tag 标签: Commercial经管大学堂:名校名师名课

相关帖子

版块 作者 回复/查看 最后发表
我国目前有多少个北美精算师 金融类 zlzhy 2013-5-28 6 13982 好大一颗雷 2014-3-4 15:10:40
Real Optimization with SAP® APO attach_img 运营管理(物流与供应链管理) Toyotomi 2013-2-9 2 1536 olderp 2013-9-16 15:32:10
Copal Partners 招聘投行Analyst 职位-北京 经管类求职与招聘 Copal_hr 2013-9-6 0 1109 Copal_hr 2013-9-6 12:27:47
The McKinsey Global Institute Report (免费) attachment 行业分析报告 just_tonight 2013-7-6 49 5761 sw051386 2013-7-25 08:22:03
悬赏 求论文:An empirical study of the interest rate sensitivity of commercial bank.. - [!reward_solved!] attachment 求助成功区 bryant0914 2013-3-29 3 1065 zhouguohaishi 2013-5-29 13:46:57
悬赏 Management and governance of venture capital: A challenge for commercial bank - [!reward_solved!] attachment 求助成功区 brigittaree 2013-3-13 1 1247 Toyotomi 2013-3-13 22:34:16
[下载]A STUDY OF COMMERCIAL INDUSTRY attachment 商学院 MEI眼泪 2007-5-17 0 1219 MEI眼泪 2011-11-26 02:25:28
[下载]How accurate are VAR models at commercial banks attachment 金融学(理论版) wmy2cc 2006-3-19 0 2010 wmy2cc 2011-10-17 16:57:29
[下载] China Commercial Banking Report (Q4-2005) attachment 金融学(理论版) donzhang 2006-2-24 1 1811 brutl 2011-10-14 19:46:19
免费!KPMG:China City Commercial Bank pdf 32p attachment 金融学(理论版) wangrong83 2006-1-7 1 3015 micheal 2011-10-13 10:33:00
The economic of commercial property market.pdf attachment 金融学(理论版) xumw128 2009-6-15 2 1968 自由雨 2010-8-7 00:48:49
BMI_China Commercial Banking Report Q1 2009 attachment 金融学(理论版) hyliuscut 2009-5-26 1 1384 lcwiss 2009-5-26 18:21:00
Commercial due diligence case studies attachment 金融学(理论版) dragonoenix 2009-3-28 0 2109 dragonoenix 2009-3-28 11:24:00
[下载]The Economic of commercial property market attachment 金融学(理论版) baihj 2008-12-18 3 1418 wesker1999 2008-12-18 20:38:00
Business for Development 2008 -PROMOTING COMMERCIAL AGRICULTURE IN AFRICA attachment 农林经济学 tyn 2008-11-22 0 1934 tyn 2008-11-22 12:19:00
[下载]US commercial real estatet akeII Fundamentals to there scue attachment 金融学(理论版) kiddinsh 2008-10-17 0 1316 kiddinsh 2008-10-17 09:48:00
Profits and Balance Sheet Developments of US Commercial Banks (1988-2007) attachment 数据交流中心 lawee 2008-9-20 1 1453 sunlongtop 2008-9-20 15:15:00
[求助]关于Commercial bank customer manager system 的英语文献 求助成功区 QWWEASW 2008-1-27 5 2390 kamenashikazuya 2008-4-6 12:49:00
Chongqing City Commercial Bank 行业分析报告 Jinlin漫步 2007-4-4 0 3478 Jinlin漫步 2007-4-4 03:01:00

相关日志

分享 super commercial
cutelxh 2013-9-29 20:06
表名 南京:工业地产租金:物流仓储 同比增速 环比增速 青岛:工业地产租金:物流仓储 南京:工业地产租金:物流仓储 杭州:工业地产租金:物流仓储 成都:工业地产租金:物流仓储 重庆:工业地产租金:物流仓储 武汉:工业地产租金:物流仓储 宁波:工业地产租金:物流仓储 广州:工业地产租金:物流仓储 深圳:工业地产租金:物流仓储 北京:工业地产租金:物流仓储 天津:工业地产租金:物流仓储 大连:工业地产租金:物流仓储 同比增速 同比增速 同比增速 同比增速 同比增速 同比增速 同比增速 同比增速 同比增速 同比增速 同比增速 同比增速 指标名称 季     季 季 季 季 季 季 季 季 季 季 季 季                         指标ID 元/平方米/月     元/平方米/月 元/平方米/月 元/平方米/月 元/平方米/月 元/平方米/月 元/平方米/月 元/平方米/月 元/平方米/月 元/平方米/月 元/平方米/月 元/平方米/月 元/平方米/月                         2011-03 12.00     11.40 12.00 13.00 20.50 14.80 17.80 14.20 27.30 27.80 29.40 26.60 24.00                         2011-06 12.10     11.60 12.10 13.00 21.30 15.20 18.70 14.60 28.00 27.80 30.90 26.80 23.40                         2011-09 12.40     11.70 12.40 13.30 23.30 15.90 18.80 15.00 28.10 28.80 32.60 26.80 23.90                         2011-12 12.40     11.70 12.40 13.30 23.50 16.00 18.90 15.20 28.20 28.80 33.90 26.90 24.30                         2012-03 12.90 7.50 4.03 11.80 12.90 13.50 23.50 15.90 19.30 15.70 28.40 28.80 34.50 27.10 24.50 3.51 7.50 3.85 14.63 7.43 8.43 10.56 3.60 17.35 1.88 2.08 2012-06 13.10 8.26 1.55 11.80 13.10 14.00 23.70 16.30 19.30 15.50 28.10 28.80 35.30 28.00 25.40 1.72 8.26 7.69 11.27 7.24 3.21 6.16 3.60 14.24 4.48 8.55 2012-09 13.30 7.26 1.53 12.20 13.30 14.00 25.50 16.90 19.80 15.60 28.50 28.50 35.70 28.60 25.60 4.27 7.26 5.26 9.44 6.29 5.32 4.00 -1.04 9.51 6.72 7.11 2012-12 19.30 55.65 45.11 12.20 19.30 21.00 25.60 17.20 19.90 20.40 28.70 28.90 37.60 29.00 25.10 4.27 55.65 57.89 8.94 7.50 5.29 34.21 0.35 10.91 7.81 3.29 指标名称 青岛:优质写字楼新增供应量 上海:优质写字楼新增供应量 南京:优质写字楼新增供应量 杭州:优质写字楼新增供应量 成都:优质写字楼新增供应量 重庆:优质写字楼新增供应量 武汉:优质写字楼新增供应量 宁波:优质写字楼新增供应量 广州:优质写字楼新增供应量 深圳:优质写字楼新增供应量 北京:优质写字楼新增供应量 天津:优质写字楼新增供应量 大连:优质写字楼新增供应量 沈阳:优质写字楼新增供应量 单位 平方米 万平方米 万平方米 万平方米 万平方米 万平方米 万平方米 万平方米 万平方米 万平方米 万平方米 万平方米 万平方米 万平方米 2011-03 0 15.71 6.00 13.90 0.00 0.00 2.50 5.20 17.00 11.00 0.00 0.00 0.00 0.00 2011-06 0 53.94 0.00 7.00 18.10 10.41 0.00 13.05 33.05 9.55 0.00 0.00 0.00 0.00 2011-09 0 16.67 0.00 20.00 0.00 9.27 0.00 5.32 29.85 0.00 10.20 20.39 0.00 10.35 2011-12 0 6.42 0.00 40.73 0.00 0.00 8.66 9.91 9.20 17.50 8.20 0.00 10.50 0.00 2012-03 15 13.70 0.00 0.00 5.00 9.87 10.89 0.00 15.00 7.90 0.00 0.00 0.00 2.30 2012-06 0 12.44 0.00 0.00 29.86 11.56 1.72 3.00 18.50 0.00 0.00 0.00 6.80 0.00 2012-09 0 41.90 0.00 0.00 22.30 7.59 6.47 5.40 5.00 0.00 3.70 0.00 0.00 0.00 2012-12 5 11.50 0.00 10.00 41.00 0.00 7.97 2.00 13.00 0.00 0.00 6.45 4.04 0.00 2013-03 3 4.37 0.00 0.00 6.80 5.10 0.00 5.00 11.00 0.00 0.00 0.00 8.10 0.00 2013-06 2 18.03 6.10 21.20 58.00 5.40 18.00 2.40 21.00 0.00 0.00 0.00 0.00 9.80 指标名称 青岛:优质写字楼空置率 上海:优质写字楼空置率 南京:优质写字楼空置率 杭州:优质写字楼空置率 成都:优质写字楼空置率 重庆:优质写字楼空置率 武汉:优质写字楼空置率 宁波:优质写字楼空置率 广州:优质写字楼空置率 深圳:优质写字楼空置率 北京:优质写字楼空置率 天津:优质写字楼空置率 大连:优质写字楼空置率 沈阳:优质写字楼空置率 单位 % % % % % % % % % % % % % % 2011-03 13.90 8.00 22.30 17.40 25.80 25.00 12.30 17.90 11.80 8.80 11.60 12.70 13.30 11.50 2011-06 11.80 10.10 18.00 16.20 26.00 33.20 9.20 18.20 12.40 9.10 7.60 11.50 11.30 10.30 2011-09 11.50 7.90 16.10 17.30 27.80 33.60 9.70 19.10 12.00 7.30 6.80 23.10 11.70 11.90 2011-12 10.60 7.10 15.60 20.90 25.40 29.90 9.20 19.90 13.40 9.00 6.30 20.30 10.50 10.10 2012-03 15.20 6.00 14.80 19.20 24.90 30.90 14.00 18.90 13.70 8.40 5.00 17.70 9.30 7.80 2012-06 14.60 6.70 14.50 17.90 28.80 33.20 12.50 19.60 13.30 8.10 4.00 15.80 11.90 7.90 2012-09 13.60 8.00 13.70 23.20 31.70 32.10 13.90 22.30 11.90 8.60 3.80 14.10 11.60 7.90 2012-12 14.50 8.00 13.50 23.90 34.60 28.10 17.80 22.70 12.50 8.10 3.20 16.90 13.10 7.40 2013-03 15.00 7.30 12.80 22.90 35.20 27.00 17.00 22.00 12.50 7.80 2.60 16.30 16.50 7.60 2013-06 15.00 