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 Series Title: Other loans and leases: All other loans and leases: Other loans not elsewhere classified, large domestically chartered commercial banks, seasonally adjusted; Millions of Dollars; Weekly: Percentage change from 52 weeks ago
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Yearly Chart  |  Excel file  |  Self-updating Excel file
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 2016 01 06 6411·065453053187800
 2016 01 13 5711.781476102040200
 2016 01 20 2410·301543660468800
 2016 01 27 3711·407643851995700
 2016 02 03 929·946986558549910
 2016 02 10 8511·237821394548300
 2016 02 17 189.682418335280520
 2016 02 24 199.064942085379670
 2016 03 02 9810·840658418816300
 2016 03 09 2510.744303531176600
 2016 03 16 2510.032086344095800
 2016 03 23 119.379355898740880
 2016 03 30 349.055245690462190
 2016 04 06 579·170989172318070
 2016 04 13 589.282270339131850
 2016 04 20 5910.194984921214700
 2016 04 27 759·068836656801540
 2016 05 04 8810.321855241544600
 2016 05 11 568.699996499940780
 2016 05 18 328·305605770510870
 2016 05 25 208·957408071202640
 2016 06 01 509·047843349008010
 2016 06 08 818.786874795547760
 2016 06 15 238·574043402922290
 2016 06 22 967·442347434578940
 2016 06 29 07.184741012331260
 2016 07 06 208·259565979394770
 2016 07 13 527·308817665856980
 2016 07 20 537·439724367604010
 2016 07 27 197·504103533778680
 2016 08 03 887.567682264390970
 2016 08 10 637.853749482378070
 2016 08 17 656·720941549170470
 2016 08 24 145.818348504678970
 2016 08 31 216.301050530276790
 2016 09 07 245·755109755589770
 2016 09 14 356.953903691913750
 2016 09 21 166.074423671710320
 2016 09 28 836·027051710783060
 2016 10 05 318.160651031265180
 2016 10 12 865.935198437555210
 2016 10 19 825.491893519997170
 2016 10 26 615.435756967509290
 2016 11 02 25·852040422025520
 2016 11 09 705.450574433120360
 2016 11 16 946.448594371754200
 2016 11 23 695.390884224317330
 2016 11 30 824·908844326429770
 2016 12 07 614.116329664849560
 2016 12 14 594.396208282886940
 2016 12 21 444·076011041978880
 2016 12 28 393.640469482109300
 2017 01 04  613·211442796133060
 2017 01 11  72·444499869705940
 2017 01 18  502·707161211808500
 2017 01 25  682·305702592577210
 2017 02 01  944·323578922071910
 2017 02 08  962·308073124200050
 2017 02 15  733·212296530053550
 2017 02 22  874·195649850979130
 2017 03 01  112.572071822768460
 2017 03 08  72.840287346386590
 2017 03 15  282·641128326126800
 2017 03 22  423.630246996189390
 2017 03 29  883·514521218063730
 2017 04 05  483.005859496484130
 2017 04 12  512.427458709767790
 2017 04 19  11.879408880471160
 2017 04 26  242·390761249233140
 2017 05 03  481.679546688781410
 2017 05 10  62.148638831511000
 2017 05 17  582.752618026819540
 2017 05 24  452·931976224974540
 2017 05 31  661.995211316623610
 2017 06 07  812·123810522475720
 2017 06 14  322.122586742865720
 2017 06 21  13.423529912136750
 2017 06 28  832·812115364833660
 2017 07 05  883.634840056247830
 2017 07 12  682·914390602962460
 2017 07 19  693·316645724459950
 2017 07 26  63·794708464326700
 2017 08 02  664.185870315907360
 2017 08 09  353·537102291465130
 2017 08 16  484.225164619818770
 2017 08 23  654.189120685604890
 2017 08 30  773.710192194868990
 2017 09 06  274.732546835409450
 2017 09 13  633·432656209507410
 2017 09 20  193·681308488158310
 2017 09 27  93·582202914521340
 2017 10 04  621·496738339191480
 2017 10 11  662.689057901270740
 2017 10 18  473·146952826049470
 2017 10 25  763·624243369789500
 2017 11 01  863.164595261471500
 2017 11 08  303·268078196098250
 2017 11 15  582.046198313546550
 2017 11 22  142.730092873092030
 2017 11 29  672.553064057728700
 2017 12 06  583.445673671576110
 2017 12 13  833.212128407442690
 2017 12 20  883·261248623506050
 2017 12 27  995·026444762279310
 2018 01 03 743.691294020502190
 2018 01 10 783·445099809702400
 2018 01 17 844.117225321702180
 2018 01 24 24·756229134390640
 2018 01 31 293·901910295562310
 2018 02 07 254·531217318381180
 2018 02 14 164.539090679243380
 2018 02 21 193.758007963082940
 2018 02 28 974·263146523843080
 2018 03 07 303·050329421249210
 2018 03 14 213.884069451727350
 2018 03 21 213.063833005759230
 2018 03 28 803.770743749107660
 2018 04 04 262·908577844881630
 2018 04 11 632·950497381039560
 2018 04 18 02.854647003081890
 2018 04 25 33.814043051875160
 2018 05 02 682·748811134704690
 2018 05 09 293.159904233680530
 2018 05 16 763·827550602544920
 2018 05 23 162·990320679282510
 2018 05 30 403.590817307173170
 2018 06 06 323·851744123339350
 2018 06 13 943·657578936059400
 2018 06 20 943.295939287651150
 2018 06 27 463·472818793104060
 2018 07 04 112·176228303320630
 2018 07 11 222·500857074291200
 2018 07 18 381·890737917765710
 2018 07 25 191·314121466971830
 2018 08 01 271.481615440962170
 2018 08 08 550.817860765923717
 2018 08 15 740.937663764954988
 2018 08 22 160·103178814458671
 2018 08 29 700.205395645246953
 2018 09 05 11-0·110352244364009
 2018 09 12 51-0·558451740691324
 2018 09 19 18-0·384347113871020
 2018 09 26 51-0·264694295043222
 2018 10 03 35-0·307061146612153
 2018 10 10 46-0.694646663853760
 2018 10 17 31-1.584599144688490
 2018 10 24 9-1·363211331484060


 2018 10 31 96-1.010768424155490
 2018 11 07 58-2.477510198894040
 2018 11 14 88-2·186754387383600
 2018 11 21 7-1.915302378047480
 2018 11 28 88-1.758612413232840
 2018 12 05 13-0·028543784585644
 2018 12 12 45-1.382027092890360
 2018 12 19 32-1·033954994088850
 2018 12 26 301.103948986831100
 2019 01 02  61-0·114767356173817
 2019 01 09  84-1.545850176473370
 2019 01 16  97-2.409142990219880
 2019 01 23  67-2.225818158744140
 2019 01 30  78-3·053057587749440
 2019 02 06  11-3·284515862750740
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 Series Title: Other loans and leases: All other loans and leases: Other loans not elsewhere classified, large domestically chartered commercial banks, seasonally adjusted; Millions of Dollars; Weekly: Percentage change from 52 weeks ago
   For this series:   Numerical Data  |  GIF Chart
   Transform this series  |  Display series in COPY/PASTE format

New data set: Quarterly Financial Reporting: Manufacturing, Mining, Trade, and Selected Service Industries

Sites of Interest: Conerly Consulting: Economics for Business Decisions *

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