Functions

get_failures

Details

• Description: Detail on failed financial institutions
• Return: dict or pandas.DataFrame
• Arguments

Argument	Description	Type	Default	Required	Options
filters	Filter(s) for the bank search	str	None	optional	See filtering
fields	Comma delimited list of fields to retrieve	str	All fields included by default	optional
sort_by	Field name by which to sort returned data	str	FAILDATE	optional	See meta_dict
sort_order	Indicator if ascending or descending	str	DESC	optional	ASC DESC
limit	Number of records to return	int	10000	optional	0 to 10,000
offset	Offset of page to return	int	0	optional
output	Format of data to return	str	json	optional	json pandas
limit	Number of records to return	int	10000	optional	0 to 10,000
friendly_fields	Replace keys / column names with friendlier title	bool	False	optional	True False

Example

import bankfind as bf

data = bf.get_failures()
data['data'][0]

Data

{
    'data': {
        'QBFDEP': 139526,
        'PSTALP': 'WV',
        'FIN': '10536',
        'FAILDATE': '04/03/2020',
        'RESTYPE': 'FAILURE',
        'CITYST': 'BARBOURSVILLE, WV',
        'SAVR': 'DIF',
        'RESTYPE1': 'PA',
        'CHCLASS1': 'NM',
        'NAME': 'THE FIRST STATE BANK',
        'COST': None,
        'QBFASSET': 152400,
        'CERT': 14361,
        'FAILYR': '2020',
        'ID': '4102'
    },
    'score': 1
}

get_history

Details

• Description: Detail on structure change events
• Return: dict or pandas.DataFrame
• Arguments

Argument	Description	Type	Default	Required	Options
filters	Filter(s) for the bank search	str	None	optional	See filtering
search	Flexible text search against institution records (fuzzy name matching)	str	None	optional	See search
fields	Comma delimited list of fields to retrieve	str	All fields included by default	optional
sort_by	Field name by which to sort returned data	str	FAILDATE	optional	See meta_dict
sort_order	Indicator if ascending or descending	str	DESC	optional	ASC DESC
limit	Number of records to return	int	10000	optional	0 to 10,000
offset	Offset of page to return	int	0	optional
output	Format of data to return	str	json	optional	json pandas
limit	Number of records to return	int	10000	optional	0 to 10,000
friendly_fields	Replace keys / column names with friendlier title	bool	False	optional	True False

Example

import bankfind as bf

data = bf.get_history()
data['data'][0]