7.70 13.30 27.10 40.80 27.40 24.50 21.40 13.80 7.50 2.30 15.70 16.00 12.80 指标名称 青岛:优质写字楼租金 上海:优质写字楼租金 南京:优质写字楼租金 杭州:优质写字楼租金 成都:优质写字楼租金 重庆:优质写字楼租金 武汉:优质写字楼租金 宁波:优质写字楼租金 广州:优质写字楼租金 深圳:优质写字楼租金 北京:优质写字楼租金 天津:优质写字楼租金 大连:优质写字楼租金 沈阳:优质写字楼租金 单位 元/平方米/月 元/平方米/月 元/平方米/月 元/平方米/月 元/平方米/月 元/平方米/月 元/平方米/月 元/平方米/月 元/平方米/月 元/平方米/月 元/平方米/月 元/平方米/月 元/平方米/月 元/平方米/月 2011-03 76.00 232.30 87.90 111.90 96.70 67.50 59.70 68.80 107.50 139.00 248.50 109.30 76.10 70.10 2011-06 76.40 244.40 89.00 112.30 97.90 71.70 61.80 68.60 115.40 145.20 301.10 110.20 77.50 70.80 2011-09 76.70 252.90 92.30 114.00 98.10 73.80 63.30 72.10 124.40 150.60 327.60 118.60 81.70 72.30 2011-12 77.20 256.10 94.20 111.20 98.60 75.70 71.00 72.20 132.00 156.80 349.80 119.80 86.50 76.20 2012-06 82.00 258.10 98.30 115.80 101.70 80.80 77.00 71.50 128.20 160.30 401.30 130.70 91.20 83.80 2012-03 82.30 257.30 96.30 115.70 99.70 75.90 75.30 72.90 133.00 161.80 387.00 120.20 87.40 78.30 2012-09 82.50 253.90 99.20 121.20 101.20 92.50 82.20 67.70 128.50 163.80 407.40 131.00 92.70 84.40 2012-12 82.80 251.80 99.10 122.80 100.50 91.80 88.80 66.40 128.80 165.80 409.00 132.10 93.40 85.20 2013-03 87.00 250.20 99.70 122.50 100.60 92.70 90.10 65.90 130.30 165.30 409.90 132.20 92.60 85.30 2013-06 87.50 250.00 103.50 94.50 91.70 91.20 66.50 132.70 167.80 409.60 132.20 92.80 85.60 指标名称 青岛:优质零售物业新增供应量 上海:优质零售物业新增供应量 南京:优质零售物业新增供应量 杭州:优质零售物业新增供应量 成都:优质零售物业新增供应量 重庆:优质零售物业新增供应量 武汉:优质零售物业新增供应量 宁波:优质零售物业新增供应量 广州:优质零售物业新增供应量 深圳:优质零售物业新增供应量 北京:优质零售物业新增供应量 天津:优质零售物业新增供应量 大连:优质零售物业新增供应量 沈阳:优质零售物业新增供应量 单位 万平方米 万平方米 万平方米 万平方米 万平方米 万平方米 万平方米 万平方米 万平方米 万平方米 万平方米 万平方米 万平方米 万平方米 2011-03 5.60 3.00 0.00 0.00 12.00 13.00 6.80 0.00 8.30 0.00 0.00 0.00 0.00 25.50 2011-06 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.80 0.00 9.79 5.00 0.00 31.90 2011-09 0.00 0.00 0.00 5.00 0.00 0.00 39.41 0.00 12.00 0.00 11.20 0.00 0.00 38.80 2011-12 0.00 0.00 0.00 0.00 0.00 13.40 4.20 0.00 18.00 0.00 12.50 8.00 0.00 0.00 2012-03 0.00 2.04 0.00 0.00 0.00 3.88 0.00 0.00 31.80 0.00 31.20 25.00 0.00 9.45 2012-06 6.80 7.00 15.00 4.00 24.40 0.00 0.00 0.00 0.00 0.00 13.36 4.50 8.00 15.70 2012-09 0.00 2.20 0.00 0.00 8.25 0.00 9.93 5.00 0.00 12.00 8.40 27.50 0.00 25.00 2012-12 13.10 0.00 3.00 0.00 29.00 9.60 0.00 12.60 12.00 10.00 37.00 2.90 0.00 29.00 2013-03 7.20 0.00 0.00 0.00 24.50 31.60 0.00 0.00 9.00 19.80 18.50 13.10 0.00 0.00 2013-06 0.00 0.00 0.00 7.50 8.90 0.00 0.00 2.00 0.00 0.00 13.50 0.00 20.00 0.00 指标名称 青岛:优质零售物业首层租金 上海:优质零售物业首层租金 南京:优质零售物业首层租金 杭州:优质零售物业首层租金 成都:优质零售物业首层租金 重庆:优质零售物业首层租金 武汉:优质零售物业首层租金 宁波:优质零售物业首层租金 广州:优质零售物业首层租金 深圳:优质零售物业首层租金 北京:优质零售物业首层租金 天津:优质零售物业首层租金 大连:优质零售物业首层租金 沈阳:优质零售物业首层租金 单位 元/平方米·天 元/平方米/天 元/平方米/天 元/平方米/天 元/平方米/天 元/平方米/天 元/平方米/天 元/平方米/天 元/平方米/天 元/平方米/天 元/平方米/天 元/平方米/天 元/平方米/天 元/平方米/天 2011-03 22.40 50.10 31.50 28.70 37.40 22.40 21.50 24.10 47.20 26.70 33.90 21.50 25.50 22.10 2011-06 22.40 52.50 32.10 29.10 28.50 22.30 21.90 23.90 46.90 27.40 35.90 21.80 25.50 22.30 2011-09 22.40 52.50 32.20 29.30 28.90 22.60 20.50 24.10 48.10 29.00 38.90 21.90 25.50 22.00 2011-12 22.60 53.40 33.00 29.50 28.20 22.80 19.80 24.20 46.50 29.30 38.30 21.40 24.80 22.00 2012-06 22.00 54.40 34.10 30.60 27.80 22.50 20.60 24.80 46.70 31.10 38.00 21.50 22.90 21.40 2012-03 22.60 54.00 33.90 30.10 27.90 22.40 19.80 24.70 46.60 30.40 38.70 21.50 25.10 21.90 2012-09 21.90 60.80 34.30 33.80 28.10 24.20 21.30 24.40 46.70 30.90 39.40 21.60 23.00 21.10 2012-12 21.50 62.10 34.40 34.20 27.80 24.40 21.70 24.10 46.10 30.80 40.20 22.20 23.10 21.00 2013-03 22.10 63.00 34.90 35.60 27.70 23.20 22.20 24.00 44.80 31.10 40.80 21.60 23.20 20.90 2013-06 22.10 35.40 36.80 28.10 23.40 22.30 24.40 44.60 30.90 40.90 21.60 23.20 20.50 指标名称 青岛:优质零售物业空置率 上海:优质零售物业空置率 南京:优质零售物业空置率 杭州:优质零售物业空置率 成都:优质零售物业空置率 重庆:优质零售物业空置率 武汉:优质零售物业空置率 宁波:优质零售物业空置率 广州:优质零售物业空置率 深圳:优质零售物业空置率 北京:优质零售物业空置率 天津:优质零售物业空置率 大连:优质零售物业空置率 沈阳:优质零售物业空置率 单位 % % % % % % % % % % % % % % 2011-03 8.70 6.00 3.20 1.00 13.60 12.60 4.90 0.90 9.40 8.50 11.10 13.50 6.90 19.50 2011-06 8.10 5.80 2.70 0.80 13.10 10.80 3.20 1.50 8.30 8.50 9.90 12.70 6.50 14.10 2011-09 7.80 5.50 3.50 1.40 12.80 10.20 3.80 1.00 8.20 6.40 9.50 11.40 6.80 18.80 2011-12 7.40 5.70 9.90 1.50 11.00 9.60 1.90 2.00 9.40 4.30 10.40 10.90 5.80 16.70 2012-03 6.90 5.60 2.70 1.40 11.60 8.50 2.60 0.60 9.30 4.00 12.60 13.50 5.80 16.30 2012-06 7.30 6.30 6.00 1.60 10.50 4.60 1.40 0.70 8.80 4.00 11.80 10.80 8.80 17.70 2012-09 6.80 9.90 4.70 1.50 10.90 4.00 1.30 5.40 8.50 4.40 11.00 16.10 8.20 15.80 2012-12 5.00 9.20 6.70 1.50 10.00 6.60 1.30 4.50 9.70 5.50 11.30 12.80 7.30 18.10 2013-03 3.00 8.00 5.60 1.30 11.60 5.10 1.00 4.30 9.90 6.60 10.80 9.60 6.90 18.90 2013-06 2.70 7.40 8.60 2.80 10.60 4.80 0.60 3.20 10.00 6.40 11.30 9.20 5.90 20.20
个人分类: 数据|0 个评论
分享 人均commercial shop-2011
cutelxh 2013-9-13 19:40
2011年底城市综合体数量 图表 1 : 2008-2011 年全国 35 个主要城市城镇人均商业面积概况(单位:平方米) 城市 体量 数量 万平方米 个 区域 人均商业面积 人均商业面积 人均商业面积 人均商业面积 北京 1684 42         上海 584 23 -2008 -2010 (餐饮、零售)( 2008 ) (餐饮、零售)( 2010 ) 深圳 276 11 1 全国 0.6 0.81 0.47 0.6 广州 573 15 1 厦门 3.7 4.3 1.96 2.08 2 宁波 3.17 4.28 2.07 2.63 3 银川 2.48 3.32 2 2.63 1 沈阳 1206 14 4 合肥 1.98 2.88 1.28 1.75 2 重庆 1050 16 5 北京 1.87 2.56 0.65 0.92 3 成都 522 17 6 呼和浩特 1.51 2.54 1.12 2 4 南京 469 13 7 杭州 1.79 2.42 0.97 1.21 5 武汉 380 9 8 上海 1.56 2.01 0.88 1.05 6 天津 322 7 9 重庆 1.61 1.97 1.3 1.58 7 长春 133 4 10 深圳 1.89 1.95 1.23 1.23 8 苏州 260 10 11 郑州 1.13 1.82 0.79 1.15 9 贵阳 186 4 12 沈阳 1.1 1.78 0.95 1.55 10 青岛 118 3 13 长沙 1.4 1.7 1.08 1.29 11 西安 78 4 14 昆明 1.16 1.61 0.85 1.16 12 合肥 70 1 15 贵阳 1.07 1.58 0.7 0.98 13 昆明 43 2 16 哈尔滨 1.29 1.53 1.07 1.27 14 宁波 133 3 17 成都 1.17 1.51 0.9 1.05 18 广州 1.07 1.49 0.61 0.83 19 青岛 1.16 1.47 0.83 1.09 20 乌鲁木齐 1.14 1.42 0.84 1.04 21 天津 1.06 1.41 0.72 0.97 22 大连 1.07 1.33 0.89 1.08 23 福州 1.01 1.13 0.76 0.84 24 南宁 0.88 1.13 0.6 0.78 25 长春 0.63 0.96 0.51 0.81 26 南京 0.85 0.96 0.47 0.55 27 西安 0.67 0.92 0.3 0.43 28 武汉 0.66 0.84 0.45 0.58 29 南昌 0.56 0.79 0.48 0.63 30 海口 0.59 0.73 0.43 0.5 31 兰州 0.54 0.71 0.35 0.49 32 太原 0.54 0.64 0.31 0.39 33 济南 0.47 0.58 0.23 0.29 34 西宁 0.49 0.43 0.3 0.28 35 石家庄 0.22 0.27 0.16 0.19
