CN116205742A - System and method for accurately simulating cash flow of consumed financial assets - Google Patents
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Abstract
The invention relates to a system and a method for accurately simulating cash flow of a consumed financial asset, wherein the device comprises an input field standardization unit, a parameter value extraction unit of a simulation factor, a cash flow simulation unit of an asset life cycle, an asset quality index calculation unit and a positioning factor offset and quantization deviation value unit; the parameter value extraction unit of the simulation factor is used for extracting key parameters such as newly increased overdue rate, mobility, early compensation rate and the like; the cash flow simulation unit of the asset life cycle is used for calculating and simulating each minimum granularity index value of a single asset; the asset quality index calculation unit is used for calculating pricing yield, long term, loss rate, net price difference and the like of the standard asset; the positioning factor offset and quantization deviation value unit is used for describing the sensitivity of the asset quality of the single asset to the factors so as to perform parameter calibration and model iteration and simulate cash flow trend changes in the life cycle of the asset more accurately.
Description
Technical Field
The invention relates to the technical field of consumption financial asset simulation tools, in particular to a system and a method for accurately simulating cash flow of consumption financial assets.
Background
The following is merely representative of the applicant's background art and is not admitted to be prior art by the public at any time known in the art.
The consumer financial business is a "quantized" business. When a financial service entity (especially a trusted company) performs a consumer financial business, it is necessary to simulate, analyze, monitor and predict the consumer financial assets during the entire period of the business. A pre-lending stage in which cash flow recovery of the asset is simulated from the sample data; in the lending stage, the quality deviation condition of the asset is required to be monitored according to the existing performance of the asset, a deviation factor is positioned, a throwing strategy is adjusted, and the cash flow flowing out and recycling which are not yet achieved are further simulated; in the post-loan stage, the historical performance and income situation of the assets need to be traced back, and cash flow redemption gaps are predicted to formulate a coping scheme.
In the prior art, three-party institutions (such as technical service companies, rating institutions, accounting institutions and the like) can partially meet the simulation requirements of the pre-loan stage, but have a plurality of defects, such as non-uniform adjustment fields of different three-party institutions, different caliber definitions and incomparable results; the service is not well understood, the measuring and calculating logic is not transparent, the algorithm coarse precision is limited, and the output dimension is not enough; high measuring and calculating cost, low feedback efficiency, high communication cost and the like. In the middle and post-loan stages, the financial service body has no mature tool to use, so that verification of simulation effectiveness in the adjustment stage is lacking, so that the post-loan and pre-loan are disjointed, the subsequent asset release and management are difficult to guide, and the full-period quantitative management goal is not achieved.
In summary, the existing consumer financial asset simulation tools cannot cover the full period of management, and the existing simulation methods of the three-party institutions have the defects of inaccuracy, opacity, discontinuity and non-uniformity. Accordingly, there is an urgent need to independently develop a system and method for accurately simulating cash flow of a consumed financial asset.
Disclosure of Invention
The invention aims to provide a system and a method for accurately simulating cash flow of consumed financial assets, which are used for solving the problems of tool deficiency, different methods and poor accuracy of a trusted company in the aspects of analyzing and managing consumed financial assets.
The invention aims to solve the defects of the prior art and provides a system for accurately simulating the cash flow of a consumed financial asset, which comprises an input field standardization unit, a parameter value extraction unit of a simulation factor, a cash flow simulation unit of an asset life cycle, an asset quality index calculation unit and a positioning factor deviation and quantization deviation value unit; the input field standardization unit is used for obtaining standard fields according to the data of the static pool caliber input by the asset end; the parameter value extraction unit of the simulation factor is used for extracting newly increased overdue rate, mobility, absolute early compensation rate, early compensation long term, return long term, normal principal coefficient and normal interest coefficient; the cash flow simulation unit of the asset life cycle is used for calculating the following indexes for a single product: advancing payoff principal, advancing payoff interest, normal principal balance, returning normal principal, returning overdue principal, recovering interest, collecting default principal, overdue principal balance, overdue 1-30 days (M1 loan balance), overdue 31-60 days (M2 loan balance), overdue 61-90 days (M3 loan balance), overdue 91-120 days (M4 loan balance), bad account loan balance (D loan balance); the asset quality index calculation unit is used for calculating pricing yield, long term, loss rate and net price difference; the positioning factor offset and quantization deviation value unit is used for selecting a reference value of a single factor or a plurality of factors, drawing up a factor change step length, changing the parameter of the selected factor into a reference value plus step length, describing the sensitivity of the asset quality of the standard asset to the factor, and more accurately simulating the internal cash flow and trend change of the life cycle of the standard asset
Preferably, the standard fields include deadline, repayment style, payment month, viewing month, payment amount in month, weighted average execution interest rate, normal loan balance, M1 loan balance, M2 loan balance, M3 loan balance, M4 loan balance, M5 loan balance, M6 loan balance, M6+ loan balance, early monthly principal, late monthly principal, early monthly principal, normal principal returned in month, and late monthly principal.
