CN112446578A - Risk monitoring method and device - Google Patents

Risk monitoring method and device Download PDF

Info

Publication number
CN112446578A
CN112446578A CN201910832188.9A CN201910832188A CN112446578A CN 112446578 A CN112446578 A CN 112446578A CN 201910832188 A CN201910832188 A CN 201910832188A CN 112446578 A CN112446578 A CN 112446578A
Authority
CN
China
Prior art keywords
monitored object
interest rate
cash flow
coefficient
risk
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201910832188.9A
Other languages
Chinese (zh)
Inventor
张直
高磊
王元芳
黄晶
庞博
周逸文
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
JD Digital Technology Holdings Co Ltd
Original Assignee
JD Digital Technology Holdings Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by JD Digital Technology Holdings Co Ltd filed Critical JD Digital Technology Holdings Co Ltd
Priority to CN201910832188.9A priority Critical patent/CN112446578A/en
Publication of CN112446578A publication Critical patent/CN112446578A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0635—Risk analysis of enterprise or organisation activities
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/02—Banking, e.g. interest calculation or account maintenance

Abstract

The disclosure provides a risk monitoring method and a risk monitoring device, and relates to the field of data processing. The interest rate corresponding to the time parameter is determined according to the interest rate distribution information; calculating a long term coefficient according to the interest rate corresponding to the time parameter; weighting the cash flow of the monitored object in each time period by using a long-term coefficient to obtain the cash flow value of the monitored object in each time period; calculating the duration of the monitored object according to the cash flow current value of the monitored object in each time period; and monitoring the interest rate risk of the monitored object according to the long term of the monitored object. By refining the duration coefficient, each monitored object can reuse the duration coefficient to calculate the duration, and the calculation efficiency of the duration is improved.