个人分类: 数据|0 个评论
分享 credit performance
insight 2013-6-1 17:10
http://www.phil.frb.org/consumer-credit-and-payments/statistics/ Consumer Debt Aggregate Indebtedness of Consumers Total consumer credit outstanding is broken down into two categories in the G.19 report: revolving and nonrevolving credit. The G.19, a Federal Reserve report covering consumer credit, is released around the fifth business day of each month. The G.19 report contains statistics for the amounts of outstanding credit among several major holders of consumer credit. Also included are the terms of credit across a variety of institutions and types of loans. Access at: http://www.federalreserve.gov/releases/g19/current/g19.htm Consumer Credit (G.19) (EOP, SA, Bil.$) 2006 2007 2008 2009 2010 2011 2012 Q3 2012 Q4 Total Outstanding $2,361.8 $2,506.3 $2,525.9 $2,420.2 $2,522.2 $2,615.7 $2,723.8 $2,768.2 Revolving $924.9 $1,002.9 $1,005.2 $917.2 $840.7 $842.5 $845.1 $845.8 Nonrevolving $1,436.9 $1,503.4 $1,520.7 $1,503.0 $1,681.5 $1,773.2 $1,878.6 $1,922.4 Notes: Consumer credit covers most short- and intermediate-term credit extended to individuals. It includes revolving credit (credit card credit and balances outstanding on unsecured revolving lines of credit) and nonrevolving credit (such as secured and unsecured credit for automobiles, mobile homes, trailers, durable goods, vacations, and other purposes). Consumer credit excludes loans secured by real estate (such as mortgage loans, home equity loans, and home equity lines of credit). EOP = end of period, SA = seasonally adjusted Consumer Debt Composition The data used to show consumer debt composition come from two subsections of the Federal Reserve Flow of Funds Accounts (Z.1) . These subsections (Tables D.1 and D.3) measure debt growth and debt outstanding in several sectors. The Federal Reserve Board of Governors releases these statistics during the second week of March, June, September, and December. Access at: http://www.federalreserve.gov/releases/z1/ under "Debt growth, borrowing and debt outstanding tables." Consumer Debt Composition and Growth 2006 2007 2008 2009 2010 2011 Q3.12 Q4.12 Debt Outstanding (SA, $ Bil) Credit Market $12,856.0 $13,711.5 $13,688.0 $13,410.1 $13,073.7 $12,869.4 $12,755.1 $12,830.8 Home Mortgages $9,896.5 $10,579.7 $10,519.1 $10,368.1 $9,889.8 $9,660.7 $9,449.3 $9,430.5 Consumer Credit $2,385.0 $2,528.8 $2,548.9 $2,438.7 $2,541.6 $2,627.4 $2,733.8 $2,779.2 Growth Rate (SAAR, %) Credit Market 9.62 6.41 -0.19 -1.71 -2.23 -1.60 -1.95 2.45 Home Mortgage 10.79 6.64 -0.60 -1.42 -2.98 -2.33 -3.09 -0.80 Consumer Credit 4.94 5.79 0.81 -4.62 -1.25 3.35 4.20 6.65 Notes: Home mortgages and consumer credit will not add up to total household debt because the other four components are unpublished. The four unpublished components are municipal securities, bank loans nec, other loans and advances, and commercial mortgages SA = seasonally adjusted, SAAR = seasonally adjusted annual rate Data are on an end-of-period basis and may differ from monthly average statistics in the Board's H.6 release. Credit Performance Loan Charge-Offs The charge-off statistics released by the Federal Reserve Credit Performance Loan Charge-Offs The charge-off statistics released by the Federal Reserve Board are calculated from data available in the Report of Condition and Income (Call Report), filed each quarter by all commercial banks. Charge-off rates for any category of loan are defined as the flow of a bank's net charge-offs (gross charge-offs minus recoveries) during a quarter divided by the average level of its loans outstanding over that quarter. Data for each calendar quarter become available approximately 60 days after the end of the quarter. Access at: http://www.federalreserve.gov/releases/chargeoff/ Loan Charge-Offs 2006 2007 2008 2009 2010 2011 Q3.12 Q4.12 Charge-Off Rate1 (SAAR, %) Consumer Loans 2.01 2.50 3.53 5.49 5.88 3.62 2.47 2.50 Credit Cards 3.54 4.00 5.52 9.40 9.34 5.68 3.86 4.06 Residential Real Estate Loans2 0.10 0.26 1.28 2.36 2.12 1.58 1.74 1.08 Net Charge-Offs3 (NSA, $ Mil) Consumer Loans $16,314 $21,987 $34,190 $52,961 $74,345 $43,010 $7,305 $7,558 Credit Cards $11,007 $13,339 $19,950 $34,883 $61,886 $35,017 $5,788 $5,906 Residential Real Estate Loans2 $1,835 $5,036 $25,513 $49,540 $44,273 $32,155 $9,058 $5,669 Source: Federal Financial Institutions Examination Council. FRB Call Report. Board of Governors of the Federal Reserve System. Notes: SAAR = seasonally adjusted annual rate, NSA = not seasonally adjusted 1 Charge-off rate is the flow of a bank's net charge-offs (gross charge-offs minus recoveries) during a quarter divided by the average level of its loan outstanding over that quarter multiplied by 400 to express the ratio as an annual percentage rate. Charged-off loans are reported on schedule RI-B and the average levels of loans on schedule RC-K. 2 Residential real estate loans include loans secured by one- to four-family properties, including home equity lines of credit. 3 Charge-offs are the value of loans and leases removed from the books and charged against loss reserves. Credit Card Charge-Offs: Managed Assets Basis* This chart is derived from data available in the Report of Condition and Income (Call Report), filed each quarter by all commercial banks. The charge-off rate is calculated by dividing the sum of on- and off-balance-sheet credit card net charge-offs (gross charge-offs minus recoveries) during a quarter by the on- and off-balance-sheet total amount outstanding for the end of the previous quarter. *The charge-off rate presented here may vary slightly from measures reported by the Board because the Board’s charge-off rate is calculated on the basis of average quarterly credit card assets. ( http://www.federalreserve.gov/releases/chargeoff/ ) Source: Federal Financial Institutions Examination Council. FRB Call Report. Note: The on-balance-sheet net charge-offs calculation comes from the aggregation of variables