Preferably, the method for extracting the M1 loan balance specifically comprises the following steps:
the extraction method of the newly increased overdue rate specifically comprises the following steps:
s101, obtaining a new overdue rate (M1 rate for short), wherein the formula is as follows: observing the loan balance/the current month deposit amount of the month M1;
s102, eliminating abnormal values, wherein the formula is as follows: the M1 rate is more than 5 percent or the M1 rate is less than 0 or the M1 rate is 0 between the 1 st account age and the longest account age of the asset;
s103, weighting and averaging according to account age and period number, wherein the formula is as follows: sigma month deposit amount the current month M1 rate/sigma month deposit amount.
Preferably, the mobility extraction method specifically comprises the following steps
S201, calculating mobility, wherein the formula is as follows:
mobility m1_m2=current M2 loan balance/previous M1 loan balance from M1 loan balance to M2 loan balance;
mobility of M2 to M3 loan balance m2_m3=current M3 loan balance/previous M2 loan balance;
mobility of M3 to M4 loan balance m3_m4=current M4 loan balance/previous M3 loan balance;
mobility m4_d of M4 to D loan balance = current newly added bad account loan balance/previous M4 loan balance;
s202, eliminating abnormal values, wherein the formula is as follows: mobility >1 or mobility < = 0 or mobility outside three standard deviations (3 sigma criterion for short, mean ± 3 standard deviations) as outlier rejection;
s203, weighted average according to the number of times, wherein the formula is as follows: sigma current month deposit amount. Mobility/Σcurrentmonth deposit amount.
Preferably, the extraction method of early compensation rate specifically comprises the following steps:
s301, solving absolute early compensation rate, wherein the formula is as follows: the present money/the present money amount is paid early in the current month;
s302, eliminating abnormal values, and if the absolute early compensation rate obtained through calculation is greater than 1 or less than or equal to 0, eliminating the abnormal values;
s303, weighted average according to account age and period number, wherein the formula is as follows: sigma current month deposit amount. Early compensation rate/sigma current month deposit amount.
Preferably, the extraction method for early compensation and long term specifically comprises the following steps:
s401, early compensation long period, wherein the formula is as follows: early compensation interest in month/(normal loan balance in early period × interest rate/act); wherein act=360 or 365;
s402, eliminating abnormal values, and if the calculated early compensation period is greater than 45, eliminating the abnormal values;
s403, weighted average according to account age and period number, wherein the formula is as follows: sigma current month deposit amount × early compensated long term/sigma current month deposit amount.
Preferably, the method for extracting the return-to-life specifically comprises the following steps:
s501, calculating a catalytic recovery period X, wherein the formula is as follows:
[ m1_c x+m2_c (x+30) +m3_c (x+60) +m4_c (x+90) ] (1+ penalty floating ratio) xinterest/act=current month refund penalty, wherein m1_c=current M2 loan balance-upper M1 loan balance, m2_c=current M3 loan balance-upper M2 loan balance, m3_c=current M4 loan balance-upper M3 loan balance, m4_c=current M5 loan balance-upper M4 loan balance;
s502, eliminating abnormal values, wherein if the calculated return-to-life period is more than 31 days or less than 0 days, the abnormal values are eliminated;
s503, weighted average according to account age and period number, wherein the formula is as follows: sigma current month deposit amount × the return-to-the-long term/Σcurrentmonth deposit amount.
Preferably, the method for extracting the normal principal coefficients specifically comprises the following steps:
s601, solving a normal principal coefficient, wherein the formula is as follows: normal repayment in month/(normal loan balance in month+normal repayment in month);
s602, eliminating abnormal values, wherein the formula is as follows:
if the normal principal coefficient of the account age > number of the period +1 is not equal to 0, rejecting the account age as an abnormal value;
s603, weighted average according to account age and period number, wherein the formula is as follows: sigma current month deposit amount normal principal coefficient/sigma current month deposit amount.
Preferably, the method for extracting the normal interest coefficient specifically comprises the following steps:
s701, solving a normal interest coefficient, wherein the formula is as follows: normal interest in the month/(normal loan balance in the month+normal repayment in the month);
s702, eliminating abnormal values, wherein for equal fees, equal information or credit card-like repayment modes, if the calculated normal interest coefficient is more than 1, the abnormal values are eliminated; for repayment modes except for equal cost, equal cost and the like or credit card, if the calculated normal interest coefficient is more than 0.03, rejecting the repayment modes as abnormal values;
s703, weighted average according to account age and period number, wherein the formula is as follows: sigma current month deposit amount normal interest factor/sigma current month deposit amount.