Description

Risk monitoring method and device
Technical Field
The present disclosure relates to the field of data processing, and in particular, to a risk monitoring method and apparatus.
Background
The interest rate risk is one of main market risks faced by various large financial institutions, and after interest rate control is cancelled, gaps caused by the change of interest rates of assets and liabilities of financial institutions and the change of economic values of the gaps face more uncertainty, so that the interest rate change can be well predicted, the long-term accurate interest rate risk management of the assets and the liabilities can be more meaningful, and the economic value is also achieved. Meanwhile, the long-term metering method is an important analysis method of the financial institution in the interest rate risk management system, and the long-term metering method can uniformly return and meter the interest rate risks in each stage, provides reference for comparative analysis between different financial products and between different financial institutions, and is also an urgent need for the financial institution to monitor the interest rate risks.
Longevity (also known as duration) is one of the important means of monitoring interest rate risks of financial products. In some related technologies, a CIR (Cox, Ingersoll and Ross) model is used to describe interest rate distribution, and then cash flow occurring in a financial product at a future time is weighted and summed with a period of time from the occurrence of the corresponding cash flow to the present according to a current interest rate discount occurrence value, and the weighted sum is divided by an accumulated value of the current values to obtain a long term of the financial product.
Disclosure of Invention
The inventors found that in the related art, calculation efficiency is low for a long period of time.
The method and the device have the advantages that based on the extracted duration coefficient, each monitored object (such as a financial product) can reuse the duration coefficient to calculate the duration, and therefore the calculation efficiency of the duration is improved. In addition, interest rate distribution information for refining the long-term coefficient is constructed according to the logarithmic form of the interest rate and the logarithmic form of the interest rate fluctuation rate, so that the interest rate and the interest rate fluctuation rate are ensured to be greater than 0, the situation that the negative interest rate, the interest rate fluctuation rate is 0 and the like do not conform to the actual situation is avoided, and the accuracy of long-term calculation is improved.
Some embodiments of the present disclosure provide a risk monitoring method, including:
weighting the cash flow of the monitored object in each time period by using a long-term coefficient to obtain the cash flow present value of the monitored object in each time period, wherein the long-term coefficient is calculated according to the interest rate corresponding to the time parameter, and the interest rate corresponding to the time parameter is determined according to the interest rate distribution information;
calculating the duration of the monitored object according to the cash flow current value of the monitored object in each time period;
and monitoring the interest rate risk of the monitored object according to the long term of the monitored object.
In some embodiments, the interest rate distribution information is constructed from a logarithmic form of interest rate and a logarithmic form of interest rate fluctuation rate.
In some embodiments, said calculating the age factor comprises:
calculating a discount factor according to interest rates corresponding to the time parameters and the current period of the cash flow;
accumulating the discount factors from the period from the occurrence of the first cash flow to the occurrence of the last cash flow to obtain a duration factor.
In some embodiments, the age coefficients include one or more of a first age coefficient, a second age coefficient, a third age coefficient;
the first age factor is:
Figure BDA0002191067830000021
in the case of the single-benefit form,
Figure BDA0002191067830000022
in the form of a multi-interest form,
Figure BDA0002191067830000023
the second age factor is:
Figure BDA0002191067830000024
the third longevity coefficient is:
Figure BDA0002191067830000025
in the case of the single-benefit form,
Figure BDA0002191067830000031
under the continuous multi-interest form, the method can realize the continuous multi-interest form,
Figure BDA0002191067830000032
wherein, yTIndicating interest rate, y, at time TiIndicating an on-demand rate for a certain period of time, EV1And EV2Representing the discount factor, t represents the time period from which cash flow occurred, and N represents the time period from which the last cash flow occurred.
In some embodiments, said calculating the age of the monitored object comprises:
and dividing the current value of the cash flow of the monitored object in each time period by the accumulated value of the current values of the cash flow of the monitored object in each time period, and weighting and summing the current period of the corresponding cash flow and the current period to obtain the long period of the monitored object.
In some embodiments, the age of the monitored subject is weighted with at least one of interest rate scene coefficients and pressure scene coefficients.
In some embodiments, the monitoring interest rate risk of the monitored subject comprises:
and determining the long-term risk quota of the monitored object according to the long term of the monitored object, the long-term fluctuation rate of the monitored object and the quantile point value corresponding to the preset confidence interval.
In some embodiments, the monitoring interest rate risk of the monitored subject comprises:
and monitoring the interest rate risk of the monitored object according to whether the duration of the monitored object exceeds a set threshold value.
Some embodiments of the present disclosure provide a risk monitoring device, comprising:
a memory; and
a processor coupled to the memory, the processor configured to perform the risk monitoring method of any of the embodiments based on instructions stored in the memory.
Some embodiments of the present disclosure propose a non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the risk monitoring method of any of the embodiments.
Drawings
The drawings that will be used in the description of the embodiments or the related art will be briefly described below. The present disclosure will be more clearly understood from the following detailed description, which proceeds with reference to the accompanying drawings,
it is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without undue inventive faculty.