RIADB514 (gross charge-offs) and RIADB515 (recoveries) from the Call Report. The total amount outstanding for on-balance-sheet assets comes from the aggregation of variable RCFDB538 from the Call Report. For off-balance-sheet assets, the calculation of net charge-offs comes from the aggregation of variables RIADB749 (gross charge-offs) and RIADB756 (recoveries) from the Call Report. The total amount outstanding for off-balance-sheet assets comes from the aggregation of variable RCFDB707 from the Call Report. The bars depict on- and off-balance-sheet charge-offs in the quarter in which they occurred. The charge-off rate is the ratio of net charge-offs realized in the quarter divided by the sum of on- and off-balance-sheet credit card assets from the end of the previous quarter. Loan Delinquencies The delinquency statistics presented on the Federal Reserve Board's website are calculated from data available in the Report of Condition and Income (Call Report), filed each quarter by all commercial banks. The delinquency rate for any loan category is the ratio of the dollar amount of a bank's delinquent loans in that category to the dollar amount of total loans outstanding in that category. Data for each calendar quarter become available approximately 60 days after the end of the quarter. Access at: http://www.federalreserve.gov/releases/chargeoff/ Loan Delinquencies 2006 2007 2008 2009 2010 2011 Q3.12 Q4.12 Delinquency Rate1 (SAAR, %) Consumer Loans 2.90 3.13 3.76 4.70 4.15 3.23 2.77 2.62 Credit Cards 4.01 4.25 5.03 6.53 4.90 3.54 2.82 2.73 Residential Real Estate Loans2 1.73 2.54 4.99 9.14 10.84 10.41 10.60 10.07 Delinquencies3 (NSA, EOP, $ Mil) Consumer Loans $26,104 $33,737 $44,007 $46,140 $46,064 $38,573 $33,554 $33,684 Credit Cards $13,738 $17,376 $22,935 $24,368 $27,489 $20,950 $17,295 $17,563 Residential Real Estate Loans2 $39,925 $65,942 $145,024 $232,739 $220,389 $217,754 $221,307 $215,039 Source: Federal Financial Institutions Examination Council. FRB Call Report. Board of Governors of the Federal Reserve System. Notes: NSA = not seasonally adjusted, EOP = end of period 1 "Delinquency Rate" is delinquent loan/lease as a percent of end-of-period loan/lease balance 2 Residential real estate loans include loans secured by one- to four-family properties, including home equity lines of credit. 3 Delinquent loans include those past due 30 days or more and still accruing interest, as well as those on nonaccrual status. Bankruptcy The statistics used to measure bankruptcy filings come from the Administrative Office of the United States Courts. Included are bankruptcy filings by both business and nonbusiness entities. It is also important to note the surge of bankruptcies in 2005 due to the Bankruptcy Abuse Prevention and Consumer Protection Act (BAPCPA), which took effect on October 17, 2005. Access at: http://www.uscourts.gov/bnkrpctystats/bankruptcystats.htm Bankruptcy Filings 2006 2007 2008 2009 2010 2011 Q3.12 Q4.12 Total 621,349 849,412 1,115,813 1,472,238 1,592,669 1,410,918 298,310 273,878 Nonbusiness 601,535 821,275 1,072,952 1,411,708 1,536,623 1,363,015 288,995 264,647 Source: Administrative Office of the United States Courts Note: Annual data aggregated from the monthly and quarterly series do not match the annual series because the annual series includes revisions, while the monthly and quarterly series do not. Credit Standards and the Demand for Credit The data used to describe banks’ credit standards and demand for consumer loans come from two questions asked by the Senior Loan Officer Opinion Survey (SLOOS). This survey covers approximately 60 large domestic banks and 24 U.S. branches and agencies of foreign banks. The Federal Reserve generally conducts the survey quarterly, timing it so that results are available for the January/February, April/May, August, and October/November meetings of the Federal Open Market Committee. Questions cover changes in the standards and terms of the banks' lending and the state of business and household demand for loans, or occasionally specific topics of current interest. Access at: http://www.federalreserve.gov/boarddocs/snloansurvey/ Note: The height of the line in the above graph is the net percentage of banks tightening credit standards for new credit card applicants. Note: The height of the line in the above graph is the net percentage of banks with strengthening demand for consumer loans. Credit at the Family Level The data used to describe the revolving credit of families come from the Survey of Consumer Finances (SCF). The SCF is a triennial survey of the balance sheet, pension, income, and other demographic characteristics of U.S. families. The survey also gathers information on the use of financial institutions. Access at: http://www.federalreserve.gov/pubs/oss/oss2/scfindex.html Percent of Families with a Transaction Account (%) 92 95 98 01 04 07 10 All Families 86.9 87.4 90.6 91.4 91.3 92.1 92.5 Income Percentile Less than 20% 62.5 63.2 68.8 71.6 75.5 74.9 76.2 20-39.9% 83.9 85.2 90.3 90.3 87.3 90.1 91.1 40-59.9% 91.7 92.0 95.4 96.6 95.9 96.3 96.4 60-79.9% 97.6 97.3 98.9 99.1 98.4 99.3 98.9 80-89.9% 98.8 98.7 99.6 99.7 99.1 100.0 99.8 90-100% 98.7 99.8 100.0 99.2 100.0 100.0 99.9 Age of Family Head 35 or Younger 81.3 80.9 84.7 81.7 86.4 87.3 89.0 35-44 86.8 87.6 90.5 91.1 90.8 91.2 90.6 45-54 88.9 89.2 94.1 92.7 91.8 91.7 92.5 55-64 90.2 88.8 93.9 93.8 93.2 96.4 94.2 65-74 88.9 91.7 94.1 93.8 93.9 94.6 95.8 75 or Older 91.8 93.2 90.0 93.7 96.4 95.3 96.4 Housing Status Homeowner 94.0 95.3 96.4 96.7 96.0 97.3 97.4 Renter or Not Homeowner 74.3 72.9 79.4 80.3 80.9 80.8 82.4 Median Value of Transaction Accounts for Families with Holdings (2010 dollars) 92 95 98 01 04 07 10 All Families 3,500 3,000 4,000 4,800 4,300 4,200 3,500 Income Percentile Less than 20% 800 1,000 900 1,100 700 800 700 20-39.9% 1,700 1,800 2,000 2,200 1,700 1,700 1,500 40-59.9% 3,000 2,300 3,000 3,400 3,500 2,900 2,800 60-79.9% 4,200 3,500 5,700 6,400 7,500 6,300 5,300 80-89.9% 