375
transcript.pyannote[197].end 574.40534375
transcript.pyannote[198].speaker SPEAKER_02
transcript.pyannote[198].start 574.62471875
transcript.pyannote[198].end 577.15596875
transcript.pyannote[199].speaker SPEAKER_01
transcript.pyannote[199].start 577.22346875
transcript.pyannote[199].end 582.80909375
transcript.pyannote[200].speaker SPEAKER_01
transcript.pyannote[200].start 583.39971875
transcript.pyannote[200].end 583.43346875
transcript.pyannote[201].speaker SPEAKER_02
transcript.pyannote[201].start 583.43346875
transcript.pyannote[201].end 583.73721875
transcript.pyannote[202].speaker SPEAKER_01
transcript.pyannote[202].start 583.73721875
transcript.pyannote[202].end 588.86721875
transcript.pyannote[203].speaker SPEAKER_01
transcript.pyannote[203].start 589.42409375
transcript.pyannote[203].end 597.32159375
transcript.pyannote[204].speaker SPEAKER_01
transcript.pyannote[204].start 597.69284375
transcript.pyannote[204].end 598.80659375
transcript.pyannote[205].speaker SPEAKER_01
transcript.pyannote[205].start 599.59971875
transcript.pyannote[205].end 600.96659375
transcript.pyannote[206].speaker SPEAKER_02
transcript.pyannote[206].start 600.96659375
transcript.pyannote[206].end 609.96096875
transcript.pyannote[207].speaker SPEAKER_01
transcript.pyannote[207].start 610.33221875
transcript.pyannote[207].end 635.20596875
transcript.pyannote[208].speaker SPEAKER_02
transcript.pyannote[208].start 617.41971875
transcript.pyannote[208].end 617.97659375
transcript.pyannote[209].speaker SPEAKER_00
transcript.pyannote[209].start 617.97659375
transcript.pyannote[209].end 618.70221875
transcript.pyannote[210].speaker SPEAKER_02
transcript.pyannote[210].start 632.67471875
transcript.pyannote[210].end 633.92346875
transcript.pyannote[211].speaker SPEAKER_02
transcript.pyannote[211].start 634.12596875
transcript.pyannote[211].end 635.17221875
transcript.pyannote[212].speaker SPEAKER_02
transcript.pyannote[212].start 635.20596875
transcript.pyannote[212].end 637.07909375
transcript.pyannote[213].speaker SPEAKER_01
transcript.pyannote[213].start 635.77971875
transcript.pyannote[213].end 641.77034375
transcript.pyannote[214].speaker SPEAKER_02
transcript.pyannote[214].start 638.51346875
transcript.pyannote[214].end 638.61471875
transcript.pyannote[215].speaker SPEAKER_01
transcript.pyannote[215].start 642.39471875
transcript.pyannote[215].end 643.59284375
transcript.pyannote[216].speaker SPEAKER_01
transcript.pyannote[216].start 644.40284375
transcript.pyannote[216].end 645.41534375
transcript.pyannote[217].speaker SPEAKER_01
transcript.pyannote[217].start 645.82034375
transcript.pyannote[217].end 646.64721875
transcript.pyannote[218].speaker SPEAKER_01
transcript.pyannote[218].start 646.74846875
transcript.pyannote[218].end 648.48659375
transcript.pyannote[219].speaker SPEAKER_02
transcript.pyannote[219].start 647.28846875
transcript.pyannote[219].end 647.44034375
transcript.pyannote[220].speaker SPEAKER_02
transcript.pyannote[220].start 648.48659375
transcript.pyannote[220].end 648.77346875
transcript.pyannote[221].speaker SPEAKER_01