Fig. 1 is a flow diagram illustrating some embodiments of a method for lifetime computation according to the present disclosure.
FIG. 2 is a schematic flow chart diagram illustrating some embodiments of a longevity-based risk monitoring method of the present disclosure.
FIG. 3 is a schematic flow chart diagram illustrating some embodiments of a longevity-based risk monitoring method of the present disclosure.
Fig. 4 is a schematic structural diagram of some embodiments of the risk monitoring device of the present disclosure.
Detailed Description
The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure.
Fig. 1 is a flow diagram illustrating some embodiments of a method for lifetime computation according to the present disclosure. As shown in fig. 1, the term calculation method of this embodiment includes steps 13-14, i.e., each monitored object (e.g., financial product) can calculate the term by reusing a term coefficient; the duration calculation method of this embodiment may further optionally include steps 11-12 of calculating a duration coefficient in advance; the method for calculating the lifetime of this embodiment may further optionally include step 15, weighting the lifetime according to the service requirement.
In step 11, the interest rate corresponding to the time parameter is determined according to the interest rate distribution information.
The interest rate distribution information is constructed according to the logarithmic form of the interest rate and the logarithmic form of the interest rate fluctuation rate, the interest rate and the interest rate fluctuation rate are ensured to be greater than 0, the situations that the negative interest rate, the interest rate fluctuation rate is 0 and the like are not in line with the actual situation are avoided, and the accuracy of long-term calculation is improved.
In some embodiments, interest rate distribution information may be expressed, for example, as:
Figure BDA0002191067830000041
wherein f (x) represents an interest rate distribution function, x represents an interest rate, μ represents a long-term mean value of the interest rate, α represents a recovery rate of the interest rate, and σ represents a fluctuation rate of the interest rate, and x, α, and σ are positive numbers by using logarithmic properties, and μ is a positive number. The interest rate distribution function can be obtained by, for example, logarithmic processing of the CIR distribution function.
In step 12, a longevity coefficient is calculated according to the interest rate corresponding to the time parameter.
In some embodiments, calculating the age factor includes, for example: calculating the discount factor according to the interest rate corresponding to the time parameter and the current period of the cash flow, and accumulating the discount factor from the current period of the first cash flow to the current period of the last cash flow to obtain the long-term coefficient.
The age coefficient includes one or more of a first age coefficient, a second age coefficient, and a third age coefficient. In the following formula, yTIndicating interest rate, y, at time TiIndicating an on-demand rate for a certain period of time, EV1And EV2Representing discount factor, t tableShowing the time period of cash flow from the current time, and N showing the time period of the last cash flow from the current time.
The first age factor is:
Figure BDA0002191067830000051
in the case of the single-benefit form,
Figure BDA0002191067830000052
in the form of a multi-interest form,
Figure BDA0002191067830000053
the second longevity coefficient is:
Figure BDA0002191067830000054
wherein the second duration coefficient can be calculated by performing a first derivative on the first duration coefficient.
The third longevity coefficient is:
Figure BDA0002191067830000055
in the case of the single-benefit form,
Figure BDA0002191067830000056
in the form of a multi-interest form,
Figure BDA0002191067830000057
the third long term coefficient can reflect the change of the immediate interest rate, overcomes the limit of the horizontal interest rate distribution curve hypothesis, and can reflect the actual discount factor and the long term coefficient.
The embodiment calculates the duration coefficient according to the interest rate and the time information, and the duration coefficient is irrelevant to the business information of the monitored object (such as a financial product), so that each monitored object (such as a financial product) can calculate the duration by reusing the various duration coefficients. In addition, in general, the duration coefficient can be pre-calculated and stored, and the duration coefficient can be directly called to calculate the duration of the monitored object (such as a financial product) in the follow-up process, so that the real-time performance and the calculation efficiency of the duration calculation can be improved.
In step 13, the cash flow of the monitored object in each time segment is weighted by using the age factor to obtain the cash flow value of the monitored object in each time segment.
The cash flow of the monitored object in each time period may be directly obtained from the service system, which is exemplified below.
For example: the method comprises the following steps that a certain person deposits an account regularly, the expiration date is 2009-01-01, the due paying mode is one-time cost-back, the interest paying frequency is one-time cost-back, the annual interest rate is 1%, the current balance is 1000 yuan, and then the account has 2 cash flows in the future, wherein the two cash flows are respectively as follows:
first cash flow: the payment date of principal: 2010-01-01, principal payment amount: 1000 yuan;
the second cash flow: interest payment date: 2010-01-01, interest payment amount: 10 yuan.
In the case where the interest rate changes, for example, a monitoring target such as a credit-type monitoring target that makes a significant adjustment to the cash flow due to a change in the interest rate, or an authorized bond, the cash flow rate of the monitoring target can be corrected by the adjustment coefficient.
In some embodiments, the lifetime coefficient is multiplied by the cash flow of the monitored object in each time period to obtain the cash flow of the monitored object in the corresponding time period. The present value of cash flow is also referred to as cash-out flow.
In step 14, the duration of the monitored object is calculated according to the current value of the cash flow of the monitored object in each time period.
Specifically, the current value of the cash flow of the monitored object in each time period is divided by the accumulated value of the current values of the cash flow of the monitored object in each time period, and the accumulated values and the current period of the corresponding cash flow are weighted and summed to obtain the long term of the monitored object.