Preferably, the specific method for calculating the related index by the asset quality index calculating unit comprises the following steps:
s901, calculating a static overdue rate vintageM3+ more than 90 days after overdue, wherein the formula is as follows:
vintagem3+ =m1_m2_m2_m3_m3_m4_m4_d Σm1i, i=1, 2 … … asset periods, asset period +1; m1_m2 is the mobility of the M1 loan balance to the M2 loan balance; m2_m3 is the mobility of the M2 loan balance to the M3 loan balance; m3_m4 is the mobility of the M3 loan balance to the M4 loan balance; m4_d is the mobility of the M4 loan balance to the D loan balance; m1i is the newly increased overdue rate;
s902, calculating a long term, wherein the formula is as follows:
long term (month) = Σaccount age x recovery principal amount per account age/recovery principal amount per account age;
s903, calculating a loss rate, wherein the formula is as follows:
loss rate= (vintagem3+) -12/long term;
s904, calculating a net valence difference IRR:
the net price difference is obtained through iterative calculation, and the specific calculation method comprises the following steps:
wherein NCF (m) is net cash flow of the mth account age, and m is the account age; NCF (m) =withdrawal principal m +withdrawal interest m + collect the deposit of default m =pay-ahead principal m + advance repayment interest m Normal principal of return + m Normal interest return to + m +recovery of overdue principal m +recovery of overdue interest and penalty m + collect the deposit of default m ；
R calculated by an iterative algorithm is a month number;
net valence difference = r 12;
s905, calculating pricing yield: resetting the early compensation rate and the newly added overdue rate parameters to 0, and repeating the step S904 to calculate the pricing yield.
The invention also provides a method for accurately simulating the cash flow of the consumption financial asset, which comprises the following steps:
first step, standardizing input fields: obtaining standard fields according to data of a static caliber input by a property end, wherein the standard fields comprise a deadline, a repayment mode, a repayment month, an observation month, a current month repayment amount, a weighted average execution interest rate, a normal loan balance, an M1 loan balance, an M2 loan balance, an M3 loan balance, an M4 loan balance, an M5 loan balance, an M6 loan balance, an M6+ loan balance, a current month early compensation principal, a current month early compensation interest, a current month real principal, a current month returning normal principal and a current month recovery overdue principal;
extracting parameter values of simulation factors, including newly increased overdue rate, mobility, early compensation rate, early compensation long term, return long term, normal principal coefficient and normal interest coefficient;
third, simulating cash flow of the life cycle of the asset, and calculating the following indexes for a single product: advancing payoff principal, advancing payoff interest, normal principal balance, returning normal principal, returning normal interest, recovering overdue principal, recovering overdue interest, recovering principal, recovering interest, recovering surprise, collecting default principal, overdue principal balance, M1 loan balance, M2 loan balance, M3 loan balance, M4 loan balance and D loan balance;
the fourth step, calculate the quality index of the asset, include specifically:
s901, calculating a static overdue rate vintageM3+ more than 90 days after overdue, wherein the formula is as follows:
vintagem3+ =m1_m2_m2_m3_m3_m4_m4_d Σm1i, i=1, 2 … … asset periods, asset period +1; m1_m2 is the mobility of the M1 loan balance to the M2 loan balance; m2_m3 is the mobility of the M2 loan balance to the M3 loan balance; m3_m4 is the mobility of the M3 loan balance to the M4 loan balance; m4_d is the mobility of the M4 loan balance to the D loan balance; m1i is the newly increased overdue rate;
s902, calculating a long term, wherein the formula is as follows:
long term (month) = Σaccount age x recovery principal amount per account age/recovery principal amount per account age;
s903, calculating a loss rate, wherein the formula is as follows:
loss rate= (vintagem3+) -12/long term;
s904, calculating a net valence difference:
the net valence difference IRR is obtained through iterative calculation, and the specific calculation method comprises the following steps:
wherein NCF (m) is net cash flow of the mth account age, and m is the account age; NCF (m) =withdrawal principal m +withdrawal interest m + collect the deposit of default m =pay-ahead principal m + advance repayment interest m Normal principal of return + m Normal interest return to + m +recovery of overdue principal m +recovery of overdue interest and penalty m + collect the deposit of default m ；
R calculated by an iterative algorithm is a month number;
net valence difference irr=r 12;
s905, calculating pricing yield: resetting the early compensation rate and the newly added overdue rate parameters to 0, and repeating the step S904 to calculate the pricing yield;
fifth, the offset of the positioning factor and the quantized offset value specifically include:
the proposed net price difference formula is as follows:
net price difference = pricing rate of return-loss rate = pricing rate of return-12/lifetime vintagem3+;
factors influence the index, which influences the net price difference; for each factor, the elasticity of the factor for the net valence difference can be characterized, the elasticity = the variation ratio of the dependent variable/the variation ratio of the independent variable = (Δy/y)/(Δx/x), the elasticity of each factor for the net valence difference is calculated, and the model error and the factor offset are quantized to calibrate the model. The greater the elasticity the greater the factor importance, the higher frequency iteration or calibration can be set.
