iVOD / 154498

Field Value
IVOD_ID 154498
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/154498
日期 2024-07-03
會議資料.會議代碼 委員會-11-1-20-20
會議資料.會議代碼:str 第11屆第1會期財政委員會第20次全體委員會議
會議資料.屆 11
會議資料.會期 1
會議資料.會次 20
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1會期財政委員會第20次全體委員會議
影片種類 Clip
開始時間 2024-07-03T11:25:33+08:00
結束時間 2024-07-03T11:37:47+08:00
影片長度 00:12:14
支援功能[0] ai-transcript
支援功能[1] gazette
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/5ad2054f9b7cf4bd080148958083d084cb3f5941fe168625e8e3eb0bf88d021c54de318ebac86ee55ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 王世堅
委員發言時間 11:25:33 - 11:37:47
會議時間 2024-07-03T09:00:00+08:00
會議名稱 立法院第11屆第1會期財政委員會第20次全體委員會議(事由:一、邀請金融監督管理委員會彭主任委員金隆、財政部莊部長翠雲就「如何促進保險業資金擴大參與公共建設,加速建設之推動。」進行專題報告,並備質詢;另邀請中央銀行、國家發展委員會、經濟部、交通部列席備詢。 二、繼續審查本院委員羅明才等17人擬具「保險法第一百四十六條之四條文修正草案」案。 【7月3日及4日二天一次會】)
gazette.lineno 860
gazette.blocks[0][0] 王委員世堅:(11時25分)謝謝主席,我請金管會彭主委。
gazette.blocks[1][0] 主席:請彭主委。
gazette.blocks[2][0] 彭主任委員金隆:王委員好。
gazette.blocks[3][0] 王委員世堅:我們壽險業資產總額已經高達36兆,而他們可運用的資金32兆當中,現在照這個分配比,竟然國外投資占了70%!你看一下表格的金額,高達22兆、69.7%。當然這不能單獨怪你,可是我們先比較一下國外各國在壽險業海外投資的部分占多少,就舉對岸中國為例好了,中國壽險業只有2%耶!2%的資金到國外。韓國不到10%,是8.3%;日本21.6%;美國12%。獨獨臺灣正需要公共建設,正需要大家投入臺灣、對我們國家有信心的時候,我們竟然放任最大的資金──壽險業的資金高達70%、22兆到國外去投資!
gazette.blocks[3][1] 在座各位都是金融專家,你們很清楚,國外這些投資最大的風險,第一個是戰爭;第二個是匯率;第三,連他們的利率,表面上高的地方,但你賺了它的利息、賠了本金。我現在簡單講俄國就好,在俄國我們竟然有8家壽險業持有它1,380億債券!好了,這1,380億通通暴險,怎麼講?俄烏戰爭還在打。不講這個戰爭,壽險業說不知道兩年前他們會打仗,那你至少要知道俄國那麼極權的國家,在世界版圖裡面它是軸心國,拜託!這些壽險業唯利是圖,利率高就去!他們不但價值理念跟我們自由世界的國家不同,現在它有戰爭,說翻臉就翻臉。我光指現在,這8家有72張投資型保單,現在已經被通知啦!這只是冰山一小小角,有11億已經通知說這個到時候要逾期,踩雷了,說要等到解禁才能收回。所以光這11億,有8,000萬資金要損失掉,我們的保戶根本拿不到錢。這些壽險業就是這樣,「用別人的拳頭拇舂石獅」!賺是它要賺,賠是保戶賠,就是這樣!這8家不只這11億,11億是被通知到的,因為馬上就暴險,後續這1,380億,彭主委,我本來一上台想問你是哪8家,後來我想想,其實最主要不是你造成的啦,是你的前任黃天牧主委!他在2020年的時候就說壽險業海外投資暴險金額比率過高,應該要降低。說要降,結果4年來越降越高,從他4年前上任時的64%拿到海外去,到現在高達70%!當然,他卸任了,而且他過去也有一些好的表現,我就不提他了,但是在你任內,尤其壽險是你的專業,我希望你拿出你的專業、堅持你的風骨,我認為壽險資金投資海外要大幅降低!當然,財政部也要配合。部長,你坐在位子上聽就好,財政部應該協調各部會,針對我們重大的公共建設、需要資金的公共建設,引領各部會趕快來跟財政部協商,由財政部幫他們發行公債嘛!不是嗎?
gazette.blocks[3][2] 這麼多年來,財政部在蔡總統任內代為發行的乙類公債有7大項,都是很有意義的公共建設,從桃園航空城、國道建設到高速鐵路,這些都非常好,自償性也很高,可是這7檔加起來才1,500億,占不到1%!天啊!這麼努力之下喔!
gazette.blocks[3][3] 壽險業又說了,他們說我們國內的債券市場太小了、我們利率太低了,他們是為了保障保戶的收益。主委,這些話我就用4個字來形容──鬼話連篇!他們說要保障保戶的收益,欸!你在任何時間點賣的保單都是以當年、當時我們國內的利率去計算期望值的,所以不要在那邊「騙痟的」啦!以現在的利率計算的保單期望值,那它賠什麼賠?這10年來、這20年來都以各該當時的利率計算不是嗎?然後他們還額外賺什麼?他們還賺國內這麼多不動產的投資、這些不動產的增值。我相信這些經過詳細的計算後,主委,你下去計算一下,我有初步的一些概算,我認為這些壽險業的業主心思都不單純,很邪惡啦!
gazette.blocks[3][4] 第一點,他們對建設我們臺灣、建設我們國家沒有信心,否則怎麼會說國內債券市場規模太小?我就講我們國家發行的公債就好了啊!國家發行的公債數十年來超過10兆,到現在我們國債(公債)的餘額還有5.8兆喔!那你至少先拿個10%,32兆拿個10%,用3兆2來買國債總可以吧!可是它不!他們不買!這胡說八道嘛!不但帶頭對建設我們國家沒信心,第二點,還坑殺保戶,他們去國外利率高的地方,賺的時候它賺,現在賠了,我剛剛講俄國現在暴險了!已經暴險的部分保戶就要賠7,000萬,光11億就要賠7,000萬,統統賠保戶的!後續它還有1,380億,這8家!所以我希望你私下告訴我是哪8家,我們一起想想辦法看怎麼整他們啦!幫保戶討回公道嘛!可不可以?
gazette.blocks[4][0] 彭主任委員金隆:我們來看一下資料,如果可以提供的話,再提供給委員參考。
gazette.blocks[5][0] 王委員世堅:表示你有資料嘛!不是嗎?你剛剛說看一下資料再來決定。好啦!因為你剛上任不久,我對你不苛責。我是對你不苛責,但是抱著期許!