transcript.pyannote[221].start 648.77346875
transcript.pyannote[221].end 648.79034375
transcript.pyannote[222].speaker SPEAKER_02
transcript.pyannote[222].start 648.79034375
transcript.pyannote[222].end 650.29221875
transcript.pyannote[223].speaker SPEAKER_01
transcript.pyannote[223].start 650.29221875
transcript.pyannote[223].end 650.32596875
transcript.pyannote[224].speaker SPEAKER_01
transcript.pyannote[224].start 650.49471875
transcript.pyannote[224].end 650.76471875
transcript.pyannote[225].speaker SPEAKER_02
transcript.pyannote[225].start 650.76471875
transcript.pyannote[225].end 650.79846875
transcript.pyannote[226].speaker SPEAKER_01
transcript.pyannote[226].start 650.79846875
transcript.pyannote[226].end 650.96721875
transcript.pyannote[227].speaker SPEAKER_02
transcript.pyannote[227].start 650.96721875
transcript.pyannote[227].end 651.08534375
transcript.pyannote[228].speaker SPEAKER_01
transcript.pyannote[228].start 651.08534375
transcript.pyannote[228].end 655.16909375
transcript.pyannote[229].speaker SPEAKER_02
transcript.pyannote[229].start 652.78971875
transcript.pyannote[229].end 653.04284375
transcript.whisperx[0].start 4.195
transcript.whisperx[0].end 11.238
transcript.whisperx[0].text 謝謝主席以及各位先進有請央郎 楊總裁以及財政部的莊部長請央郎 楊總裁 財政部莊部長兩位長官早有關於新青安的部分啦財政部目前履 履把它履到什麼程度這個有沒有開始有一些
transcript.whisperx[1].start 32.728
transcript.whisperx[1].end 60.581
transcript.whisperx[1].text 沒有交房貸的啦什麼之類的有沒有這個一些正常嗎新興安的相關的一個預期的一些狀況我們也去了解基本上它的平均率比全國的住宅貸款的預期繳款的低很多全國的是百分之0.08而新興安的部分是百分之0.01那大家有個人的一些因素我想這個部分我們都持續都在密切的關注
transcript.whisperx[2].start 61.306
transcript.whisperx[2].end 76.461
transcript.whisperx[2].text 你有沒有注意到這些新清安的這些房貸族拿這個貸貸的錢拿去這個股票市場有沒有他必須要買房子他才能夠他才能夠貸新清安啊他才能貸
transcript.whisperx[3].start 77.162
transcript.whisperx[3].end 82.886
transcript.whisperx[3].text 所以他必須是要買房嘛他能不能再把這個房買到二胎貸款可不可以二胎貸的話當然銀行在審核的時候必須他的信用能夠擔保到二胎新秦安可不可以去做二胎的房貸可不可以沒有限制我們沒有做這個
transcript.whisperx[4].start 100.6
transcript.whisperx[4].end 121.289
transcript.whisperx[4].text 沒有做這個沒有做這個部分的限制因為這房地產沒有規定不可以嘛但是委員房地產是他的啊而且他的擔保的保證是要能夠足夠擔保啊他拿去貸進去股市這是我擔心的我現在告訴兩位長官啊我們現在就是拿去房貸不管有沒有歐運啊就進入股市41.7萬的
transcript.whisperx[5].start 125.891
transcript.whisperx[5].end 135.895
transcript.whisperx[5].text 40幾萬戶口影響不可謂不大現在請問總裁啊我們要總共房子幾戶啊總共台灣的房子幾戶啊台灣的房子幾戶是不是 這個我就不曉得應該有數字啊 我知道是全部都800多萬戶吧800多萬戶吧
transcript.whisperx[6].start 152.419
transcript.whisperx[6].end 177.116
transcript.whisperx[6].text 八百多萬戶以過去的印象當中那如果41萬那就是很高的比例喔那個你剛才已經回答了就是央行不會有進一步的信用管制是不是我想呢這個因為我們剛好18號要禮監事會啦禮監事會也會就選擇性信用管制來討論啦
transcript.whisperx[7].start 180.361
transcript.whisperx[7].end 205.124
transcript.whisperx[7].text 還要討論個利率啊外資信貸已經有國外的有些金融機構已經預估說台灣的央行下禮拜會提高利息因為通貨膨脹一直上來然後股市很熱這個希望能夠用
transcript.whisperx[8].start 206.383
transcript.whisperx[8].end 208.495
transcript.whisperx[8].text 加個半碼或者是一碼來
transcript.whisperx[9].start 215.172
transcript.whisperx[9].end 231.064
transcript.whisperx[9].text 這個訊息我們都掌握當中不過有的是說會誠如委員所說的這樣但是有的是說會不動所以這些的情況我想18號就會知道了所以你不願意透露一點點
transcript.whisperx[10].start 240.051
transcript.whisperx[10].end 256.727
transcript.whisperx[10].text 你來這裡也需要透露一下表情 講清楚一下因為委員 我也跟委員報告一下我們10天之內就是說禮監事會禮監事會的10天之內呢每一個委員呢 都是監默期他是一個監默期