7,300 6,100 10,000 11,600 12,700 13,500 11,100 90-100% 23,500 18,800 24,000 31,900 32,200 38,400 35,000 Age of Family Head 35 or younger 2,000 1,700 2,000 2,100 2,100 2,500 2,100 35-44 3,100 2,800 3,800 4,200 3,500 3,600 2,500 45-54 4,500 4,200 5,900 5,600 5,500 5,200 3,500 55-64 4,500 4,400 5,400 6,700 7,700 5,400 5,000 65-74 5,800 4,600 7,500 9,800 6,300 8,100 5,700 75 or Older 6,100 7,100 8,000 8,900 7,400 6,400 7,200 Housing Status Homeowner 5,200 4,200 6,500 7,100 6,900 6,500 5,800 Renter or Not Homeowner 1,500 1,600 1,500 1,500 1,300 1,300 1,000 Percent of Households with a Credit Card Balance (%) 92 95 98 01 04 07 10 All Families 43.7 47.3 44.1 44.4 46.2 46.1 39.4 Income Percentile Less than 20% 23.4 26.0 24.5 30.3 28.8 25.7 23.2 20-39.9% 41.9 43.2 40.9 44.5 42.9 39.5 33.4 40-59.9% 51.9 52.9 50.1 52.8 55.1 54.8 45.0 60-79.9% 55.6 60.0 57.4 52.6 56.1 62.1 53.1 80-89.9% 53.6 61.0 53.1 50.3 57.6 55.8 51.0 90-100% 37.9 47.3 42.1 33.1 38.5 40.6 33.6 Age of Family Head 35 or Younger 51.8 54.7 50.7 49.6 47.5 48.5 38.7 35-44 50.9 55.9 51.3 54.1 58.8 51.7 45.6 45-54 48.9 56.4 52.5 50.4 54.0 53.6 46.2 55-64 37.2 43.2 45.7 41.6 42.1 49.9 41.3 65-74 32.1 30.5 29.2 30.0 31.9 37.0 31.9 75 or Older 20.1 17.5 11.2 18.4 23.5 18.8 21.7 Housing Status Homeowner 46.6 51.1 46.2 44.4 48.8 50.1 43.1 Renter or Not Homeowner 38.6 40.3 40.0 44.3 40.4 37.3 31.8 Median Value of Credit Card Balances for Households with Holdings (2010 dollars) 92 95 98 01 04 07 10 All Families 1,500 2,100 2,300 2,300 2,500 3,100 2,600 Income Percentile Less than 20% 800 1,000 1,300 1,200 1,200 1,000 1,000 20-39.9% 1,200 1,700 1,600 1,500 2,100 1,900 1,500 40-59.9% 1,4000 2,100 2,500 2,500 2,500 2,500 2,200 60-79.9% 2,200 2,200 2,900 2,800 3,500 4,200 3,100 80-89.9% 2,300 2,800 2,700 4,600 3,100 5,800 5,900 90-100% 3,400 4,000 4,000 3,400 4,600 7,900 8,000 Age of Family Head 35 or younger 1,400 1,800 2,000 2,500 1,700 1,900 1,600 35-44 1,800 2,700 2,700 2,500 2,900 3,700 3,500 45-54 2,300 2,800 2,400 2,800 3,300 3,800 3,500 55-64 1,500 1,800 2,700 2,300 2,500 3,800 2,800 65-74 1,200 1,100 1,500 1,200 2,500 3,100 2,200 75 or Older 800 500 900 900 1,200 800 1,800 Housing Status Homeowner 1,700 2,100 2,700 2,600 2,900 3,800 3,400 Renter or Not Homeowner 1,400 1,700 1,700 1,500 1,700 1,400 1,300 Debtors with Payment-to-Income Ratio Greater Than 40 Percent (%) 92 95 98 01 04 07 10 All Families 11.4 11.7 13.6 11.8 12.3 14.8 13.8 Income Percentile Less than 20% 27.1 27.4 29.8 29.3 26.8 26.9 26.1 20-39.9% 16.0 18.0 18.3 16.6 18.6 19.5 18.6 40-59.9% 10.8 9.9 15.9 12.3 13.8 14.5 15.4 60-79.9% 8.2 7.7 9.8 6.5 7.3 12.9 11.0 80-89.9% 3.5 4.7 3.5 3.5 2.6 8.2 5.3 90-100% 2.4 2.3 2.8 2.0 1.5 3.8 2.9 Age of Family Head 35 or Younger 11.1 12.1 12.9 12.0 12.8 15.1 11.6 35-44 12.2 9.9 12.5 10.1 12.4 12.8 16.4 45-54 10.5 12.3 12.8 11.6 13.3 16.3 15.5 55-64 14.6 15.1 14.0 12.3 10.3 14.5 13.0 65-74 7.4 11.3 18.1 14.7 11.6 15.6 12.1 75 or Older 12.0 7.4 21.4 14.6 10.7 13.9 11.9 Housing Status Owner 14.5 14.3 16.5 14.7 15.0 18.1 17.1 Renter or Not Homeowner 4.9 5.8 6.5 4.2 4.3 5.4 5.0 Note: The payment-to-income ratio reflects the sum of family debt payments divided by the household income. Debtors with Any Payment Past Due 60 Days or More (%) 92 95 98 01 04 07 10 All Families 6.0 7.1 8.1 7.0 8.9 7.1 10.8 Percentile of income Less than 20% 11.0 10.4 13.0 13.4 15.9 15.1 21.2 20-39.9% 9.3 10.2 12.4 11.7 13.8 11.5 15.2 40-59.9% 6.9 8.8 10.0 7.9 10.4 8.3 10.2 60-79.9% 4.4 6.6 5.9 4.0 7.1 4.1 8.8 80-89.9% 1.8 2.8 3.9 2.6 2.3 2.1 5.4 90-100% 1.0 1.0 1.6 1.3 0.3 0.2 2.1 Age of Family Head 35 or Younger 8.3 8.8 11.1 11.9 13.7 9.4 10.4 35-44 6.8 7.7 8.4 5.9 11.7 8.6 15.7 45-54 5.4 7.4 7.4 6.2 7.6 7.3 12.6 55-64 4.7 3.2 7.5 7.1 4.2 4.9 8.4 65-74 1.0 5.3 3.1 1.5 3.4 4.4 6.1 75 or Older 1.8 5.4 1.1 0.8 3.9 1.1 3.2 Housing status Owner 3.6 5.1 6.1 4.3 5.6 4.8 8.7 Renter or Not Homeowner 11.2 11.6 12.9 14.0 18.6 13.5 16.6 Maps of Local Credit Quality The Federal Reserve Bank of New York publishes regional information on consumer credit conditions addressing mortgage delinquency and foreclosure issues. The U.S. Credit Conditions section offers interactive maps and data on auto and student loan delinquencies and mortgage "roll" rates. These features complement existing maps and spreadsheets on mortgage foreclosures and delinquencies, measures of subprime and alt-A mortgages, and bank credit card delinquencies. The data are available at the state and county level. Access at: http://data.newyorkfed.org/creditconditions/ Noncash Payments Checks Credit Cards Debit Cards Prepaid ACH Adoption of Payments SCPC Noncash Payments The data used to describe noncash payments come from the 2007 and 2010 editions of the Federal Reserve Payments Studies. The Federal Reserve Payments Study is a triennial survey of the payments industry first conducted in 2001. These studies are part of a Federal Reserve System effort to track noncash payments in the United States, and they reflect the efforts of hundreds of organizations across the country. Access at: http://www.frbservices.org/files/communications/pdf/research/2010_payments_study.pdf Noncash Payments 2003 2006 2009 Volume (Bil) Value ($ Tril) Volume (Bil) Value ($ Tril) Volume (Bil) Value ($ Tril) Total Noncash Payments 81.4 $67.6 95.2 $75.7 109.0 $72.2 Checks (paid)1 37.3 $41.1 30.5 $41.6 24.5 $31.6 Debit Card 15.6 $0.6 25.0 $1.0 37.9 $1.4 Signature 10.3 $0.4 15.7 $0.6 23.4 $0.9 PIN 5.3 $0.2 9.4 $0.4 14.5 $0.6 Prepaid Card2 3.3 $0.08 6.0 $0.14 EBT2 0.8 * 1.1 $0.03 2.0 $0.05 Credit Card 19.0 $1.7 21.7 $2.1 21.6 $1.9 ACH 8.8 $24.1 14.6 $31.0 19.1 $37.6 Source: 2007 and 2010 Federal Reserve Payments Studies 1 Nominal values of checks (paid) increased (displayed in the table). However, in constant dollars the value of checks (paid) showed a growth rate of -2.5 percent per year. 2 Revisions made to the 2007 and 2010 studies re-categorized prepaid cards so as not to include them with debit card estimates *Values too small to display. The value of EBT