The first age of the monitored object calculated based on the first age coefficient may be expressed as:
Figure BDA0002191067830000061
wherein the content of the first and second substances,
Figure BDA0002191067830000062
other symbolic meanings are referred to above and will not be described herein.
The second age of the monitored object calculated based on the second age coefficient may be expressed as:
Figure BDA0002191067830000071
the third longevity of the monitored object calculated based on the third longevity coefficient can be expressed as:
Figure BDA0002191067830000072
wherein the content of the first and second substances,
Figure BDA0002191067830000073
other symbolic meanings are referred to above and will not be described herein.
In step 15, the monitoring object is weighted by at least one of the interest rate scene coefficient and the pressure scene coefficient for a long time, so as to obtain the long time under different interest rate scenes and different pressure scenes.
The various durations after weighting with interest rate scene coefficients can be expressed as: mu.sc＊MacD、μc＊D*、
Figure BDA0002191067830000074
Wherein, mucAnd the interest rate scene coefficient is expressed and can be set according to reference factors such as currency, the standard interest rate impact amplitude of the currency, the variation trend of the interest rate distribution curve, the variation trend of short-term interest rate and long-term interest rate and the like.
The age weighted with the pressure scenario coefficients can be expressed as: mu.ss＊MacD、μs＊D*、
Figure BDA0002191067830000075
Wherein, musThe pressure scenario coefficient is expressed, and may be set according to reference factors such as a benchmark interest Rate, a currency exchange Rate change, an economic development cycle stage, and a Loan market price (LPR).
FIG. 2 is a schematic flow chart diagram illustrating some embodiments of a longevity-based risk monitoring method of the present disclosure. The method is suitable for the above-mentioned various long periods, such as MacD and D*、
Figure BDA0002191067830000076
μc＊MacD、μc＊D*、
Figure BDA0002191067830000077
μs＊MacD、μs＊D*、
Figure BDA0002191067830000078
And the like. Therefore, the interest rate risk of the monitored object is monitored according to the long term of the monitored object.
As shown in fig. 2, the method of this embodiment includes steps 21-25.
In step 21, cash flow data of the monitored object is selected through the set time window.
At step 22, according to the method of the embodiment shown in fig. 1, a certain age of the monitored object under the time window is calculated, e.g. MacD, D*、
Figure BDA0002191067830000079
μc＊MacD、μc＊D*、
Figure BDA00021910678300000710
μs＊MacD、μs＊D*、
Figure BDA00021910678300000711
And the like.
In step 23, the time window is divided into a plurality of intervals, and the fluctuation rate of the monitored object in the long term is calculated from the long term at each interval, for example, the variance of the long term at each interval is taken as the fluctuation rate in the long term.
In step 24, a quantile point value corresponding to the preset confidence interval is calculated.
The quantile point values are normally distributed relative to the confidence values, the confidence values at two ends of the confidence interval are input into a normal distribution function, and the quantile point value corresponding to the confidence value can be output. For example, the distribution of quantile point values with confidence values of 95% and 99% is Zα(95％)＝1.645，Zα(99％)＝2.33。
In step 25, the duration D of the monitored object and the duration fluctuation rate σ of the monitored object are calculated according to the aboveDAnd a quantile point value Z corresponding to a preset confidence intervalαDetermining a VAR for a monitoring subject's long-term risk quotaDThe formula is expressed as:
VARD＝ZασDD。
in the embodiment, the long-term risk limit is calculated according to the long term of the monitored object, the interest rate risk of the monitored object is monitored by using the long-term risk limit, and if the interest rate risk exceeds the limit, the interest rate risk of the monitored object is higher.
FIG. 3 is a schematic flow chart diagram illustrating some embodiments of a longevity-based risk monitoring method of the present disclosure. The method is suitable for the above-mentioned various long periods, such as MacD and D*、
Figure BDA0002191067830000081
μc＊MacD、μc＊D*、
Figure BDA0002191067830000082
μs＊MacD、μs＊D*、
Figure BDA0002191067830000083
And the like. Therefore, the interest rate risk of the monitored object is monitored according to the long term of the monitored object.
As shown in fig. 3, the method of this embodiment includes steps 31-32.
In step 31, a threshold for the lifetime is set.
At step 32, a determination is made of a certain age of the monitored object, e.g., MacD, D*、
Figure BDA0002191067830000084
μc＊MacD、μc＊D*、
Figure BDA0002191067830000085
μs＊MacD、μs＊D*、
Figure BDA0002191067830000086
Etc., whether the threshold is exceeded.
In step 33, if the threshold is exceeded, it indicates that the interest rate risk of the monitored object is higher, and at this time, the monitoring result may be sent to achieve the purpose of prompting.
The interest rate risk of the monitored object is monitored according to the duration of the monitored object and the set threshold value, and if the interest rate risk exceeds the threshold value, the interest rate risk of the monitored object is higher.
Fig. 4 is a schematic structural diagram of some embodiments of the risk monitoring device of the present disclosure. As shown in fig. 4, the risk monitoring device 40 of this embodiment includes: a memory 41, and a processor 42 coupled to the memory 41, the processor 42 configured to perform the risk monitoring method of any of the embodiments based on instructions stored in the memory 41.
The memory 41 may include, for example, a system memory, a fixed nonvolatile storage medium, and the like. The system memory stores, for example, an operating system, an application program, a Boot Loader (Boot Loader), and other programs.
As will be appreciated by one skilled in the art, embodiments of the present disclosure may be provided as a method, system, or computer program product. Accordingly, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable non-transitory storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the disclosure. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only exemplary of the present disclosure and is not intended to limit the present disclosure, so that any modification, equivalent replacement, or improvement made within the spirit and principle of the present disclosure should be included in the scope of the present disclosure.