S1001, selecting a reference value of a single or multiple factors;
s1002, a factor change step is formulated, and the step=factor reference value is 1%;
s1003, changing the parameter of the selected factor into a reference value plus step length, repeating the third step and the fourth step, and calculating a new net price difference;
s1004, factor elasticity= [ (new net valence difference-reference net valence difference)/reference net valence difference ]/1%.
Advantageous effects
Compared with the prior art, the invention has the beneficial effects that:
the system and the method for accurately simulating the cash flow of the consumed financial asset provide a set of complete methods for splitting, calculating, extracting and using the simulation factors through splitting factors, constructing indexes, extracting indexes and establishing a checking relation, generate the cash flow of the consumed financial asset through algorithm simulation, so as to carry out cash flow analysis, yield analysis and project full period management, and solve the problems of tool deficiency, different methods and poor accuracy of a trusted company in the aspects of analysis and management of the consumed financial asset.
The invention unifies 7 simulation factors: the cash flow of the asset is simulated through the inherent arithmetic logic of each simulation factor, and the cash flow and the income ratio conditions of each party in the circulation purchasing mode are further simulated. In addition, the design of the simulation factors fully considers the independence and the coupling relation among the factors, and when the values of the simulation factors change, cash flow conditions under the pressure factors can be simulated so as to meet the sensitivity analysis and pressure test requirements of the whole project operation period.
The method has good accuracy, universality and stability, can be embedded into a monitoring operation system for managing various small-amount scattered assets by a trust company, and fills up the tool blank of the trust company in the aspects of identifying, metering, monitoring and analyzing the risk of the gold-eliminating assets.
(1) Accuracy. The algorithm for splitting and extracting the factor parameters provided by the method is more in line with the inherent logic of the consumption financial assets (many algorithms in the prior art are not opposite), each factor is relatively independent and convenient for sensitivity analysis, and splitting can be carefully convenient for tracing and positioning to find out the reason of asset quality variation.
(2) Universality. On the one hand, specific payment modes such as equal cost, equal cost and the like are not required to be known, and the method can process asset cash flows in various typical payment modes, mixed payment modes, and special payment modes designed by each institution or product by self by using the unified rule extraction factors. In another aspect, the method of the present invention is applicable to a wide variety of small-scale discrete assets that conform to law of large numbers, such as personal cash credits, personal scene credits, business operations credits, and the like.
(3) Stability. The method has stable and consistent algorithm, can be simultaneously used for overall process management of project analysis and monitoring before, during and after the loan, and ensures that the analysis result is comparable, traceable and attributive.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate and do not limit the invention.
FIG. 1 is a schematic representation of an asset quality (net price difference) deconstructment in accordance with the present invention.
Detailed Description
The present invention is described in more detail below to facilitate an understanding of the present invention.
The consumption of financial class assets belongs to a small decentralized asset, which complies with the law of high numbers. The invention provides a complete method for splitting, calculating, extracting and using simulation factors by splitting factors, constructing indexes, extracting indexes and establishing a colluded relationship, generates cash flow of consumed financial assets through algorithm simulation, is used for carrying out cash flow analysis, yield analysis and project full period management, and solves the problems of tool deficiency, different methods and poor accuracy of a trusted company in the aspects of analysis and management of consumed financial assets.
Specifically, the invention provides a system for accurately simulating cash flow of a consumed financial asset, as shown in fig. 1 (fig. 1 shows factors affecting net price difference (asset quality), which comprises an input field standardization unit, a parameter value extraction unit for simulating factors, a cash flow simulation unit for asset life cycle, an asset quality index calculation unit and a positioning factor offset and quantization deviation value unit; the input field standardization unit is used for obtaining standard fields according to the data of the static pool caliber input by the asset end; the parameter value extraction unit of the simulation factor is used for extracting newly increased overdue rate, mobility, early compensation rate, early compensation long term, return long term, normal principal coefficient and normal interest coefficient; the cash flow simulation unit of the asset life cycle is used for calculating the following indexes for a single product: advancing payoff principal, advancing payoff interest, normal principal balance, returning normal principal, returning normal interest, recovering overdue principal, recovering overdue interest, recovering principal, recovering interest, recovering surprise, collecting default principal, overdue principal balance, M1 loan balance, M2 loan balance, M3 loan balance, M4 loan balance and D loan balance; the asset quality index calculation unit is used for pricing yield, long term, loss rate, net price difference and the like; the positioning factor offset and quantization deviation value unit is used for selecting a reference value of a single factor or a plurality of factors, drawing up a factor change step length, changing the parameter of the selected factor into the reference value plus step length, and describing the sensitivity of the asset quality of a single asset to the factor so as to perform parameter calibration and model iteration and simulate cash flow trend change in the life cycle of the asset more accurately.