payments was $22 billion in 2003 and $30 billion in 2006. Checks The data used to describe checks come from the 2007 and the 2010 Federal Reserve Payments Studies and the 2010 Federal Reserve Check Sample Study. The Federal Reserve Payments Study is a triennial survey of the payments industry first conducted in 2001. These studies are part of a Federal Reserve System effort to track noncash payments in the United States, and they reflect the activities of financial institutions, networks, and other providers of payment services across the country. The 2010 Depository Institution Study is a random sample of depository institutions that collects the number and value of different types of payments and contributes to the estimates of total checks written. The 2010 Check Sample Study is a random sample of checks processed by 11 large commercial banks used to estimate the distribution of checks among various counterparties. Access at: http://www.frbservices.org/files/communications/pdf/research/2010_payments_study.pdf Checks Paid by Type of Depository Institution 2003 2006 2009 Number (Bil) Value ($ Tril) Number (Bil) Value ($ Tril) Number (Bil) Value ($ Tril) Total 37.3 $41.1 30.5 $41.6 24.5 $31.6 Commercial Banks 29.7 $38.4 25.0 $39.0 20.7 $29.2 Credit Unions 4.2 $0.9 2.8 $0.8 2.1 $0.7 Savings Institutions 3.0 $1.5 2.3 $1.6 1.3 $1.3 Source: 2007 and 2010 Federal Reserve Payments Studies Distribution of Checks by Dollar Amount Dollar Amount Range Distribution $0.01-$50 31% $50.01-$100 16% $100.01-$500 32% $500.01-$1000 9% $1000.01-$2500 6% $2500.01-$5000 2% $5000.01 + 3% Source: 2010 Federal Reserve Check Sample Study Notes: The distributions have up to a 0.5% margin of error and may not add to 100 percent Distribution of the Number of Checks by Counterparty Counterparty Distribution C2B 44.3% C2C 10.1% B2B 27.1% B2C 18.3% Unknown* 0.1% *Unknown includes all counterparty combinations where either the payer, payee, or both the payer and payee are an unknown/indeterminate classification. Distribution of the Value of Checks by Counterparty Counterparty Distribution C2B 13.1% C2C 4.1% B2B 66.4% B2C 16.4% Unknown* 0.0% *Unknown includes all counterparty combinations where either the payer, payee, or both the payer and payee are an unknown/indeterminate classification. Credit Cards The data used to describe credit cards come from the 2007 and the 2010 Federal Reserve Payments Studies and The Nilson Report , a twice-monthly newsletter based in Carpinteria, California. The Federal Reserve Payments Study is a triennial survey of the payments industry first conducted in 2001. These studies are part of a Federal Reserve System effort to track noncash payments in the United States, and they reflect the efforts of hundreds of organizations across the country. Nilson kindly permits some of its data to be included in tabulations that appear in the U.S. Census Bureau’s Statistical Abstract of the U.S. We include data from the 2009 edition here. More recent data should be obtained directly from Nilson. Access at: The 2010 Federal Reserve Payments Study U.S Census Bureau: Banking, Finance, Insurance: Payment Systems, Consumer Credit, Mortgage Debt Credit Card Volume, Value and Average Value 2003 2006 2009 Volume (Bil) Value ($ Tril) Avg Value ($) Volume (Bil) Value ($ Tril) Avg Value ($) Volume (Bil) Value ($ Tril) Avg Value ($) Total 19.0 $1.7 $89 21.7 $2.1 $98 21.6 $1.9 $89 General Purpose 15.2 $1.4 $93 19.0 $1.9 $99 19.9 $1.7 $86 Private Label 3.8 $0.3 $76 2.8 $0.3 $92 1.7 $0.2 $121 Source: 2007 and 2010 Federal Reserve Payments Studies Figures may not add due to rounding. Distribution of General Purpose Credit Card Payments Number (Bil) % of Total Value (Bil) % of Total $5 2.1 10.7% $4 0.3% $5.00-$14.99 3.7 18.5% $36 2.1% $15-$24.99 2.9 14.5% $57 3.3% $25+ 11.2 56.3% $1,624 94.4% Source: 2010 Federal Reserve Payments Studies Credit Cardholders and Number of Cards Type of Card 2000 2009 2012 proj. Cardholders1 (Mil) Cards (Mil) Cardholders1(Mil) Cards (Mil) Cardholders1(Mil) Cards (Mil) Total 159 1,425 156 1,245 160 1,167 Visa 93 255 100 270 107 261 MasterCard 86 200 80 203 84 174 Discover/Amex 59 83 74 103 80 111 Store 114 597 100 470 96 455 Oil Company 76 98 58 61 56 60 Other2 133 192 105 370 81 106 Source: The Nilson Report , Carpinteria, CA, twice-monthly newsletter. (Used with permission.) 1 Cardholders may hold more than one type of card. 2 Includes Universal Air Travel Plan (UATP), phone cards, automobile rental, and miscellaneous cards; credit card purchase volume excludes phone cards. Credit Card Rates The data used to describe credit card interest rates and the rates of return to credit card banks come from the Report to Congress on the Profitability of Credit Card Operations of Depository Institutions provided by the Board of Governors of the Federal Reserve System. This report is transmitted to Congress annually and is based mainly on the Call Report, the Quarterly Report of Credit Card Interest Rates, and the Survey of Terms of Credit Card Plans. The Board released the data in this report in June. Access at: http://www.federalreserve.gov/pubs/reports_other.htm (see "Profitability of Credit Card Operations of Depository Institutions") Interest Rate on Revolving Credit Cards (%) Q1 Q2 Q3 Q4 Avg 2003 12.85% 12.82% 13.11% 12.91% 12.92% 2004 12.41% 12.93% 13.60% 13.92% 13.22% 2005 14.13% 14.81% 14.75% 14.48% 14.54% 2006 14.38% 14.77% 14.67% 15.09% 14.73% 2007 14.64% 14.47% 15.24% 14.35% 14.68% 2008 13.77% 13.51% 13.64% 13.36% 13.57% 2009 13.54% 14.43% 14.90% 14.37% 14.31% 2010 14.67% 14.48% 14.22% 13.67% 14.26% 2011 13.44% 13.06% 13.08% 12.78% 13.09% Source: Board of Governors of the Federal Reserve System, Quarterly Report of Credit Card Interest Rates Return on Assets at Large U.S. Credit Card Banks (%) Year Return 2001 3.24 2002 3.28 2003 3.66 2004 3.55 2005 2.85 2006 3.34 2007 2.75 2008 1.43 2009 -3.01 2010 2.36 2011 5.25 Note: Credit card banks are commercial banks with average managed assets (loans to