transcript.whisperx[11].start 258.849
transcript.whisperx[11].end 265.992
transcript.whisperx[11].text 所以呢很抱歉啦那個委員所以我才會剛剛跟你們報告就是說我們18號的時候呢經過委員的充分討論之後呢他的結果呢一定會在當天馬上更佈不管你沒有在緘默期你都不會講啦就這樣才對啦
transcript.whisperx[12].start 280.98
transcript.whisperx[12].end 299.677
transcript.whisperx[12].text 我請教你 全球的資金 比如說加密貨幣 黃金等等是不是因為都投入股市而暴跌 然後資金都跑去股市股市佔整個的 到底股市投入的比例多高資金多高 我看了一個數字
transcript.whisperx[13].start 301.613
transcript.whisperx[13].end 307.118
transcript.whisperx[13].text 比如說美國股市佔M2 它有這個指標股市的總值佔M2 315%美國日本呢102% 韓國83% 台股183%所以相對的台灣的錢進入股市是不是水位已經相當高了
transcript.whisperx[14].start 330.126
transcript.whisperx[14].end 359.145
transcript.whisperx[14].text 所以這個就是相對的啦如果我們是跟台灣跟如果我們說跟三四年前來比較的話那當然現在目前投入股市的資金是比較多了跟三四年前來比較的話那如果說跟剛剛委員所報告的這樣子的話事實上我們台灣看起來算相較啦這是相較啦你看看美國又那麼高
transcript.whisperx[15].start 360.066
transcript.whisperx[15].end 361.408
transcript.whisperx[15].text 那跟韓國來講的話你剛剛是說他是85嘛但是我跟委員報告
transcript.whisperx[16].start 379.943
transcript.whisperx[16].end 397.749
transcript.whisperx[16].text 韓國是在前幾年的時候 前兩年的時候 它是非常低的是最近才很直線的上來所以呢 委員你也會發現到韓國的股市呢 它的一個修正它的修正呢 它非常劇烈的我再關心一個題目因為台股前天大跌 昨天倡力反彈昨天外匯成交47.46美金
transcript.whisperx[17].start 410.645
transcript.whisperx[17].end 427.75
transcript.whisperx[17].text 我沒有記錄啊你是說那個外匯的市場外匯的市場就是說因為是供需嘛我們的出口商也蠻有錢的你也知道啊我們出口商他的那個什麼他的出口非常少啊那如果說出口商價格好的時候呢出口商會出來好來問你啊
transcript.whisperx[18].start 430.031
transcript.whisperx[18].end 445.818
transcript.whisperx[18].text 6月底 今天是6月10號6月1號到現在外資總共賣了2528億台幣等於80億美金台股這句話 我問你這句話是不是成立台股已經成了外資的提款機這句對不對
transcript.whisperx[19].start 447.624
transcript.whisperx[19].end 471.278
transcript.whisperx[19].text 我想是我們可以這麼說就是說那個外資他對於我們台股他是非常感興趣的為什麼因為我們台股他的dividend他的股率非常豐厚所以他是進進出出只是說現在因為我們的股價比較大比較高所以他的進出的金額他現在是進會出
transcript.whisperx[20].start 475.902
transcript.whisperx[20].end 479.506
transcript.whisperx[20].text 他也會進來也會出去你現在講六月的話呢我跟委員報告他是出去出去多少Net
transcript.whisperx[21].start 490.598
transcript.whisperx[21].end 507.362
transcript.whisperx[21].text Net的話呢 因為他會有時間的落後那我在想應該至少 至少應該他都有50億啦50億 至少啦那如果說 如果說 委員如果說就外資來講的話呢50億是不高啦
transcript.whisperx[22].start 510.684
transcript.whisperx[22].end 519.91
transcript.whisperx[22].text 聯準會要上台了喔川普要他降息可是美國經濟好啊就業也好啊通膨高他怎麼降呢這出去看不可能降啊你從你專家中的專家來講不可能降嘛對不對我現在講對吧我剛才的描述對吧美國經濟好就業好通膨高他怎麼降息他要升息喔
transcript.whisperx[23].start 540.319
transcript.whisperx[23].end 562.29
transcript.whisperx[23].text 同意嗎市場是也有做這樣的一個Price in就是說有這樣的一個預期也就是說美國的經濟好就是因為美國的經濟好還有現在的美伊戰爭所以導致它這個通膨也是比較高所以它的債券的利率就高我認為主要還是它的經濟好美國的債券30年起破5%了10年起的4.5%
transcript.whisperx[24].start 570.294
transcript.whisperx[24].end 598.606
transcript.whisperx[24].text 那一般來講說我只要七到八八就等於垃圾債券美國美債會不會變垃圾債券沒有 不過我跟委員報告美國的現在的債券是AAAAA離這個BBB-那還差很遠所以你拼命買進美債我們也沒有說拼命買進因為我們的外匯群體都是diversify我們是diversify
transcript.whisperx[25].start 599.574
transcript.whisperx[25].end 627.947
transcript.whisperx[25].text 對啊 但是我覺得問一個人因為最近變化很大 經濟市場很大你給我確定一下過去的數字美債是不是在你的歐益存底還是有八成左右我們隨時再調整八成可以吧有些時候是會超過有些時候是會比較低因為最主要的是跟美元的匯率有關係如果說美元的匯率高它比較強的時候呢它的那個比例就會提高
transcript.whisperx[26].start 629.608
transcript.whisperx[26].end 651.422
transcript.whisperx[26].text 如果說美元是比較弱的時候它的那個比重就會低但是呢除了這個匯率的調整以外我們本身呢我們也會做動態的調整黃金有沒有加一丁到目前還沒有黃金沒有買到目前還沒有買美債就是在八成左右應該可以這麼說了謝謝賴思寶委員