Data

{
    'data': {
        'REPORT_TYPE': 711,
        'INSAGENT1': 'DIF',
        'INSAGENT2': '',
        'OFF_PCITY': 'Colorado Springs',
        'EFFDATE': '2020-07-27T00:00:00',
        'CHARTAGENT': 'STATE',
        'PSTALP': 'NE',
        'CLASS': 'NM',
        'FRM_OFF_SERVTYPE': 0,
        'OFF_LONGITUDE': -104.87635200138965,
        'OFF_PSTATE': 'COLORADO',
        'BANK_INSURED': 'Y',
        'CNTYNUM': 157,
        'INSTNAME': 'First State Bank',
        'OFF_PADDR': '3216 W Colorado AVE',
        'FRM_CLCODE': 0,
        'OFF_SERVTYPE_DESC': 'FULL SERVICE - BRICK AND MORTAR',
        'TRANSNUM': 202012234,
        'MZIPREST': '0000',
        'FDICREGION_DESC': 'KANSAS CITY',
        'FRM_OFF_CLCODE': 0,
        'PZIP5': '69361',
        'OFF_PZIPREST': '1906',
        'OFF_NAME': 'First State Bank Colorado Springs West Branch',
        'CERT': 15586,
        'OFF_PSTALP': 'CO',
        'PCITY': 'SCOTTSBLUFF',
        'LATITUDE': 0,
        'PROCDATE': '2020-08-05T00:00:00',
        'ACQDATE': '9999-12-31T00:00:00',
        'CHANGECODE': 711,
        'PADDR': '2002 BROADWAY',
        'MZIP5': '69361',
        'FI_UNINUM': 9873,
        'LONGITUDE': 0,
        'FRM_LATITUDE': 0,
        'STATE': 'NEBRASKA',
        'MSTALP': 'NE',
        'CNTYNAME': 'SCOTTS BLUFF',
        'ACQ_UNINUM': 0,
        'OFF_CNTYNUM': 41,
        'FI_EFFDATE': '2019-06-10T00:00:00',
        'FDICREGION': 11,
        'MSTATE': 'NEBRASKA',
        'FRM_LONGITUDE': 0,
        'OFF_CNTYNAME': 'EL PASO',
        'CHANGECODE_DESC': 'BRANCH OPENING',
        'MCITY': 'SCOTTSBLUFF',
        'MADDR': 'P.O. BOX  1267',
        'OFF_PZIP5': '80904',
        'OUT_UNINUM': 0,
        'PZIPREST': '0000',
        'ORG_STAT_FLG': 'Y',
        'FRM_OFF_LONGITUDE': 0,
        'ENDDATE': '9999-12-31T00:00:00',
        'UNINUM': 625952,
        'OFF_NUM': 6,
        'CLCODE': 21,
        'OFF_SERVTYPE': 11,
        'FRM_OFF_CNTYNUM': 0,
        'ORG_ROLE_CDE': 'BR',
        'REGAGENT': 'FDIC',
        'OFF_LATITUDE': 38.85583298227556,
        'ESTDATE': '2020-07-27T00:00:00',
        'FRM_OFF_LATITUDE': 0,
        'TRUST': 'Full',
        'ID': '20eb98a36c7c77cf6bc019ce391ba7c9'
    },
    'score': 1
}

get_institutions

Details

• Description: List of financial institutions
• Return: dict or pandas.DataFrame
• Arguments

Argument	Description	Type	Default	Required	Options
filters	Filter(s) for the bank search	str	None	optional	See filtering
search	Flexible text search against institution records (fuzzy name matching)	str	None	optional	See [search](#filtering.md#search
fields	Comma delimited list of fields to retrieve	str	All fields included by default	optional
sort_by	Field name by which to sort returned data	str	FAILDATE	optional	See meta_dict
sort_order	Indicator if ascending or descending	str	DESC	optional	ASC DESC
limit	Number of records to return	int	10000	optional	0 to 10,000
offset	Offset of page to return	int	0	optional
output	Format of data to return	str	json	optional	json pandas
limit	Number of records to return	int	10000	optional	0 to 10,000
friendly_fields	Replace keys / column names with friendlier title	bool	False	optional	True False

Example

import bankfind as bf

data = bf.get_institutions()
data['data'][0]