gazette.blocks[6][0] 彭主任委員金隆:謝謝,謝謝委員。
gazette.blocks[7][0] 王委員世堅:我期許你對這些惡劣的壽險公司能夠拿出風骨跟膽識。不是每一家都惡劣喔!就是已經變成金融怪獸的這幾家。我剛剛講至少有8家是非常、非常惡劣!我有計算,也希望你下去計算一下,針對他們講的這些謬論,看看用什麼方式去反駁。它說要保障保戶的收益,所以必須到海外去,海外利率才高,我剛剛跟你講了嘛!利率高,你賺了人家利率,它從匯率把你整回來。第二點,遇到戰爭怎麼辦?第三點是最重要的,我們國家、我們的公共建設需要資金,要帶頭對我們國家有信心,要建設我們臺灣才對!不是嗎?我們有那麼多的建設需要,現在除了大型的公共建設,另類的公共建設也很多啊!社會住宅、長照、社福機構,這些也都有他們的自償性,都足以讓壽險的資金回流去投資,不是嗎?但是他們置若罔聞、視若無睹,就是這些業者這麼惡劣的行徑!
gazette.blocks[7][1] 所以,彭主委,因為時間到了,我對你有期許啦!
gazette.blocks[8][0] 彭主任委員金隆:謝謝。
gazette.blocks[9][0] 王委員世堅:我對部長也有期許,雖然比較低。
gazette.blocks[9][1] 但是我希望你針對我講的,做一份簡單扼要的說明,私下告訴我怎麼來處理,好不好?一定要降低這些壽險業海外投資的占比,占到70%,已經到了非常惡劣、離譜的地步了。好,謝謝。
gazette.blocks[10][0] 彭主任委員金隆:謝謝,謝謝委員,謝謝!
gazette.blocks[11][0] 主席:好,謝謝。現在請央行楊總裁,還有彭主委和莊部長到前面這邊來。我們現在休息。
gazette.blocks[11][1] 休息(11時37分)
gazette.blocks[11][2] 繼續開會(12時3分)
gazette.blocks[12][0] 主席:我們繼續開會。下一位質詢請陳玉珍陳委員。
gazette.agenda.page_end 68
gazette.agenda.meet_id 委員會-11-1-20-20
gazette.agenda.speakers[0] 羅明才
gazette.agenda.speakers[1] 林德福
gazette.agenda.speakers[2] 吳秉叡
gazette.agenda.speakers[3] 賴士葆
gazette.agenda.speakers[4] 郭國文
gazette.agenda.speakers[5] 李坤城
gazette.agenda.speakers[6] 賴惠員
gazette.agenda.speakers[7] 顏寬恒
gazette.agenda.speakers[8] 王鴻薇
gazette.agenda.speakers[9] 李彥秀
gazette.agenda.speakers[10] 黃珊珊
gazette.agenda.speakers[11] 王世堅
gazette.agenda.speakers[12] 陳玉珍
gazette.agenda.speakers[13] 伍麗華Saidhai‧Tahovecahe
gazette.agenda.speakers[14] 黃國昌
gazette.agenda.speakers[15] 林楚茵
gazette.agenda.speakers[16] 鍾佳濱
gazette.agenda.speakers[17] 吳春城
gazette.agenda.speakers[18] 楊瓊瓔
gazette.agenda.page_start 1
gazette.agenda.meetingDate[0] 2024-07-03
gazette.agenda.gazette_id 1136901
gazette.agenda.agenda_lcidc_ids[0] 1136901_00002
gazette.agenda.meet_name 立法院第11屆第1會期財政委員會第20次全體委員會議紀錄
gazette.agenda.content 一、邀請金融監督管理委員會彭主任委員金隆、財政部莊部長翠雲就「如何促進保險業資金擴大 參與公共建設,加速建設之推動。」進行專題報告,並備質詢;另邀請中央銀行、國家發展委員 會、經濟部、交通部列席備詢;二、繼續審查本院委員羅明才等17人擬具「保險法第一百四十六 條之四條文修正草案」案
gazette.agenda.agenda_id 1136901_00001
transcript.pyannote[0].speaker SPEAKER_00
transcript.pyannote[0].start 0.89159375
transcript.pyannote[0].end 2.17409375
transcript.pyannote[1].speaker SPEAKER_00
transcript.pyannote[1].start 2.49471875
transcript.pyannote[1].end 2.81534375
transcript.pyannote[2].speaker SPEAKER_00
transcript.pyannote[2].start 3.30471875
transcript.pyannote[2].end 4.48596875
transcript.pyannote[3].speaker SPEAKER_00
transcript.pyannote[3].start 4.99221875
transcript.pyannote[3].end 5.70096875
transcript.pyannote[4].speaker SPEAKER_00
transcript.pyannote[4].start 9.07596875
transcript.pyannote[4].end 9.56534375
transcript.pyannote[5].speaker SPEAKER_00
transcript.pyannote[5].start 10.37534375
transcript.pyannote[5].end 11.05034375
transcript.pyannote[6].speaker SPEAKER_00
transcript.pyannote[6].start 11.23596875
transcript.pyannote[6].end 11.53971875
transcript.pyannote[7].speaker SPEAKER_00
transcript.pyannote[7].start 11.77596875
transcript.pyannote[7].end 12.90659375
transcript.pyannote[8].speaker SPEAKER_00
transcript.pyannote[8].start 13.85159375
transcript.pyannote[8].end 16.14659375
transcript.pyannote[9].speaker SPEAKER_00
transcript.pyannote[9].start 16.41659375
transcript.pyannote[9].end 17.54721875
transcript.pyannote[10].speaker SPEAKER_00
transcript.pyannote[10].start 18.27284375
transcript.pyannote[10].end 18.69471875
transcript.pyannote[11].speaker SPEAKER_00
transcript.pyannote[11].start 18.98159375
transcript.pyannote[11].end 25.12409375
transcript.pyannote[12].speaker SPEAKER_00
transcript.pyannote[12].start 26.05221875
transcript.pyannote[12].end 27.01409375
transcript.pyannote[13].speaker SPEAKER_00
transcript.pyannote[13].start 27.62159375
transcript.pyannote[13].end 29.12346875
transcript.pyannote[14].speaker SPEAKER_00
transcript.pyannote[14].start 29.34284375
transcript.pyannote[14].end 31.80659375
transcript.pyannote[15].speaker SPEAKER_00
transcript.pyannote[15].start 32.98784375
transcript.pyannote[15].end 39.63659375
transcript.pyannote[16].speaker SPEAKER_00
transcript.pyannote[16].start 40.96971875
transcript.pyannote[16].end 43.45034375
transcript.pyannote[17].speaker SPEAKER_00
transcript.pyannote[17].start 45.28971875
transcript.pyannote[17].end 47.43284375
transcript.pyannote[18].speaker SPEAKER_00
transcript.pyannote[18].start 47.98971875
transcript.pyannote[18].end 49.35659375
transcript.pyannote[19].speaker SPEAKER_00
transcript.pyannote[19].start 49.54221875
transcript.pyannote[19].end 50.87534375
transcript.pyannote[20].speaker SPEAKER_00
transcript.pyannote[20].start 50.95971875
transcript.pyannote[20].end 52.12409375
transcript.pyannote[21].speaker SPEAKER_00
transcript.pyannote[21].start 52.66409375
transcript.pyannote[21].end 55.44846875
transcript.pyannote[22].speaker SPEAKER_00
transcript.pyannote[22].start 56.14034375
transcript.pyannote[22].end 58.11471875
transcript.pyannote[23].speaker SPEAKER_00
transcript.pyannote[23].start 58.50284375
transcript.pyannote[23].end 68.94846875
transcript.pyannote[24].speaker SPEAKER_00
transcript.pyannote[24].start 69.28596875
transcript.pyannote[24].end 71.02409375
transcript.pyannote[25].speaker SPEAKER_00
transcript.pyannote[25].start 71.07471875
transcript.pyannote[25].end 75.04034375
transcript.pyannote[26].speaker SPEAKER_00
transcript.pyannote[26].start 76.49159375
transcript.pyannote[26].end 77.57159375
transcript.pyannote[27].speaker SPEAKER_00