individuals, including securitizations) greater than or equal to $200 million with a minimum 50 percent of assets in consumer lending and 90 percent of consumer lending in the form of revolving credit. Profitability of credit card banks is measured as net pretax income as a percentage of average quarterly outstanding balances. Source: Report of Condition and Income (Call Report) Debit Cards The data used to describe debit cards come from the 2007 and 2010 Federal Reserve Payments Studies and The Nilson Report , a twice-monthly newsletter based in Carpinteria, California. The Federal Reserve Payments Study is a triennial survey of the payments industry first conducted in 2001. These studies are part of a Federal Reserve System effort to track noncash payments in the United States, and they reflect the efforts of hundreds of organizations across the country. Nilson kindly permits some of its data to be included in tabulations that appear in the U.S. Census Bureau’s Statistical Abstract of the U.S. We include data from the 2009 edition here. More recent data should be obtained directly from Nilson. Access at: The 2010 Federal Reserve Payments Study U.S Census Bureau: Banking, Finance, Insurance: Payment Systems, Consumer Credit, Mortgage Debt Debit Card Volume, Value, and Average Value 2003 2006 2009 Number (Bil) Value ($ Bil) Avg Value ($) Number (Bil) Value ($ Bil) Avg Value ($) Number (Bil) Value ($ Bil) Avg Value ($) Total 15.6 $600 $40 25.0 $1,000 $39 37.9 $1,400 $38 Signature 10.3 $400 $42 15.7 $600 $40 23.4 $900 $37 PIN 5.3 $200 $38 9.4 $300 $37 14.5 $600 $39 Source: 2007 and 2010 Federal Reserve Payments Studies Figures may not add due to rounding. Distribution of General Purpose Signature Debit Card Payments Number (Bil) % of Total Value (Bil) % of Total $5 3.6 15.4% $10 1.1% $5.00-$14.99 7.3 31.3% $70 7.9% $15-$24.99 4.0 17.3% $80 9.1% $25+ 8.4 36.0% $700 81.9% Source: 2010 Federal Reserve Payments Studies Distribution of General Purpose PIN Debit Card Payments Number (Bil) % of Total Value (Bil) % of Total $5 1.3 8.7% $4 0.7% $5.00-$14.99 3.5 24.1% $34 5.6% $15-$24.99 2.6 17.7% $51 8.4% $25+ 7.2 49.5% $512 85.3% Source: 2010 Federal Reserve Payments Studies Debit Card Holders and Number of Cards Type of Card 2000 2008 2012 proj. Holders1 (Mil) Cards (Mil) Holders1(Mil) Cards (Mil) Holders1 (Mil) Cards (Mil) Total 160 235 181 491 191 530 Signature2 137 137 160 449 165 484 PIN3 159 223 180 276 189 291 Other4 11 11 12 12 14 14 Source: The Nilson Report , a twice-monthly newsletter based in Carpinteria, CA. (Used with permission.) 1 Cardholders may hold more than one type of card. Bank cards and EFT cards are the same pieces of plastic that carry multiple brands. The total card figure shown does not include any duplication. 2 “Signature Debit” is defined by Nilson as bank cards or Visa and MasterCard debit cards. For 2006 and later, Nilson includes Interlink Master Card PIN debit. 3 “PIN Debit” is defined by Nilson as EFT cards issued by financial institution members of regional and national switches such as Star, Interlink, Pulse, Nyce, etc. 4 Retail cards such as those issued by supermarkets Prepaid The data used to describe prepaid cards come from the 2007 and 2010 Federal Reserve Payments Studies. The Federal Reserve Payments Study is a triennial survey of the payments industry first conducted in 2001. These studies are part of a Federal Reserve System effort to track noncash payments in the United States, and they reflect the efforts of hundreds of organizations across the country. Access at: http://www.frbservices.org/files/communications/pdf/research/2010_payments_study.pdf Prepaid Card Volume, Value, and Average Value 2006 2009 Number (Bil) Value ($ Bil) Avg Value ($) Number (Bil) Value ($ Bil) Avg Value ($) Total 3.3 $80 $23 6.0 $140 $24 Private Label 1.9 $30 $18 2.7 $40 $17 General Purpose 0.3 $10 $41 1.3 $40 $33 EBT 1.1 $30 $27 2.0 $50 $28 Source: 2010 Federal Reserve Payments Studies Figures may not add due to rounding. Distribution of Open Loop Prepaid Card Payments Number (Bil) % of Total Value (Bil) % of Total $5 0.2 18.8% $1 1.6% $5.00-$14.99 0.4 32.4% $4 8.9% $15-$24.99 0.2 15.9% $4 9.3% $25+ 0.4 32.9% $34 80.2% Source: 2010 Federal Reserve Payments Studies. ACH The data used to describe automated clearing house (ACH) payments come from quarterly statistical reports published publicly by NACHA, the Electronic Payments Association. NACHA is a non-for-profit that oversees the ACH network. In NACHA’s quarterly reports, it publishes the breakdown of ACH transactions from the previous quarter and tracks growth. Access at: http://www.nacha.org/c/ACHntwkstats.cfm ACH Transactions and Dollar Value (not including “on-us” transactions) (Mil) 2005 2006 2007 2008 2009 2010 2011 CIE1 121 138 133 127 119 138 156 PPD Debits2 2,332 2,498 2,611 2,741 2,770 2,833 2,933 PPD Credits3 3,557 3,771 4,021 4,333 4,545 4,710 4,879 RCK4 22 21 20 16 12 8 7 TEL5 239 292 335 347 344 354 367 WEB6 1,006 1,364 1,737 2,078 2,280 2,449 2,680 Total ACH Transactions (Mil)7 10,696 12,323 13,972 14,961 15,257 15,617 16,079 Total ACH Value ($ Tril) $24.00 $26.15 $28.54 $26.90 $29.59 $31.70 $33.90 Source: NACHA, the Electronic Payments Association 1 CIE = Customer Initiated Entry: A credit entry is initiated by an individual and is used to pay some sort of obligation 2 PPD Debits = Prearranged Payments and Deposit Debit Application: A transfer of funds into a consumer account at the Receiving Depository Financial Institution 3 PPD Credit = Prearranged Payments and Deposit Credit Application: Authority is granted by the consumer to companies with billing operations to initiate one time or periodic charges to his or her account as bills become due 4 RCK = Re-presented Check: An ACH debit application used by originators to re-present a check that has been processed through the check collections system and returned because of insufficient or uncollected funds 5 TEL = Telephone Authorized Entry: Oral authorization is obtained