Data

{
    'data': {
        'ZIP': '31087',
        'SASSER': 0,
        'CHRTAGNT': 'STATE',
        'CONSERVE': 'N',
        'REGAGENT2': '',
        'STNAME': 'Georgia',
        'ROAQ': 0.65,
        'INSDATE': '01/01/1934',
        'TE06N528': '',
        'TE06N529': '',
        'OFFOA': 0,
        'FDICDBS': '05',
        'NAMEHCR': '',
        'OCCDIST': '5',
        'CMSA': '',
        'DEPDOM': 59267,
        'CBSA_METRO_FLG': '0',
        'TE10N528': '',
        'NETINC': 124,
        'CBSA_DIV_NO': '',
        'MUTUAL': '0',
        'MSA_NO': '0',
        'OFFFOR': 0,
        'INSSAVE': 0,
        'CHARTER': '0',
        'RSSDHCR': '',
        'TE04N528': '',
        'TE04N529': '',
        'CERT': '10057',
        'STALP': 'GA',
        'SPECGRP': 7,
        'CFPBENDDTE': '31-Dec-9999',
        'TE09N528': '',
        'IBA': 0,
        'INSBIF': 0,
        'INSFDIC': 1,
        'ENDEFYMD': '12/31/9999',
        'MSA': '',
        'TE02N528': '',
        'CB': '1',
        'TE02N529': '',
        'TE07N528': '',
        'FDICSUPV': 'Atlanta',
        'FED': '6',
        'REGAGNT': 'FDIC',
        'NEWCERT': 0,
        'ASSET': 76416,
        'CBSA_MICRO_FLG': '1',
        'OFFICES': 1,
        'STCNTY': '13141',
        'CSA_FLG': '0',
        'CITY': 'Sparta',
        'CLCODE': '21',
        'INACTIVE': 0,
        'CMSA_NO': '0',
        'STALPHCR': '',
        'INSAGNT1': 'DIF',
        'BKCLASS': 'NM',
        'EFFDATE': '08/31/2009',
        'SUPRV_FD': '05',
        'DATEUPDT': '09/02/2009',
        'INSAGNT2': '',
        'TE05N528': '',
        'TE05N529': '',
        'ROEQ': 2.96,
        'FDICREGN': 'Atlanta',
        'FLDOFF': 'Savannah',
        'WEBADDR': 'http://www.bankofhancock.com',
        'QBPRCOML': '2',
        'COUNTY': 'Hancock',
        'DOCKET': '0',
        'ULTCERT': '10057',
        'OTSDIST': '2',
        'LAW_SASSER_FLG': 'N',
        'PARCERT': '0',
        'ROA': 0.65,
        'CFPBFLAG': 0,
        'RISDATE': '12/31/2019',
        'ROE': 2.96,
        'INSCOML': 1,
        'OTSREGNM': 'Southeast',
        'EQ': '17026',
        'RUNDATE': '08/08/2020',
        'TE03N528': '',
        'TE03N529': '',
        'NAME': 'Bank of Hancock County',
        'HCTMULT': '',
        'CBSA_DIV': '',
        'ADDRESS': '12855 Broad Street',
        'OFFDOM': 1,
        'SUBCHAPS': '0',
        'PROCDATE': '09/02/2009',
        'INSSAIF': 0,
        'DENOVO': '0',
        'CBSA_NO': '33300',
        'ACTIVE': 1,
        'CFPBEFFDTE': '31-Dec-9999',
        'STCHRTR': 1,
        'REPDTE': '03/31/2020',
        'FORM31': '0',
        'CSA': '',
        'INSDIF': 1,
        'TE01N529': '',
        'ROAPTX': 0.65,
        'STNUM': '13',
        'OAKAR': 0,
        'SPECGRPN': 'Other Specialized Under 1 Billion',
        'ROAPTXQ': 0.65,
        'FED_RSSD': '37',
        'CSA_NO': '',
        'CBSA_METRO': 0,
        'INSTCRCD': 0,
        'DEP': 59267,
        'UNINUM': '6429',
        'INSTAG': '0',
        'TE01N528': '',
        'CITYHCR': '',
        'TRACT': '0',
        'CBSA': 'Milledgeville, GA',
        'CBSA_DIV_FLG': '0',
        'TE08N528': '',
        'NETINCQ': 124,
        'CHANGEC1': 520,
        'CERTCONS': '0',
        'ESTYMD': '09/01/1904',
        'FEDCHRTR': 0,
        'TRUST': '0',
        'ID': '10057'
    },
    'score': 1
}

get_locations

Details

• Description: Detail on failed financial institutions
• Return: dict or pandas.DataFrame
• Arguments