transcript.pyannote[27].start 78.34784375
transcript.pyannote[27].end 79.64721875
transcript.pyannote[28].speaker SPEAKER_00
transcript.pyannote[28].start 81.63846875
transcript.pyannote[28].end 89.21534375
transcript.pyannote[29].speaker SPEAKER_00
transcript.pyannote[29].start 90.14346875
transcript.pyannote[29].end 91.66221875
transcript.pyannote[30].speaker SPEAKER_00
transcript.pyannote[30].start 91.91534375
transcript.pyannote[30].end 93.68721875
transcript.pyannote[31].speaker SPEAKER_00
transcript.pyannote[31].start 94.73346875
transcript.pyannote[31].end 97.88909375
transcript.pyannote[32].speaker SPEAKER_00
transcript.pyannote[32].start 98.83409375
transcript.pyannote[32].end 99.17159375
transcript.pyannote[33].speaker SPEAKER_00
transcript.pyannote[33].start 100.16721875
transcript.pyannote[33].end 100.70721875
transcript.pyannote[34].speaker SPEAKER_00
transcript.pyannote[34].start 102.78284375
transcript.pyannote[34].end 103.66034375
transcript.pyannote[35].speaker SPEAKER_00
transcript.pyannote[35].start 104.67284375
transcript.pyannote[35].end 105.88784375
transcript.pyannote[36].speaker SPEAKER_00
transcript.pyannote[36].start 106.68096875
transcript.pyannote[36].end 106.91721875
transcript.pyannote[37].speaker SPEAKER_00
transcript.pyannote[37].start 107.44034375
transcript.pyannote[37].end 109.75221875
transcript.pyannote[38].speaker SPEAKER_00
transcript.pyannote[38].start 109.95471875
transcript.pyannote[38].end 110.89971875
transcript.pyannote[39].speaker SPEAKER_00
transcript.pyannote[39].start 111.81096875
transcript.pyannote[39].end 112.55346875
transcript.pyannote[40].speaker SPEAKER_00
transcript.pyannote[40].start 113.93721875
transcript.pyannote[40].end 118.42596875
transcript.pyannote[41].speaker SPEAKER_00
transcript.pyannote[41].start 118.96596875
transcript.pyannote[41].end 120.90659375
transcript.pyannote[42].speaker SPEAKER_00
transcript.pyannote[42].start 121.85159375
transcript.pyannote[42].end 123.65721875
transcript.pyannote[43].speaker SPEAKER_00
transcript.pyannote[43].start 124.78784375
transcript.pyannote[43].end 127.31909375
transcript.pyannote[44].speaker SPEAKER_00
transcript.pyannote[44].start 128.77034375
transcript.pyannote[44].end 130.87971875
transcript.pyannote[45].speaker SPEAKER_00
transcript.pyannote[45].start 132.73596875
transcript.pyannote[45].end 133.59659375
transcript.pyannote[46].speaker SPEAKER_00
transcript.pyannote[46].start 134.69346875
transcript.pyannote[46].end 141.12284375
transcript.pyannote[47].speaker SPEAKER_00
transcript.pyannote[47].start 141.79784375
transcript.pyannote[47].end 142.52346875
transcript.pyannote[48].speaker SPEAKER_00
transcript.pyannote[48].start 143.85659375
transcript.pyannote[48].end 144.37971875
transcript.pyannote[49].speaker SPEAKER_00
transcript.pyannote[49].start 144.70034375
transcript.pyannote[49].end 147.14721875
transcript.pyannote[50].speaker SPEAKER_00
transcript.pyannote[50].start 147.68721875
transcript.pyannote[50].end 148.21034375
transcript.pyannote[51].speaker SPEAKER_00
transcript.pyannote[51].start 148.46346875
transcript.pyannote[51].end 148.69971875
transcript.pyannote[52].speaker SPEAKER_00
transcript.pyannote[52].start 149.13846875
transcript.pyannote[52].end 150.58971875
transcript.pyannote[53].speaker SPEAKER_00
transcript.pyannote[53].start 152.71596875
transcript.pyannote[53].end 153.17159375
transcript.pyannote[54].speaker SPEAKER_00
transcript.pyannote[54].start 154.16721875
transcript.pyannote[54].end 163.98846875
transcript.pyannote[55].speaker SPEAKER_00
transcript.pyannote[55].start 165.35534375
transcript.pyannote[55].end 170.45159375
transcript.pyannote[56].speaker SPEAKER_00
transcript.pyannote[56].start 171.56534375
transcript.pyannote[56].end 172.62846875
transcript.pyannote[57].speaker SPEAKER_00
transcript.pyannote[57].start 172.72971875
transcript.pyannote[57].end 173.15159375
transcript.pyannote[58].speaker SPEAKER_00
transcript.pyannote[58].start 173.45534375
transcript.pyannote[58].end 174.68721875
transcript.pyannote[59].speaker SPEAKER_00
transcript.pyannote[59].start 175.39596875
transcript.pyannote[59].end 177.23534375
transcript.pyannote[60].speaker SPEAKER_00
transcript.pyannote[60].start 178.02846875
transcript.pyannote[60].end 178.48409375
transcript.pyannote[61].speaker SPEAKER_00
transcript.pyannote[61].start 179.20971875
transcript.pyannote[61].end 180.94784375
transcript.pyannote[62].speaker SPEAKER_00
transcript.pyannote[62].start 182.26409375
transcript.pyannote[62].end 185.18346875
transcript.pyannote[63].speaker SPEAKER_00
transcript.pyannote[63].start 185.67284375
transcript.pyannote[63].end 192.43971875
transcript.pyannote[64].speaker SPEAKER_00
transcript.pyannote[64].start 193.36784375
transcript.pyannote[64].end 194.36346875
transcript.pyannote[65].speaker SPEAKER_00
transcript.pyannote[65].start 195.07221875
transcript.pyannote[65].end 200.96159375
transcript.pyannote[66].speaker SPEAKER_00
transcript.pyannote[66].start 203.15534375
transcript.pyannote[66].end 203.66159375
transcript.pyannote[67].speaker SPEAKER_00
transcript.pyannote[67].start 204.03284375
transcript.pyannote[67].end 206.95221875
transcript.pyannote[68].speaker SPEAKER_00
transcript.pyannote[68].start 207.64409375
transcript.pyannote[68].end 210.85034375
transcript.pyannote[69].speaker SPEAKER_00