Preferably, the standard fields include deadline, repayment mode, repayment month, observation month, current month payment amount (ten thousand), weighted average execution interest rate (year), normal loan balance (including margin), M1 loan balance (not including margin), M2 loan balance, M3 loan balance, M4 loan balance, M5 loan balance, M6 loan balance, m6+ loan balance (including core round-robin), current month early compensation principal, current month early compensation interest, current month real principal (normal+early compensation+overdue return), current month real principal (normal+early compensation), current month real compensation (overdue), current month return principal (optional packing, more accurate), and current month recovery overdue principal (optional packing, more accurate).
Preferably, the method for extracting the M1 loan balance specifically comprises the following steps:
s101, obtaining a new overdue rate (M1 rate for short), wherein the formula is as follows: observing the loan balance/the current month deposit amount of the month M1;
s102, eliminating abnormal values, wherein the formula is as follows: the M1 rate is more than 5 percent or the M1 rate is less than 0 or the M1 rate is 0 between the account age 1 and the longest period of the account age asset, and then the account age asset is rejected as an abnormal value;
s103, weighting and averaging according to account age and period number, wherein the formula is as follows: sigma month deposit amount the current month M1 rate/sigma month deposit amount.
Preferably, the mobility extraction method specifically includes the following steps:
s201, calculating mobility, wherein the formula is as follows:
m1_m2 (mobility of M1 to M2 loan balance) =current M2 loan balance/previous M1 loan balance;
m2_m3 (mobility of M2 to M3 loan balance) =current M3 loan balance/previous M2 loan balance;
m3_m4 (mobility of M3 to M4 loan balance) =current M4 loan balance/previous M3 loan balance;
m4_d (mobility of M4 to D loan balance) =newly added bad account loan balance at the current period/M4 loan balance at the previous period;
s202, eliminating abnormal values, wherein the formula is as follows: mobility >1 or mobility < = 0 or mobility outside three standard deviations (3 sigma criterion for short, mean ± 3 standard deviations), then rejecting as outliers;
s203, weighted average according to the number of times, wherein the formula is as follows: sigma current month deposit amount. Mobility/Σcurrentmonth deposit amount.
Preferably, the extraction method of early compensation rate specifically comprises the following steps:
s301, solving absolute early compensation rate, wherein the formula is as follows: the present money/the present money amount is paid early in the current month;
s302, eliminating abnormal values, and if the absolute early compensation rate obtained through calculation is greater than 1 or less than or equal to 0, eliminating the abnormal values;
s303, weighted average according to account age and period number, wherein the formula is as follows: sigma current month deposit amount. Early compensation rate/sigma current month deposit amount.
Preferably, the extraction method for early compensation and long term specifically comprises the following steps:
s401, early compensation long period, wherein the formula is as follows: early compensation interest in month/(normal loan balance at early date:/act) 1 ) The method comprises the steps of carrying out a first treatment on the surface of the Wherein act is 1 =360 or 365;
s402, eliminating abnormal values, and if the calculated early compensation period is greater than 45, eliminating the abnormal values;
s403, weighted average according to account age and period number, wherein the formula is as follows: sigma current month deposit amount × early compensated long term/sigma current month deposit amount.
Preferably, the method for extracting the return-to-life specifically comprises the following steps:
s501, calculating a catalytic recovery period X, wherein the formula is as follows:
[ m1_c x+m2_c (x+30) +m3_c (x+60) +m4_c (x+90) ] (1+ penalty floating ratio) xinterest/act=current month refund penalty, wherein m1_c=current M2 loan balance-upper M1 loan balance, m2_c=current M3 loan balance-upper M2 loan balance, m3_c=current M4 loan balance-upper M3 loan balance, m4_c=current M5 loan balance-upper M4 loan balance;
s502, eliminating abnormal values, wherein if the calculated return-to-life period is more than 31 days or less than 0 days, the abnormal values are eliminated;
s503, weighted average according to account age and period number, wherein the formula is as follows: sigma current month deposit amount × the return-to-the-long term/Σcurrentmonth deposit amount.
Preferably, the method for extracting the normal principal coefficients specifically comprises the following steps:
s601, solving a normal principal coefficient, wherein the formula is as follows: normal repayment in month/(normal loan balance in month+normal repayment in month);
s602, eliminating abnormal values, wherein the formula is as follows: if the normal principal coefficient of the account age > number of the period +1 is not equal to 0, rejecting the account age as an abnormal value;
s603, weighted average according to account age and period number, wherein the formula is as follows: sigma current month deposit amount normal principal coefficient/sigma current month deposit amount.