Argument	Description	Type	Default	Required	Options
filters	Filter(s) for the bank search	str	None	optional	See filtering
fields	Comma delimited list of fields to retrieve	str	All fields included by default	optional
sort_by	Field name by which to sort returned data	str	FAILDATE	optional	See meta_dict
sort_order	Indicator if ascending or descending	str	DESC	optional	ASC DESC
limit	Number of records to return	int	10000	optional	0 to 10,000
offset	Offset of page to return	int	0	optional
output	Format of data to return	str	json	optional	json pandas
limit	Number of records to return	int	10000	optional	0 to 10,000
friendly_fields	Replace keys / column names with friendlier title	bool	False	optional	True False

Example

import bankfind as bf

data = bf.get_locations()
data['data'][0]

Data

{
    'data': {
        'ZIP': '21613',
        'CBSA_NO': '15700',
        'BKCLASS': 'SM',
        'FI_UNINUM': 3221,
        'STNAME': 'Maryland',
        'CSA': 'Salisbury-Cambridge, MD-DE',
        'COUNTY': 'Dorchester',
        'MAINOFF': 0,
        'OFFNAME': 'WOODS ROAD BRANCH',
        'CBSA_METRO_FLG': '0',
        'CBSA_MICRO_FLG': '1',
        'CSA_NO': '480',
        'CBSA_METRO': 0,
        'CBSA_DIV_NO': '',
        'RUNDATE': '08/07/2020',
        'NAME': '1880 Bank',
        'UNINUM': 204568,
        'SERVTYPE': 11,
        'CSA_FLG': '1',
        'STCNTY': '24019',
        'CBSA': 'Cambridge, MD',
        'CBSA_DIV': '',
        'CBSA_DIV_FLG': '0',
        'CITY': 'Cambridge',
        'ADDRESS': '803 Woods Road',
        'CERT': '4829',
        'STALP': 'MD',
        'OFFNUM': 1,
        'ESTYMD': '12/23/1968',
        'ID': '204568'
    },
    'score': 1
}

get_summary

Details

• Description: Detail on failed financial institutions
• Return: dict or pandas.DataFrame
• Arguments

Argument	Description	Type	Default	Required	Options
filters	Filter(s) for the bank search	str	None	optional	See filtering
fields	Comma delimited list of fields to retrieve	str	All fields included by default	optional
sort_by	Field name by which to sort returned data	str	FAILDATE	optional	See meta_dict
sort_order	Indicator if ascending or descending	str	DESC	optional	ASC DESC
limit	Number of records to return	int	10000	optional	0 to 10,000
offset	Offset of page to return	int	0	optional
output	Format of data to return	str	json	optional	json pandas
limit	Number of records to return	int	10000	optional	0 to 10,000
friendly_fields	Replace keys / column names with friendlier title	bool	False	optional	True False

Example

import bankfind as bf

data = bf.get_failures()
data['data'][0]