transcript.pyannote[69].start 211.50846875
transcript.pyannote[69].end 212.52096875
transcript.pyannote[70].speaker SPEAKER_00
transcript.pyannote[70].start 213.98909375
transcript.pyannote[70].end 214.59659375
transcript.pyannote[71].speaker SPEAKER_00
transcript.pyannote[71].start 215.69346875
transcript.pyannote[71].end 216.04784375
transcript.pyannote[72].speaker SPEAKER_00
transcript.pyannote[72].start 216.92534375
transcript.pyannote[72].end 217.70159375
transcript.pyannote[73].speaker SPEAKER_00
transcript.pyannote[73].start 218.76471875
transcript.pyannote[73].end 219.55784375
transcript.pyannote[74].speaker SPEAKER_00
transcript.pyannote[74].start 220.55346875
transcript.pyannote[74].end 231.26909375
transcript.pyannote[75].speaker SPEAKER_00
transcript.pyannote[75].start 232.21409375
transcript.pyannote[75].end 232.70346875
transcript.pyannote[76].speaker SPEAKER_00
transcript.pyannote[76].start 233.00721875
transcript.pyannote[76].end 233.93534375
transcript.pyannote[77].speaker SPEAKER_00
transcript.pyannote[77].start 234.10409375
transcript.pyannote[77].end 236.14596875
transcript.pyannote[78].speaker SPEAKER_00
transcript.pyannote[78].start 237.02346875
transcript.pyannote[78].end 239.80784375
transcript.pyannote[79].speaker SPEAKER_00
transcript.pyannote[79].start 240.46596875
transcript.pyannote[79].end 241.95096875
transcript.pyannote[80].speaker SPEAKER_00
transcript.pyannote[80].start 242.35596875
transcript.pyannote[80].end 243.84096875
transcript.pyannote[81].speaker SPEAKER_00
transcript.pyannote[81].start 245.37659375
transcript.pyannote[81].end 246.05159375
transcript.pyannote[82].speaker SPEAKER_00
transcript.pyannote[82].start 247.68846875
transcript.pyannote[82].end 249.76409375
transcript.pyannote[83].speaker SPEAKER_00
transcript.pyannote[83].start 250.74284375
transcript.pyannote[83].end 253.08846875
transcript.pyannote[84].speaker SPEAKER_00
transcript.pyannote[84].start 253.71284375
transcript.pyannote[84].end 255.77159375
transcript.pyannote[85].speaker SPEAKER_00
transcript.pyannote[85].start 256.71659375
transcript.pyannote[85].end 258.99471875
transcript.pyannote[86].speaker SPEAKER_00
transcript.pyannote[86].start 260.09159375
transcript.pyannote[86].end 261.03659375
transcript.pyannote[87].speaker SPEAKER_01
transcript.pyannote[87].start 261.45846875
transcript.pyannote[87].end 261.64409375
transcript.pyannote[88].speaker SPEAKER_00
transcript.pyannote[88].start 261.64409375
transcript.pyannote[88].end 264.17534375
transcript.pyannote[89].speaker SPEAKER_00
transcript.pyannote[89].start 265.99784375
transcript.pyannote[89].end 266.45346875
transcript.pyannote[90].speaker SPEAKER_00
transcript.pyannote[90].start 267.19596875
transcript.pyannote[90].end 268.69784375
transcript.pyannote[91].speaker SPEAKER_00
transcript.pyannote[91].start 269.65971875
transcript.pyannote[91].end 273.59159375
transcript.pyannote[92].speaker SPEAKER_00
transcript.pyannote[92].start 274.26659375
transcript.pyannote[92].end 276.37596875
transcript.pyannote[93].speaker SPEAKER_00
transcript.pyannote[93].start 277.00034375
transcript.pyannote[93].end 277.82721875
transcript.pyannote[94].speaker SPEAKER_00
transcript.pyannote[94].start 278.13096875
transcript.pyannote[94].end 278.87346875
transcript.pyannote[95].speaker SPEAKER_00
transcript.pyannote[95].start 279.31221875
transcript.pyannote[95].end 280.07159375
transcript.pyannote[96].speaker SPEAKER_00
transcript.pyannote[96].start 280.13909375
transcript.pyannote[96].end 282.33284375
transcript.pyannote[97].speaker SPEAKER_00
transcript.pyannote[97].start 283.42971875
transcript.pyannote[97].end 285.77534375
transcript.pyannote[98].speaker SPEAKER_00
transcript.pyannote[98].start 287.05784375
transcript.pyannote[98].end 288.98159375
transcript.pyannote[99].speaker SPEAKER_00
transcript.pyannote[99].start 289.13346875
transcript.pyannote[99].end 290.26409375
transcript.pyannote[100].speaker SPEAKER_00
transcript.pyannote[100].start 290.78721875
transcript.pyannote[100].end 293.47034375
transcript.pyannote[101].speaker SPEAKER_00
transcript.pyannote[101].start 294.68534375
transcript.pyannote[101].end 295.20846875
transcript.pyannote[102].speaker SPEAKER_00
transcript.pyannote[102].start 295.46159375
transcript.pyannote[102].end 299.39346875
transcript.pyannote[103].speaker SPEAKER_00
transcript.pyannote[103].start 299.95034375
transcript.pyannote[103].end 304.16909375
transcript.pyannote[104].speaker SPEAKER_00
transcript.pyannote[104].start 306.14346875
transcript.pyannote[104].end 307.61159375
transcript.pyannote[105].speaker SPEAKER_00
transcript.pyannote[105].start 308.59034375
transcript.pyannote[105].end 311.35784375
transcript.pyannote[106].speaker SPEAKER_00
transcript.pyannote[106].start 312.20159375
transcript.pyannote[106].end 312.69096875
transcript.pyannote[107].speaker SPEAKER_00
transcript.pyannote[107].start 313.92284375
transcript.pyannote[107].end 314.54721875
transcript.pyannote[108].speaker SPEAKER_00
transcript.pyannote[108].start 315.77909375
transcript.pyannote[108].end 317.44971875
transcript.pyannote[109].speaker SPEAKER_00
transcript.pyannote[109].start 318.14159375
transcript.pyannote[109].end 319.03596875
transcript.pyannote[110].speaker SPEAKER_00
transcript.pyannote[110].start 319.08659375
transcript.pyannote[110].end 320.23409375