Preferably, the method for extracting the normal interest coefficient specifically comprises the following steps:
s701, solving a normal interest coefficient, wherein the formula is as follows: normal interest in the month/(normal loan balance in the month+normal repayment in the month);
s702, eliminating abnormal values, wherein for equal fees, equal information or credit card-like repayment modes, if the calculated normal interest coefficient is more than 1, the abnormal values are eliminated; for repayment modes except for equal cost, equal cost and the like or credit card, if the calculated normal interest coefficient is more than 0.03, rejecting the repayment modes as abnormal values;
s703, weighted average according to account age and period number, wherein the formula is as follows: sigma current month deposit amount normal interest factor/sigma current month deposit amount.
Preferably, the specific method for calculating the related index by the asset quality index calculating unit comprises the following steps:
s901, calculating vintageM3+ (static overdue rate over 90 days), wherein the formula is as follows:
vintagem3+ =m1_m2_m2_m3_m3_m4_m4_d Σm1i, i=1, 2 … … asset periods, asset period +1; m1_m2 is the mobility of the M1 loan balance to the M2 loan balance; m2_m3 is the mobility of the M2 loan balance to the M3 loan balance; m3_m4 is the mobility of the M3 loan balance to the M4 loan balance; m4_d is the mobility of the M4 loan balance to the D loan balance; m1i is the newly increased overdue rate;
s902, calculating a long term, wherein the formula is as follows:
long term (month) = Σaccount age x recovery principal amount per account age/recovery principal amount per account age;
s903, calculating a loss rate, wherein the formula is as follows:
loss rate= (vintagem3+) -12/long term;
s904, calculating a net valence difference IRR:
the net price difference is obtained through iterative calculation, and the specific calculation method comprises the following steps:
wherein NCF (m) is net cash flow of the mth account age, and m is the account age; NCF (m) =withdrawal principal m +withdrawal interest m + collect the deposit of default m =pay-ahead principal m + advance repayment interest m Normal principal of return + m Normal interest return to + m +recovery of overdue principal m +recovery of overdue interest and penalty m + collect the deposit of default m ；
R calculated by an iterative algorithm is a month number;
net valence difference = r 12;
s905, calculating pricing yield: resetting the early compensation rate and the newly added overdue rate parameters to 0, and repeating the step S904 to calculate the pricing yield.
The invention also provides a method for accurately simulating the cash flow of the consumption financial asset, which comprises the following steps:
first step, standardizing input fields: the method comprises the steps of inputting static pool caliber data according to a property end to obtain standard fields, wherein the standard fields comprise a term, a repayment mode, a repayment month, an observation month, a current month repayment amount (ten thousands), a weighted average execution interest rate (year), a normal loan balance (including a wide limit), an M1 loan balance (not including a wide limit), an M2 loan balance, an M3 loan balance, an M4 loan balance, an M5 loan balance, an M6 loan balance, an M6+ loan balance (including a core pin), a current month repayment principal, a current month repayment interest (normal+early payment), a current month repayment penalty interest (overdue), a current month repayment normal principal (optional filling column, more accurate filling column) and a current month repayment principal (optional column, more accurate filling column);
secondly, extracting parameter values of simulation factors:
third, simulate cash flow of asset lifecycle:
assuming that the table length of each product=product period number n+5, m=0, 1 … … n+5, where N is a positive integer equal to or greater than 0, the following index is calculated for a single product:
pay principal in advance, calculation order 1:
■ When m=0, 1 … … n+1, the repayment principal m=initial payment amount x absolute early compensation rate x early compensation distribution m;
■ m=n+2, … … n+5, pay principal m=0 in advance;
early repayment interest, calculation sequence 2:
■ When m=0, 1 … … n+1, advance repayment interest m=advance repayment principal m pricing interest rate early compensation long period m;
■ m=n+2, … … n+5, advance payoff interest m=0;
normal principal balance, calculation order 3:
■ Normal principal balance m=normal principal balance M-1-return normal principal M-repayment principal M-M1 loan balance M in advance;
returning normal principal, calculating sequence 2:
■ Returning normal principal m=0 when m=0;
■ When m=1, 2 … … n+1, returning the normal principal m= (normal principal balance M-1-repayment principal M-M1 loan balance M in advance) the normal principal/the remaining normal principal M in the same period;
■ Returning normal principal m=0 when m=n+2, … … n+5;
returning normal interest, calculation order 3:
■ Returning normal interest m=0 when m=0;
■ When m=1, 2 … … n+1, return normal interest m= (normal principal balance m+return normal principal m) normal interest/remaining normal principal m in the same period;