Data

{
    'data': {
        'INTINC2': 51722726,
        'EXTRA': 1316,
        'LNATRES': 9769341,
        'chrtrest': 0,
        'STNAME': 'United States and Other Areas',
        'ILNS': 39718788,
        'LNAG': 3306388,
        'EINTEXP2': 10348941,
        'EPREMAGG': 2063405,
        'YEAR': '2019',
        'BKPREM': 8315925,
        'INTAN': 12025281,
        'LNRE': 444072342,
        'chartoth': 1,
        'IGLSEC': 482482,
        'OT_BIF': 0,
        'EAMINTAN': 456598,
        'newcount': 0,
        'DEPI': 840535976,
        'EFHLBADV': None,
        'tofail': 1,
        'SCMTGBK': 292023664,
        'NTRTMLG': 118177154,
        'OEA': 1483578,
        'EFREPP': 90846,
        'LNLSGR': 655127513,
        'NETINC': 15194171,
        'TOT_OTS': 334,
        'CONS': 0,
        'OTHNBORR': 91479748,
        'LNREMULT': 68529412,
        'P9LNLS': 7463014,
        'COUNT': 659,
        'LNRERES': 253541537,
        'EQCS': 790384,
        'SCAGE': 304050945,
        'LNRECONS': 23453492,
        'TOT_FDIC': 325,
        'EINTEXP': 10348941,
        'TPD': 13656751,
        'LNCI': 43378018,
        'EQNM': 125002942,
        'INTBLIB': 1007906756,
        'liqasstd': 0,
        'SC': 385021771,
        'INTBAST': 1096557030,
        'EDEPDOM': 8287049,
        'ILNDOM': 39718603,
        'NCLNLS': 11414221,
        'UNINC': 133264,
        'ISC': 10339424,
        'LIABEQ': 1153906385,
        'tochrt': 7,
        'IFEE': 865589,
        'TOT_SAVE': 659,
        'LNRESRE': None,
        'alsonew': 0,
        'NUMEMP': 121746,
        'ASSET': 1153906405,
        'TINTINC': 11723463,
        'NALNLS': 3951207,
        'EOTHNINT': 14513593,
        'TRADES': 0,
        'ESAL': 12889946,
        'ILNLS': 39999263,
        'LIAB': 1028873691,
        'LNDEP': 417597,
        'OTHBFHLB': 75972627,
        'ITAX': 4361954,
        'EQCDIVP': 12402,
        'SCRES': None,
        'TRADE': 356945,
        'MISSADJ': -1,
        'FD_BIF': 0,
        'CRLNLS': 1422110,
        'LS': 5575099,
        'tomerg': 11,
        'ELNATR': 5247975,
        'LNCRCD': 99551689,
        'INTINC': 51722726,
        'EQUPTOT': 70024149,
        'CHBALI': 64693509,
        'EQPP': 282890,
        'PTXNOINC': 19078526,
        'OINTINC': 11723463,
        'tortc': 0,
        'ILS': 280475,
        'FD_SAIF': 0,
        'EQNWCERT': None,
        'OINTBOR': 85304294,
        'SCUST': 12170713,
        'combos': 12,
        'P3LNLS': 6193737,
        'OTLNCNTA': None,
        'OTHLIAB': 16342193,
        'IFREPO': 18439,
        'LNLSNET': 645358172,
        'LNCONOT1': None,
        'EQCDIVC': 13089203,
        'SCUSA': 316221658,
        'DRLNLS': 7211296,
        'OTHBORR': 1685904,
        'EQCDIV': 13101605,
        'EDEP': 8287065,
        'BRWDMONY': 1685904,
        'comboass': 0,
        'FREPO': 1126633,
        'CHBAL': 73009001,
        'ALLOTHER': 14950385,
        'FREPP': 6067807,
        'IRAKEOGH': 123424709,
        'OT_SAIF': 0,
        'ORE': 302690,
        'SCMUNI': 10308292,
        'ESUBND': 278,
        'SCUS': 316221658,
        'ITRADE': 0,
        'OINTEXP': 1777028,
        'liqunass': 1,
        'DDT': 58550380,
        'EDEPFOR': 16,
        'LNALLOTH': 42378773,
        'SCEQ': 258574,
        'ITAXR': 19078526,
        'ILNFOR': 185,
        'ICHBAL': 1365600,
        'LNRELOC': 21179492,
        'STNUM': '0',
        'SUBLLPF': 26052,
        'OONONII': 11554071,
        'CORPBNDS': 55721897,
        'NONIX': 29466944,
        'NCHGREC': 5789186,
        'OTHASST': 28389467,
        'DEP': 921025698,
        'NIM': 41373785,
        'LNCON': 141930462,
        'EQSUR': 53905519,
        'SAVINGS': 659,
        'ORET': 302690,
        'CB_SI': 'SI',
        'TOINTEXP': 2061876,
        'LNMUNI': 1630491,
        'LNRENRES': 98547901,
        'NONII': 12419660,
        'BRO': 104643398,
        'ID': 'SI_2019_0'
    },
    'score': 1
}