Claims (10)

1. A method of risk monitoring, comprising:
weighting the cash flow of the monitored object in each time period by using a long-term coefficient to obtain the cash flow present value of the monitored object in each time period, wherein the long-term coefficient is calculated according to the interest rate corresponding to the time parameter, and the interest rate corresponding to the time parameter is determined according to the interest rate distribution information;
calculating the duration of the monitored object according to the cash flow current value of the monitored object in each time period;
and monitoring the interest rate risk of the monitored object according to the long term of the monitored object.
2. The method of claim 1, wherein the interest rate distribution information is constructed from a logarithmic form of interest rate and a logarithmic form of interest rate fluctuation rate.
3. The method of claim 1, wherein the calculating the age factor comprises:
calculating a discount factor according to interest rates corresponding to the time parameters and the current period of the cash flow;
accumulating the discount factors from the period from the occurrence of the first cash flow to the occurrence of the last cash flow to obtain a duration factor.
4. The method of claim 3, wherein the age coefficients comprise one or more of a first age coefficient, a second age coefficient, a third age coefficient;
the first age factor is:
Figure FDA0002191067820000011
in the case of the single-benefit form,
Figure FDA0002191067820000012
in the form of a multi-interest form,
Figure FDA0002191067820000013
the second age factor is:
Figure FDA0002191067820000021
the third longevity coefficient is:
Figure FDA0002191067820000022
in the case of the single-benefit form,
Figure FDA0002191067820000023
under the continuous multi-interest form, the method can realize the continuous multi-interest form,
Figure FDA0002191067820000024
wherein, yTIndicating interest rate, y, at time TiIndicating an on-demand rate for a certain period of time, EV1And EV2Representing the discount factor, t represents the time period from which cash flow occurred, and N represents the time period from which the last cash flow occurred.
5. The method of claim 1, wherein the calculating the age of the monitored object comprises:
and dividing the current value of the cash flow of the monitored object in each time period by the accumulated value of the current values of the cash flow of the monitored object in each time period, and weighting and summing the current period of the corresponding cash flow and the current period to obtain the long period of the monitored object.
6. The method of claim 1,
and weighting the long-term utilization rate scene coefficient and the pressure scene coefficient of the monitored object.
7. The method according to any one of claims 1-6, wherein said monitoring interest rate risk of said monitored subject comprises:
and determining the long-term risk quota of the monitored object according to the long term of the monitored object, the long-term fluctuation rate of the monitored object and the quantile point value corresponding to the preset confidence interval.
8. The method according to any one of claims 1-6, wherein said monitoring interest rate risk of said monitored subject comprises:
and monitoring the interest rate risk of the monitored object according to whether the duration of the monitored object exceeds a set threshold value or not, and sending a monitoring result.
9. A risk monitoring device comprising:
a memory; and
a processor coupled to the memory, the processor configured to perform the risk monitoring method of any of claims 1-8 based on instructions stored in the memory.
10. A non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the risk monitoring method of any one of claims 1-8.
CN201910832188.9A 2019-09-04 2019-09-04 Risk monitoring method and device Pending CN112446578A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910832188.9A CN112446578A (en) 2019-09-04 2019-09-04 Risk monitoring method and device