transcript.pyannote[111].speaker SPEAKER_00
transcript.pyannote[111].start 321.31409375
transcript.pyannote[111].end 322.19159375
transcript.pyannote[112].speaker SPEAKER_00
transcript.pyannote[112].start 322.64721875
transcript.pyannote[112].end 324.04784375
transcript.pyannote[113].speaker SPEAKER_00
transcript.pyannote[113].start 324.55409375
transcript.pyannote[113].end 327.32159375
transcript.pyannote[114].speaker SPEAKER_00
transcript.pyannote[114].start 328.40159375
transcript.pyannote[114].end 329.78534375
transcript.pyannote[115].speaker SPEAKER_00
transcript.pyannote[115].start 330.02159375
transcript.pyannote[115].end 330.03846875
transcript.pyannote[116].speaker SPEAKER_00
transcript.pyannote[116].start 330.12284375
transcript.pyannote[116].end 333.32909375
transcript.pyannote[117].speaker SPEAKER_00
transcript.pyannote[117].start 334.29096875
transcript.pyannote[117].end 335.80971875
transcript.pyannote[118].speaker SPEAKER_00
transcript.pyannote[118].start 337.21034375
transcript.pyannote[118].end 337.98659375
transcript.pyannote[119].speaker SPEAKER_00
transcript.pyannote[119].start 338.22284375
transcript.pyannote[119].end 341.09159375
transcript.pyannote[120].speaker SPEAKER_00
transcript.pyannote[120].start 342.10409375
transcript.pyannote[120].end 348.92159375
transcript.pyannote[121].speaker SPEAKER_00
transcript.pyannote[121].start 350.69346875
transcript.pyannote[121].end 352.43159375
transcript.pyannote[122].speaker SPEAKER_00
transcript.pyannote[122].start 353.52846875
transcript.pyannote[122].end 359.46846875
transcript.pyannote[123].speaker SPEAKER_00
transcript.pyannote[123].start 361.49346875
transcript.pyannote[123].end 362.92784375
transcript.pyannote[124].speaker SPEAKER_00
transcript.pyannote[124].start 363.28221875
transcript.pyannote[124].end 364.44659375
transcript.pyannote[125].speaker SPEAKER_00
transcript.pyannote[125].start 364.69971875
transcript.pyannote[125].end 365.20596875
transcript.pyannote[126].speaker SPEAKER_00
transcript.pyannote[126].start 365.44221875
transcript.pyannote[126].end 366.94409375
transcript.pyannote[127].speaker SPEAKER_00
transcript.pyannote[127].start 367.14659375
transcript.pyannote[127].end 367.82159375
transcript.pyannote[128].speaker SPEAKER_00
transcript.pyannote[128].start 369.32346875
transcript.pyannote[128].end 370.03221875
transcript.pyannote[129].speaker SPEAKER_00
transcript.pyannote[129].start 370.40346875
transcript.pyannote[129].end 373.03596875
transcript.pyannote[130].speaker SPEAKER_00
transcript.pyannote[130].start 373.62659375
transcript.pyannote[130].end 376.88346875
transcript.pyannote[131].speaker SPEAKER_00
transcript.pyannote[131].start 377.59221875
transcript.pyannote[131].end 378.09846875
transcript.pyannote[132].speaker SPEAKER_00
transcript.pyannote[132].start 378.57096875
transcript.pyannote[132].end 379.76909375
transcript.pyannote[133].speaker SPEAKER_00
transcript.pyannote[133].start 380.46096875
transcript.pyannote[133].end 383.17784375
transcript.pyannote[134].speaker SPEAKER_00
transcript.pyannote[134].start 383.51534375
transcript.pyannote[134].end 386.08034375
transcript.pyannote[135].speaker SPEAKER_00
transcript.pyannote[135].start 386.90721875
transcript.pyannote[135].end 387.64971875
transcript.pyannote[136].speaker SPEAKER_00
transcript.pyannote[136].start 388.27409375
transcript.pyannote[136].end 391.42971875
transcript.pyannote[137].speaker SPEAKER_00
transcript.pyannote[137].start 392.64471875
transcript.pyannote[137].end 393.42096875
transcript.pyannote[138].speaker SPEAKER_00
transcript.pyannote[138].start 393.94409375
transcript.pyannote[138].end 395.10846875
transcript.pyannote[139].speaker SPEAKER_00
transcript.pyannote[139].start 395.88471875
transcript.pyannote[139].end 396.50909375
transcript.pyannote[140].speaker SPEAKER_00
transcript.pyannote[140].start 398.01096875
transcript.pyannote[140].end 399.51284375
transcript.pyannote[141].speaker SPEAKER_00
transcript.pyannote[141].start 400.49159375
transcript.pyannote[141].end 402.46596875
transcript.pyannote[142].speaker SPEAKER_00
transcript.pyannote[142].start 403.32659375
transcript.pyannote[142].end 409.73909375
transcript.pyannote[143].speaker SPEAKER_00
transcript.pyannote[143].start 410.07659375
transcript.pyannote[143].end 410.95409375
transcript.pyannote[144].speaker SPEAKER_00
transcript.pyannote[144].start 412.69221875
transcript.pyannote[144].end 413.33346875
transcript.pyannote[145].speaker SPEAKER_00
transcript.pyannote[145].start 413.70471875
transcript.pyannote[145].end 414.63284375
transcript.pyannote[146].speaker SPEAKER_00
transcript.pyannote[146].start 415.13909375
transcript.pyannote[146].end 418.31159375
transcript.pyannote[147].speaker SPEAKER_00
transcript.pyannote[147].start 418.76721875
transcript.pyannote[147].end 420.33659375
transcript.pyannote[148].speaker SPEAKER_00
transcript.pyannote[148].start 423.07034375
transcript.pyannote[148].end 425.85471875
transcript.pyannote[149].speaker SPEAKER_00
transcript.pyannote[149].start 425.97284375
transcript.pyannote[149].end 427.59284375
transcript.pyannote[150].speaker SPEAKER_00
transcript.pyannote[150].start 427.99784375
transcript.pyannote[150].end 438.00471875
transcript.pyannote[151].speaker SPEAKER_00
transcript.pyannote[151].start 438.12284375
transcript.pyannote[151].end 442.20659375