■ Returning normal interest m=0 when m=n+2, … … n+5;
recovery of overdue principal, calculation sequence 6:
■ Recovering overdue principal=0 when m=0;
■ Recovering overdue principal when m= … … n+5 m M1 loan balance m-1 * m1_C recovery+m2 loan balance m-1 * m2_C recovery+ … … M4 loan balance m-1 * M4_c recovery; wherein m1_c recovery = 1-m1_m2 mobility, … …, m4_c recovery = 1-m4_d mobility;
recovery of overdue interest and fines, calculation order 7:
■ A is overdue penalty corresponding to overdue principal recovery;
■A m ＝SUMPRODUCT(M1 m-1 、M2 m-1 、M3 m-1 、M4 m-1 recovery per state, recovery per state = pricing rate/365 (1+ penalty floating rate), recovery per state = {15,45,75,105}, recovery per state = 1-mobility when parameters are absent;
■ "SUMPRODUCT" means multiplication and addition, respectively;
withdraw principal, calculate sequence 7:
■ Withdraw principal m Return to normal principal m + pay-off principal in advance m +recovery of overdue principal m ；
Retraction interest, calculation sequence 8:
■ Withdrawal of interest m Return to normal interest m + advance repayment interest m +recovery of overdue interest and penalty m ；
Receiving the default gold, and calculating the sequence 2:
■ The method comprises the steps of referring to the default deposit of payment in advance, collecting the default deposit m=the default deposit rate of payment in advance;
overdue principal balance, calculation order 6:
■ Overdue principal balance m ＝M1 m +M2 m +M3 m +M4 m +D m ；
M1 loan balance, calculate order 1:
■ M1=0 when m=0, n+2, n+3, n+4, n+5; m=1, … … n+1, m1=initial delivery scale M1 rate m ；
M2 loan balance, calculate order 2:
■ m=0, 1, n+3, n+4, n+5, m2=0;
■ m= … … n+2, M2 m ＝M1 m-1 * Mobility m1_m2;
m3 loan balance, calculate order 3:
■ m=0, 1,2, n+4, n+5, m3=0;
■ m= … … n+3, M3 m ＝M2 m-1 * Mobility m2_m3;
m4 loan balance, calculation order 4:
■ m=0, 1,2, 3, n+5, m4=0;
■ m= … … n+4, M4 m ＝M3 m-1 * Mobility m3_m4;
and O D, loan balance, calculating sequence 5:
■ When m=0, 1,2, 3, 4, d=0;
■ When m= … … n+5, dm=dm-1+m4m-1, mobility m4_d;
the fourth step, calculate the quality index of the asset, include specifically:
preferably, the specific method for calculating the related index by the asset quality index calculating unit comprises the following steps:
s901, calculating vintageM3+ (static overdue rate over 90 days), wherein the formula is as follows:
vintagem3+ =m1_m2_m2_m3_m3_m4_m4_d Σm1i, i=1, 2 … … asset periods, asset period +1; m1_m2 is the mobility of the M1 loan balance to the M2 loan balance; m2_m3 is the mobility of the M2 loan balance to the M3 loan balance; m3_m4 is the mobility of the M3 loan balance to the M4 loan balance; m4_d is the mobility of the M4 loan balance to the D loan balance; m1i is the newly increased overdue rate;
s902, calculating a long term, wherein the formula is as follows:
long term (month) = Σaccount age x recovery principal amount per account age/recovery principal amount per account age;
s903, calculating a loss rate, wherein the formula is as follows:
loss rate= (vintagem3+) -12/long term;
s904, calculating a net valence difference IRR:
the net price difference is obtained through iterative calculation, and the specific calculation method comprises the following steps:
wherein NCF (m) is net cash flow of the mth account age, and m is the account age; NCF (m) =withdrawal principal m +withdrawal interest m + collect the deposit of default m =pay-ahead principal m + advance repayment interest m Normal principal of return + m Normal interest return to + m +recovery of overdue principal m +recovery of overdue interest and penalty m + collect the deposit of default m ；
R calculated by an iterative algorithm is a month number;
net valence difference = r 12;
s905, calculating pricing yield: resetting the early compensation rate and the newly added overdue rate parameters to 0, and repeating the step S904 to calculate the pricing yield;
fifth, the offset of the positioning factor and the quantized offset value specifically include:
the net price difference formula is as follows
Net price difference = pricing rate of return-loss rate = pricing rate of return-12/lifetime vintagem3+;
factors affect the index, which affects the net price difference. For each factor, the elasticity of the factor for the net valence difference can be characterized, the elasticity = the variation ratio of the dependent variable/the variation ratio of the independent variable = (Δy/y)/(Δx/x), the elasticity of each factor for the net valence difference is calculated, and the model error and the factor offset are quantized to calibrate the model. The greater the elasticity the greater the factor importance, the higher frequency iteration or calibration can be set.
S1001, selecting a reference value of a single or multiple factors;
s1002, a factor change step is planned, step=factor reference value 1%
S1003, changing the parameter of the selected factor into a reference value plus step length, repeating the third step and the fourth step, and calculating a new net price difference;
s1004, factor elasticity= [ (new net valence difference-reference net valence difference)/reference net valence difference ]/1%.