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910832188.9A CN112446578A (en) 2019-09-04 2019-09-04 Risk monitoring method and device

Publications (1)

Publication Number Publication Date
CN112446578A true CN112446578A (en) 2021-03-05

Family

ID=74734806

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910832188.9A Pending CN112446578A (en) 2019-09-04 2019-09-04 Risk monitoring method and device

Country Status (1)

Country Link
CN (1) CN112446578A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113592307A (en) * 2021-08-02 2021-11-02 远见智诚市场调研咨询(广东)有限公司 Enterprise income wind control detection method and device, computer equipment and storage medium

Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1992015064A1 (en) * 1991-02-25 1992-09-03 The Prudential Insurance Company Of America Method and apparatus for volatility analysis of interest rate sensitive financial instruments
EP1023684A1 (en) * 1997-10-14 2000-08-02 Derivatives Net, Inc. Systems, methods and computer program products for electronic trading of financial instruments
US20040172355A1 (en) * 2003-02-06 2004-09-02 Pandher Gurupdesh S. Option valuation method and apparatus
CN101246579A (en) * 2008-03-21 2008-08-20 中国工商银行股份有限公司 Device, system and method for bank rate risk evaluation and monitoring
CN101714273A (en) * 2009-05-26 2010-05-26 北京银丰新融科技开发有限公司 Rule engine-based method and system for monitoring exceptional service of bank
CN101826196A (en) * 2010-04-14 2010-09-08 中国工商银行股份有限公司 Secular data metering system for interest rate risk monitoring
US20120023040A1 (en) * 2010-07-23 2012-01-26 Grant Thornton Llp Method and system for real-time equity risk premium
US20140379550A1 (en) * 2013-06-20 2014-12-25 Chicago Mercantile Exchange Inc. Blending Methodology for Settling Swaption Volatility Cube and Prices
JP5955436B1 (en) * 2015-04-23 2016-07-20 株式会社三井住友銀行 Loan risk evaluation parameter calculation apparatus, program, and method
JP2016162417A (en) * 2015-03-05 2016-09-05 株式会社日立製作所 Interest rate risk evaluation program and interest rate risk evaluation apparatus
CN107301486A (en) * 2016-04-15 2017-10-27 平安科技（深圳）有限公司 Risk management and control method and system