solely via the telephone 6 WEB = Internet Authorized Entry: Authorization is obtained solely via the Internet 7 The total ACH transactions and value include all commercial inter-bank and government transactions, but not "on-us" transactions, and are larger than the total of the entry types included. *According to the 2010 Federal Reserve Payments Study, “on-us” ACH transactions increased from 2.3 billion in 2006 to 3.7 billion in 2009. Adoption of Payments by Households The data used to describe the adoption of payments by households come from tables in an article by Loretta Mester published in the Federal Reserve Bank of Philadelphia’s Business Review . These tables are based on the Survey of Consumer Finances (SCF) as well as the author's calculations. The SCF is a triennial survey of the balance sheet, pension, income, and other demographic characteristics of U.S. families. The survey also gathers information on the use of financial institutions. Access at: Changes in the Use of Electronic Means of Payment: 1995-2010 (exhibit 1, parts 1 and 2) Survey of Consumer Finances Adoption of Payments by Households (%) 1995 1998 2001 2004 2007 2010 ATM 62.5 67.4 69.8 74.4 79.7 83.4 Debit Card 17.6 33.8 47.0 59.3 67.0 78.4 Direct Deposit 46.7 60.5 67.3 71.2 74.9 75.9 Automatic Bill Paying 21.8 36.0 40.3 47.4 45.5 48.3 Note: The percentages reported are based on the population-weighted figures using the revised Kennickell-Woodburn consistent weights for each year. (For further discussion, see the Survey of Consumer Finances codebooks at www.federalreserve.gov/pubs/oss/oss2/scfindex.html .) This exhibit reports percentages for all households. 1 The questions on ATMs and smart cards asked whether any member of the household had an ATM card or a smart card, not whether the member used it. The other questions asked about usage. The question on smart cards was dropped after the 2001 survey. Survey of Consumer Payment Choice As described on its website, the Federal Reserve Bank of Boston publishes the Survey of Consumer Payment Choice (SCPC), which develops comprehensive, publicly available data on consumer payment behavior. The 2008 SCPC is a nationally representative survey of consumer payment behavior developed by the Consumer Payments Research Center of the Boston Fed and implemented by the RAND Corporation with its American Life Panel. The primary purpose of the 2008 SCPC is to publish and document the aggregate statistics obtained from the data to help researchers learn how consumers choose among payment instruments, including cash. The 2008 SCPC report contains detailed tables providing a view of consumers' behavior regarding paper instruments, payment cards, as well as electronic instruments. The data are based on the half-hour, Internet-based survey administered by the RAND Corporation to a sample of U.S. consumers drawn from its American Life Panel. Access at: http://www.bostonfed.org/economic/ppdp/2011/ppdp1101.htm initTabs('StatsTabs',Array('Consumer Credit Snapshot','Consumer Payments Snapshot'),0,790,'',Array(false,false)); initTabs('CCSTabs',Array('Consumer Debt','Holders of Consumer Debt','Credit Performance','Credit Standards Demand','Credit at Family Level','Maps'),0,770,'',Array(false,false,false,false,false,false)); initTabs('CPSTabs',Array('Noncash Payments','Checks','Credit Cards','Debit Cards','Prepaid','ACH','Adoption of Payments','SCPC'),0,770,'',Array(false,false,false,false,false,false,false,false));
个人分类: 美国经济|8 次阅读|0 个评论
分享 JPMorgan's Eligible Gold Plummets 65% In 24 Hours To All Time Low
insight 2013-4-26 10:37
JPMorgan's Eligible Gold Plummets 65% In 24 Hours To All Time Low Submitted by Tyler Durden on 04/25/2013 17:30 -0400 We are confident that in the aftermath of our article from last night " Just What Is Going On With The Gold In JPMorgan's Vault ?" in which we showed the absolute devastation of "eligible" (aka commercial) gold warehoused in JPM's vault just over the Manhattan bedrock at 1 Chase Manhattan Place (and also in the entire Comex vault network in the past month), we were not the only ones checking every five minutes for the Comex gold depository update for April 25 . Moments ago we finally got it, and it's a doozy. Because in just the past 24 hours, from April 24 to April 25, according to the Comex, JPM's eligible gold plunged from 402.4K ounces to just 141.6K ounces, a drop of 65% in 24 hours,and the lowest amount of eligible gold held at the vault on record, since its reopening in October 2010 ! Everyone has seen what a run on the bank looks like. Below is perhaps the best chart of what a " run on the vault " is. The absolute collapse in JPM's eligible gold inventory, means total Comex eligible gold has fallen to just 5.8 million ounces, half of what it was in early 2011, and back to levels last seen in March 2009. So, once again, just like last night, we ask the same questions which are even more critical today than they were 24 hours ago: What happened to the commercial gold vaulted with JPM, and what was the reason for the historic drawdown? Gold, unlike fiat, is not created out of thin air, nor can it be shred or deleted. Where did the gold leaving the JPM warehouse end up (especially since registered JPM and total Comex gold has been relatively flat over the same period)? Did any of this gold make its way across the street, and end up at the vault of the building located at 33 Liberty street? What happens if and/or when the JPM vault is empty of commercial gold, and JPM receives a delivery notice? Incidentally, JPM now has just under a paltry 5 tons of eligible gold left in storage. We hope this is also the maximum exposure it faces for imminent delivery requests, because if tomorrow it receives withdrawal requests for 141,581.5 ounces +1 , then things get really interesting. Average: 4.929825 Your rating: None Average: 4.9 ( 57 votes)
个人分类: gold|11 次阅读|0 个评论

京ICP备16021002-2号 京B2-20170662号 京公网安备 11010802022788号 论坛法律顾问:王进律师 知识产权保护声明   免责及隐私声明

GMT+8, 2024-4-25 20:36