transcript.pyannote[152].speaker SPEAKER_00
transcript.pyannote[152].start 444.80534375
transcript.pyannote[152].end 446.94846875
transcript.pyannote[153].speaker SPEAKER_00
transcript.pyannote[153].start 447.75846875
transcript.pyannote[153].end 449.39534375
transcript.pyannote[154].speaker SPEAKER_00
transcript.pyannote[154].start 449.73284375
transcript.pyannote[154].end 450.76221875
transcript.pyannote[155].speaker SPEAKER_00
transcript.pyannote[155].start 451.84221875
transcript.pyannote[155].end 456.26346875
transcript.pyannote[156].speaker SPEAKER_00
transcript.pyannote[156].start 457.19159375
transcript.pyannote[156].end 459.90846875
transcript.pyannote[157].speaker SPEAKER_00
transcript.pyannote[157].start 460.17846875
transcript.pyannote[157].end 467.24909375
transcript.pyannote[158].speaker SPEAKER_00
transcript.pyannote[158].start 468.12659375
transcript.pyannote[158].end 477.23909375
transcript.pyannote[159].speaker SPEAKER_00
transcript.pyannote[159].start 477.96471875
transcript.pyannote[159].end 478.94346875
transcript.pyannote[160].speaker SPEAKER_00
transcript.pyannote[160].start 480.63096875
transcript.pyannote[160].end 483.29721875
transcript.pyannote[161].speaker SPEAKER_00
transcript.pyannote[161].start 484.79909375
transcript.pyannote[161].end 490.48596875
transcript.pyannote[162].speaker SPEAKER_00
transcript.pyannote[162].start 490.50284375
transcript.pyannote[162].end 494.63721875
transcript.pyannote[163].speaker SPEAKER_00
transcript.pyannote[163].start 495.31221875
transcript.pyannote[163].end 497.84346875
transcript.pyannote[164].speaker SPEAKER_00
transcript.pyannote[164].start 498.75471875
transcript.pyannote[164].end 500.45909375
transcript.pyannote[165].speaker SPEAKER_00
transcript.pyannote[165].start 501.45471875
transcript.pyannote[165].end 506.66909375
transcript.pyannote[166].speaker SPEAKER_00
transcript.pyannote[166].start 507.15846875
transcript.pyannote[166].end 508.00221875
transcript.pyannote[167].speaker SPEAKER_00
transcript.pyannote[167].start 508.20471875
transcript.pyannote[167].end 510.19596875
transcript.pyannote[168].speaker SPEAKER_00
transcript.pyannote[168].start 511.74846875
transcript.pyannote[168].end 512.79471875
transcript.pyannote[169].speaker SPEAKER_00
transcript.pyannote[169].start 514.58346875
transcript.pyannote[169].end 522.05909375
transcript.pyannote[170].speaker SPEAKER_00
transcript.pyannote[170].start 522.56534375
transcript.pyannote[170].end 523.25721875
transcript.pyannote[171].speaker SPEAKER_00
transcript.pyannote[171].start 524.05034375
transcript.pyannote[171].end 524.74221875
transcript.pyannote[172].speaker SPEAKER_00
transcript.pyannote[172].start 526.41284375
transcript.pyannote[172].end 527.81346875
transcript.pyannote[173].speaker SPEAKER_00
transcript.pyannote[173].start 528.79221875
transcript.pyannote[173].end 529.21409375
transcript.pyannote[174].speaker SPEAKER_00
transcript.pyannote[174].start 530.59784375
transcript.pyannote[174].end 531.27284375
transcript.pyannote[175].speaker SPEAKER_00
transcript.pyannote[175].start 531.54284375
transcript.pyannote[175].end 534.02346875
transcript.pyannote[176].speaker SPEAKER_00
transcript.pyannote[176].start 535.33971875
transcript.pyannote[176].end 535.87971875
transcript.pyannote[177].speaker SPEAKER_00
transcript.pyannote[177].start 536.23409375
transcript.pyannote[177].end 537.97221875
transcript.pyannote[178].speaker SPEAKER_00
transcript.pyannote[178].start 538.98471875
transcript.pyannote[178].end 541.95471875
transcript.pyannote[179].speaker SPEAKER_00
transcript.pyannote[179].start 542.96721875
transcript.pyannote[179].end 544.51971875
transcript.pyannote[180].speaker SPEAKER_00
transcript.pyannote[180].start 545.09346875
transcript.pyannote[180].end 546.67971875
transcript.pyannote[181].speaker SPEAKER_00
transcript.pyannote[181].start 547.92846875
transcript.pyannote[181].end 548.60346875
transcript.pyannote[182].speaker SPEAKER_00
transcript.pyannote[182].start 550.18971875
transcript.pyannote[182].end 556.85534375
transcript.pyannote[183].speaker SPEAKER_00
transcript.pyannote[183].start 557.46284375
transcript.pyannote[183].end 558.74534375
transcript.pyannote[184].speaker SPEAKER_00
transcript.pyannote[184].start 560.12909375
transcript.pyannote[184].end 562.62659375
transcript.pyannote[185].speaker SPEAKER_00
transcript.pyannote[185].start 563.38596875
transcript.pyannote[185].end 564.09471875
transcript.pyannote[186].speaker SPEAKER_00
transcript.pyannote[186].start 565.57971875
transcript.pyannote[186].end 567.87471875
transcript.pyannote[187].speaker SPEAKER_01
transcript.pyannote[187].start 568.09409375
transcript.pyannote[187].end 568.31346875
transcript.pyannote[188].speaker SPEAKER_00
transcript.pyannote[188].start 568.85346875
transcript.pyannote[188].end 571.06409375
transcript.pyannote[189].speaker SPEAKER_00
transcript.pyannote[189].start 571.62096875
transcript.pyannote[189].end 573.67971875
transcript.pyannote[190].speaker SPEAKER_01
transcript.pyannote[190].start 574.52346875
transcript.pyannote[190].end 579.28221875
transcript.pyannote[191].speaker SPEAKER_00
transcript.pyannote[191].start 579.28221875
transcript.pyannote[191].end 581.40846875
transcript.pyannote[192].speaker SPEAKER_00
transcript.pyannote[192].start 582.01596875
transcript.pyannote[192].end 583.97346875