Patent Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1992015064A1 (en) * 1991-02-25 1992-09-03 The Prudential Insurance Company Of America Method and apparatus for volatility analysis of interest rate sensitive financial instruments
EP1023684A1 (en) * 1997-10-14 2000-08-02 Derivatives Net, Inc. Systems, methods and computer program products for electronic trading of financial instruments
US20040172355A1 (en) * 2003-02-06 2004-09-02 Pandher Gurupdesh S. Option valuation method and apparatus
CN101246579A (en) * 2008-03-21 2008-08-20 中国工商银行股份有限公司 Device, system and method for bank rate risk evaluation and monitoring
CN101714273A (en) * 2009-05-26 2010-05-26 北京银丰新融科技开发有限公司 Rule engine-based method and system for monitoring exceptional service of bank
CN101826196A (en) * 2010-04-14 2010-09-08 中国工商银行股份有限公司 Secular data metering system for interest rate risk monitoring
US20120023040A1 (en) * 2010-07-23 2012-01-26 Grant Thornton Llp Method and system for real-time equity risk premium
US20140379550A1 (en) * 2013-06-20 2014-12-25 Chicago Mercantile Exchange Inc. Blending Methodology for Settling Swaption Volatility Cube and Prices
JP2016162417A (en) * 2015-03-05 2016-09-05 株式会社日立製作所 Interest rate risk evaluation program and interest rate risk evaluation apparatus
JP5955436B1 (en) * 2015-04-23 2016-07-20 株式会社三井住友銀行 Loan risk evaluation parameter calculation apparatus, program, and method
CN107301486A (en) * 2016-04-15 2017-10-27 平安科技（深圳）有限公司 Risk management and control method and system

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113592307A (en) * 2021-08-02 2021-11-02 远见智诚市场调研咨询(广东)有限公司 Enterprise income wind control detection method and device, computer equipment and storage medium
CN113592307B (en) * 2021-08-02 2023-08-18 远见智诚市场调研咨询(广东)有限公司 Enterprise profit wind control detection method, device, computer equipment and storage medium

Similar Documents

Publication Publication Date Title
CN110633893B (en) Policy effectiveness monitoring method and device and computer equipment
CN109583729B (en) Data processing method and device for platform online model
US20150302336A1 (en) Strategic partner governance framework and performance tracking
CN112446578A (en) Risk monitoring method and device
RU2015116731A (en) SYSTEMS AND METHODS OF PROVIDING AUTOMATED CORRECTIVE WIRES
CN111353901A (en) Risk identification monitoring method and device and electronic equipment
CN115375459A (en) Overdue interest determination method, device, equipment and medium
CN110619583A (en) Account early warning information generation method and device
CN110532156A (en) A kind of capacity prediction methods and device
CN113361798A (en) Reservoir flood control scheduling method and system based on pre-discharge index and storage medium
JP2014006578A (en) Marketplace risk prediction device, marketplace risk prediction method, and marketplace risk prediction program
CN111583010A (en) Data processing method, device, equipment and storage medium
US8751286B2 (en) Loss distribution calculation system, loss distribution calculation method and loss distribution calculation-use program
CN113868308A (en) Event analysis method, device and storage medium
CN114663232A (en) Abnormal transaction behavior monitoring method and device and computer program product
CN113849683A (en) User regular behavior identification method and device
Perederiy Endogenous derivation and forecast of lifetime PDs
KR20140029994A (en) Method for verifying sutability of loss given default/exposure at default
CN113657892A (en) Method and device for controlling transaction in network-free state
CN113627932B (en) Method and device for controlling waiting time of terminal application account in network-free state
US7873575B1 (en) Dynamic credit spread model
US20160350864A1 (en) Goal guarantee system
KR20210053716A (en) Apparatus and method for evaluating project
CN116862646A (en) User risk assessment method and device and electronic equipment
CN111898800A (en) Accumulation fund payment data prediction method and device and electronic equipment

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
CB02 Change of applicant information
CB02 Change of applicant information

Address after: Room 221, 2 / F, block C, 18 Kechuang 11th Street, Daxing District, Beijing, 100176

Applicant after: Jingdong Technology Holding Co.,Ltd.

Address before: Room 221, 2 / F, block C, 18 Kechuang 11th Street, Daxing District, Beijing, 100176

Applicant before: Jingdong Digital Technology Holding Co.,Ltd.

Address after: Room 221, 2 / F, block C, 18 Kechuang 11th Street, Daxing District, Beijing, 100176

Applicant after: Jingdong Digital Technology Holding Co.,Ltd.

Address before: Room 221, 2 / F, block C, 18 Kechuang 11th Street, Daxing District, Beijing, 100176

Applicant before: JINGDONG DIGITAL TECHNOLOGY HOLDINGS Co.,Ltd.