transcript.pyannote[193].speaker SPEAKER_01
transcript.pyannote[193].start 584.24346875
transcript.pyannote[193].end 584.26034375
transcript.pyannote[194].speaker SPEAKER_00
transcript.pyannote[194].start 584.44596875
transcript.pyannote[194].end 584.95221875
transcript.pyannote[195].speaker SPEAKER_00
transcript.pyannote[195].start 585.45846875
transcript.pyannote[195].end 589.13721875
transcript.pyannote[196].speaker SPEAKER_00
transcript.pyannote[196].start 589.50846875
transcript.pyannote[196].end 590.40284375
transcript.pyannote[197].speaker SPEAKER_01
transcript.pyannote[197].start 589.74471875
transcript.pyannote[197].end 589.94721875
transcript.pyannote[198].speaker SPEAKER_00
transcript.pyannote[198].start 591.55034375
transcript.pyannote[198].end 592.44471875
transcript.pyannote[199].speaker SPEAKER_00
transcript.pyannote[199].start 593.20409375
transcript.pyannote[199].end 596.95034375
transcript.pyannote[200].speaker SPEAKER_00
transcript.pyannote[200].start 598.11471875
transcript.pyannote[200].end 600.94971875
transcript.pyannote[201].speaker SPEAKER_00
transcript.pyannote[201].start 601.42221875
transcript.pyannote[201].end 601.77659375
transcript.pyannote[202].speaker SPEAKER_00
transcript.pyannote[202].start 603.16034375
transcript.pyannote[202].end 605.62409375
transcript.pyannote[203].speaker SPEAKER_00
transcript.pyannote[203].start 606.28221875
transcript.pyannote[203].end 607.69971875
transcript.pyannote[204].speaker SPEAKER_00
transcript.pyannote[204].start 608.99909375
transcript.pyannote[204].end 611.80034375
transcript.pyannote[205].speaker SPEAKER_00
transcript.pyannote[205].start 612.61034375
transcript.pyannote[205].end 615.98534375
transcript.pyannote[206].speaker SPEAKER_00
transcript.pyannote[206].start 617.18346875
transcript.pyannote[206].end 617.57159375
transcript.pyannote[207].speaker SPEAKER_00
transcript.pyannote[207].start 619.71471875
transcript.pyannote[207].end 622.65096875
transcript.pyannote[208].speaker SPEAKER_00
transcript.pyannote[208].start 622.92096875
transcript.pyannote[208].end 624.97971875
transcript.pyannote[209].speaker SPEAKER_00
transcript.pyannote[209].start 625.60409375
transcript.pyannote[209].end 627.51096875
transcript.pyannote[210].speaker SPEAKER_00
transcript.pyannote[210].start 627.86534375
transcript.pyannote[210].end 635.03721875
transcript.pyannote[211].speaker SPEAKER_00
transcript.pyannote[211].start 635.66159375
transcript.pyannote[211].end 637.11284375
transcript.pyannote[212].speaker SPEAKER_00
transcript.pyannote[212].start 637.61909375
transcript.pyannote[212].end 644.13284375
transcript.pyannote[213].speaker SPEAKER_00
transcript.pyannote[213].start 644.35221875
transcript.pyannote[213].end 656.16471875
transcript.pyannote[214].speaker SPEAKER_00
transcript.pyannote[214].start 657.02534375
transcript.pyannote[214].end 661.86846875
transcript.pyannote[215].speaker SPEAKER_00
transcript.pyannote[215].start 662.10471875
transcript.pyannote[215].end 665.96909375
transcript.pyannote[216].speaker SPEAKER_00
transcript.pyannote[216].start 666.35721875
transcript.pyannote[216].end 667.06596875
transcript.pyannote[217].speaker SPEAKER_00
transcript.pyannote[217].start 668.01096875
transcript.pyannote[217].end 669.15846875
transcript.pyannote[218].speaker SPEAKER_00
transcript.pyannote[218].start 670.76159375
transcript.pyannote[218].end 673.07346875
transcript.pyannote[219].speaker SPEAKER_00
transcript.pyannote[219].start 674.35596875
transcript.pyannote[219].end 675.31784375
transcript.pyannote[220].speaker SPEAKER_00
transcript.pyannote[220].start 675.92534375
transcript.pyannote[220].end 676.85346875
transcript.pyannote[221].speaker SPEAKER_00
transcript.pyannote[221].start 677.20784375
transcript.pyannote[221].end 679.85721875
transcript.pyannote[222].speaker SPEAKER_00
transcript.pyannote[222].start 680.43096875
transcript.pyannote[222].end 681.07221875
transcript.pyannote[223].speaker SPEAKER_00
transcript.pyannote[223].start 682.28721875
transcript.pyannote[223].end 685.25721875
transcript.pyannote[224].speaker SPEAKER_00
transcript.pyannote[224].start 686.23596875
transcript.pyannote[224].end 687.29909375
transcript.pyannote[225].speaker SPEAKER_00
transcript.pyannote[225].start 688.41284375
transcript.pyannote[225].end 689.79659375
transcript.pyannote[226].speaker SPEAKER_00
transcript.pyannote[226].start 691.48409375
transcript.pyannote[226].end 692.15909375
transcript.pyannote[227].speaker SPEAKER_00
transcript.pyannote[227].start 692.34471875
transcript.pyannote[227].end 693.20534375
transcript.pyannote[228].speaker SPEAKER_00
transcript.pyannote[228].start 693.72846875
transcript.pyannote[228].end 695.36534375
transcript.pyannote[229].speaker SPEAKER_00
transcript.pyannote[229].start 695.97284375
transcript.pyannote[229].end 697.28909375
transcript.pyannote[230].speaker SPEAKER_01
transcript.pyannote[230].start 697.28909375
transcript.pyannote[230].end 697.67721875
transcript.pyannote[231].speaker SPEAKER_00
transcript.pyannote[231].start 697.64346875
transcript.pyannote[231].end 701.33909375
transcript.pyannote[232].speaker SPEAKER_00
transcript.pyannote[232].start 702.73971875
transcript.pyannote[232].end 703.26284375
transcript.pyannote[233].speaker SPEAKER_00
transcript.pyannote[233].start 703.98846875
transcript.pyannote[233].end 723.74909375
transcript.pyannote[234].speaker SPEAKER_01
transcript.pyannote[234].start 723.74909375
transcript.pyannote[234].end 726.38159375
transcript.pyannote[235].speaker SPEAKER_01
transcript.pyannote[235].start 730.22909375
transcript.pyannote[235].end 735.25784375
transcript.whisperx[0].start 1.322
transcript.whisperx[0].end 14.71
transcript.whisperx[0].text 謝謝主席我請經管委員彭主委請彭主委王委好彭主委是我們授選業資產總額已經高達36兆而他們可運用的資金32兆當中現在照這個分配比
transcript.whisperx[1].start 26.127
transcript.whisperx[1].end 30.331
transcript.whisperx[1].text 竟然國外投資佔了70%高達22兆69.73%當然這不能單獨怪你啦
transcript.whisperx[2].start 45.336
transcript.whisperx[2].end 66.472
transcript.whisperx[2].text 可是我們先比較一下國外他們各國那麼在受險業海外投資的部分佔多少我們就舉對岸中國好了中國受險業只有2%欸2%的資金到國外去韓國不到10%8.3日本21.6美國12%獨獨我們台灣
transcript.whisperx[3].start 76.539
transcript.whisperx[3].end 98.906
transcript.whisperx[3].text 正需要公共建設正需要大家投入我們台灣對我們國家有信心的時候我們竟然放任最大的資金受險業的資金高達百分之七十二十二兆到國外去做投資
transcript.whisperx[4].start 104.724
transcript.whisperx[4].end 130.004
transcript.whisperx[4].text 那這些投資在座各位都是金融專家你們很清楚國外這些投資最大的風險第一個戰爭第二個匯率第三連他們的利率表面上高的地方但是你賺了他利息賠了本金我現在簡單講俄國就好俄國
transcript.whisperx[5].start 134.761
transcript.whisperx[5].end 142.026
transcript.whisperx[5].text 我們竟然有8家售險業只有他1380億的債券好啦 這1380億通通曝險怎麼講 俄烏戰爭還在打那 不講說這個戰爭好了 售險業說 我不知道兩年前他們會打仗那你至少要知道 俄國那麼極權的國家
transcript.whisperx[6].start 165.407
transcript.whisperx[6].end 191.328
transcript.whisperx[6].text 在世界的版圖裡面他是軸心國欸拜託這些壽險業唯利是圖啊利率高啦就去啦好啦他們不但價值理念跟我們自由世界國家不同好啦現在他有戰爭說翻臉就翻臉我光指現在
transcript.whisperx[7].start 193.43
transcript.whisperx[7].end 219.409
transcript.whisperx[7].text 光現在這8家有72張投資型保單現在已經被通知了這只是冰山一小小角11億已經通知說這個到時候要預期啦踩雷啦
transcript.whisperx[8].start 220.618
transcript.whisperx[8].end 239.005
transcript.whisperx[8].text 所以要等到解禁才能收尾所以啊光這11億有八千萬的資金要損失掉我們的保護根本拿不到錢所以這些受險業就是這樣啊賺他要賺賠保護賠就是這樣這八家不只這11億喔
transcript.whisperx[9].start 251.723
transcript.whisperx[9].end 275.14
transcript.whisperx[9].text 這11億是被通知到的因為馬上曝險的後續再1380億那個彭主委我本來一上台想問你說哪8家啦後來我想想其實最主要不是你造成的啦你的前任黃天慕主委他在2020年的時候
transcript.whisperx[10].start 277.042
transcript.whisperx[10].end 301.948
transcript.whisperx[10].text 他就說啊 受選業海外投資這樣的曝險過高金額比例過高啦 他說要降結果他從當年啦 欸 說要降這四年來越降越高從四年前上任的時候64%拿到海外去現在高達70%
transcript.whisperx[11].start 306.349
transcript.whisperx[11].end 335.641
transcript.whisperx[11].text 當然啦他卸任啦他過去也有一些好的表現啦我就不提他啦但是我希望在你的任內尤其受險是你的專業我希望你拿出你的專業堅持你的風骨我認為受險資金投資海外要大幅降低當然財政部也要配合
transcript.whisperx[12].start 337.25
transcript.whisperx[12].end 348.814
transcript.whisperx[12].text 那個部長你就在位子上聽著就好啦財政部應該協調各部會把我們重大的公共建設需要資金的公共建設引領各部會他們趕快跟財政部來協商財政部你幫他們發行公債嘛不是嗎
transcript.whisperx[13].start 361.55
transcript.whisperx[13].end 385.882
transcript.whisperx[13].text 有啦 這麼多年來 蔡總統的任內 有我們去推了這些大概財政部代為發行的這些以內公債有七大項啦 都很有意義的公共建設從桃園航空城 我們國道建設到高速鐵路哇 這些都非常好 自償性也很高
transcript.whisperx[14].start 386.963
transcript.whisperx[14].end 394.909
transcript.whisperx[14].text 可是這7黨加起來才1500億1500億占不到1%天啊這麼努力之下喔那受險業又說啦說啊我們國內財政市場太小啦我們利率太低啦他們是為了保障
transcript.whisperx[15].start 412.722
transcript.whisperx[15].end 413.082
transcript.whisperx[15].text 主席主席
transcript.whisperx[16].start 444.824
transcript.whisperx[16].end 455.996
transcript.whisperx[16].text 一、現在的利率算的保單的期望值那它賠什麼賠這10年來、這20年來都以各該當時的利率
transcript.whisperx[17].start 457.25
transcript.whisperx[17].end 476.562
transcript.whisperx[17].text 不是嗎?然後他額外還賺什麼?他們還賺國內這麼多不動產的投資這些不動產的增值我相信這些經過詳細的計算後那個主委你下去計算一下我有初步的一些概算我認為這些壽險業齁這些業主心思都不單純很邪惡
transcript.whisperx[18].start 484.841
transcript.whisperx[18].end 506.285
transcript.whisperx[18].text 第一點他們對我們建設我們台灣建設我們國家沒有信心啊否則你怎麼會說我們國內證券規模太小我就講我們國家發行的公債就好啊國家發行的公債數十年來超過10兆到現在我們國債的餘額公債喔還有5.8兆5.8兆啊
transcript.whisperx[19].start 514.656
transcript.whisperx[19].end 523.003
transcript.whisperx[19].text 那你至少能先拿個10%、32兆拿個10%、3兆2來買買國債總可以吧?他不!他那不買!這胡說八道嘛!不但!帶頭!對!建設!我們國家沒信心!第二點!康沙保護!
transcript.whisperx[20].start 539.042
transcript.whisperx[20].end 548.387
transcript.whisperx[20].text 他去國外利率高的地方賺他賺現在賠他我剛剛講的俄國這個現在普選啦普選啦已經普選的部分保護就要賠7千萬光11億就要賠7千萬通通賠保護的然後後續他還有1380億這8家所以我希望你私下告訴我哪8家啦
transcript.whisperx[21].start 568.905
transcript.whisperx[21].end 596.722
transcript.whisperx[21].text 我們一起想想辦法看怎麼整他們啦幫保護討回公道嘛可不可以呃我們來看一下資料我們再再來如果可以提供我們就提供給委員參考啊表示案例有資料嘛不是嗎你剛剛說看一下資料再來決定好啦你的因為你剛上任不久我對你不苛責我是對你不苛責但是抱著期許謝謝謝謝委員我期許
transcript.whisperx[22].start 598.171
transcript.whisperx[22].end 617.279
transcript.whisperx[22].text 你能夠拿出風骨跟膽識對!這些惡劣的授權公司不是每一家都惡劣喔就是已經變成金融怪獸的這幾家我剛剛講至少有8家是非常非常惡劣那
transcript.whisperx[23].start 619.775
transcript.whisperx[23].end 634.894
transcript.whisperx[23].text 我有計算啦我希望你下去計算一下就是他們講的這些謬論用什麼方式反駁他他說保障保護的收益所以必須到海外去海外啊利率才高我剛剛跟你講嘛
transcript.whisperx[24].start 636.211
transcript.whisperx[24].end 655.726
transcript.whisperx[24].text 欸!利率高!你賺了人家利率,他從匯率把你整回來。第二點,遇到戰爭,那怎麼辦?第三點,最重要的,我們國家我們的公共建設需要資金,要帶頭對我們國家有信心,要建設我們台灣才對,不是嗎?
transcript.whisperx[25].start 657.099
transcript.whisperx[25].end 684.715
transcript.whisperx[25].text 我們有那麼多的建設需要現在除了大型的公共建設欸!另類的公共建設很多啊!社會住宅、長照、社福機構這些也都有他們的自償性都足以讓受險他們的資金回流去投資,不是嗎?但是!他們自落網紋、自落無睹
transcript.whisperx[26].start 686.297
transcript.whisperx[26].end 700.892
transcript.whisperx[26].text 就是這些業者這麼惡劣的心境所以那個彭主委我因為時間到了齁我對你有期許啦我對部長也有期許啦雖然比較低齁
transcript.whisperx[27].start 702.759
transcript.whisperx[27].end 723.398
transcript.whisperx[27].text 但是那個我希望你針對我講的齁那你做一份簡單二要的一些說明私下你告訴我那怎麼來處理好不好一定要降低這些受險業海外投資佔了70%已經到了非常惡劣離譜的地步啦好謝謝謝謝謝謝委員謝謝好謝謝
transcript.whisperx[28].start 730.523
transcript.whisperx[28].end 735.196
transcript.whisperx[28].text 現在請那個央行、央總裁還有彭主任