The foregoing describes preferred embodiments of the present invention, but is not intended to limit the invention thereto. Modifications and variations to the embodiments disclosed herein may be made by those skilled in the art without departing from the scope and spirit of the invention.
Claims (10)
1. The system for accurately simulating the cash flow of the consumed financial asset is characterized by comprising an input field standardization unit, a parameter value extraction unit of simulation factors, a cash flow simulation unit of an asset life cycle, an asset quality index calculation unit and a positioning factor deviation and quantization deviation value unit; the input field standardization unit is used for obtaining standard fields according to the data of the static pool caliber input by the asset end; the parameter value extraction unit of the simulation factor is used for extracting newly increased overdue rate, mobility, absolute early compensation rate, early compensation long term, return long term, normal principal coefficient and normal interest coefficient; the cash flow simulation unit of the asset life cycle is used for calculating the following indexes for a single product: the method comprises the steps of paying principal in advance, paying interest in advance, returning normal principal balance, returning normal interest, recovering overdue principal, recovering overdue interest and fine, recovering principal, recovering interest, collecting default principal, overdue principal balance, overdue 1-30 days of loan balance, overdue 31-60 days of loan balance, overdue 61-90 days of loan balance, overdue 91-120 days of loan balance and bad account loan balance; the asset quality index calculation unit is used for calculating pricing yield, long term, loss rate and net price difference; the positioning factor offset and quantization deviation value unit is used for selecting a reference value of a single factor or a plurality of factors, drawing up a factor change step length, changing the parameter of the selected factor into the reference value plus step length, describing the sensitivity of the asset quality of the standard asset to the factor, and more accurately simulating the internal cash flow and trend change of the life cycle of the standard asset.
2. The system for accurately modeling the cash flow of a consumer financial asset of claim 1, the standard fields include deadline, payoff mode, month of payment, viewing month, amount of payment in month, weighted average execution interest, normal loan balance, M1 loan balance, M2 loan balance, M3 loan balance, M4 loan balance, M5 loan balance, M6 loan balance, M6+ loan balance, early principal of the month, interest of the month, real principal of the month, penalty of the month, normal principal of the month and overdue principal of the month.
3. The system for accurately modeling the cash flow of a consumer financial asset according to claim 1, wherein said method for extracting an newly added expiration rate comprises the steps of:
s101, obtaining a new overdue rate, wherein the formula is as follows: observing the loan balance/the current month deposit amount of the month M1;
s102, eliminating abnormal values, wherein the formula is as follows: the M1 rate is more than 5 percent or the M1 rate is less than 0 or the M1 rate is 0 between the 1 st account age and the longest account age of the asset, and then the abnormal value is removed;
s103, weighting and averaging according to account age and period number, wherein the formula is as follows: sigma month deposit amount the current month M1 rate/sigma month deposit amount.
4. The system for accurately modeling the cash flow of a consumer financial asset according to claim 1, wherein said mobility extraction method comprises the steps of:
s201, calculating mobility, wherein the formula is as follows:
mobility m1_m2=current M2 loan balance/previous M1 loan balance from M1 loan balance to M2 loan balance;
mobility of M2 to M3 loan balance m2_m3=current M3 loan balance/previous M2 loan balance;
mobility of M3 to M4 loan balance m3_m4=current M4 loan balance/previous M3 loan balance;
mobility m4_d of M4 to D loan balance = current newly added bad account loan balance/previous M4 loan balance;
s202, eliminating abnormal values, wherein the formula is as follows: mobility >1 or mobility < = 0 or mobility outside three standard deviations, then reject as outliers;
s203, weighted average according to the number of times, wherein the formula is as follows: sigma current month deposit amount. Mobility/Σcurrentmonth deposit amount.
5. The system for accurately modeling the cash flow of a consumer financial asset according to claim 1, wherein said method for extracting early compensation comprises the steps of:
s301, solving absolute early compensation rate, wherein the formula is as follows: the present money/the present money amount is paid early in the current month;
s302, eliminating abnormal values, and if the absolute early compensation rate obtained through calculation is greater than 1 or less than or equal to 0, eliminating the abnormal values;
s303, weighted average according to account age and period number, wherein the formula is as follows: sigma current month deposit amount. Early compensation rate/sigma current month deposit amount.
6. The system for accurately modeling the cash flow of a consumer financial asset according to claim 1, wherein said early-compensated long-term withdrawal method comprises the steps of:
s401, early compensation long period, wherein the formula is as follows: early compensation interest in month/(normal loan balance in early period × interest rate/act); wherein act=360 or 365;
s402, eliminating abnormal values, and if the calculated early compensation period is greater than 45, eliminating the abnormal values;
s403, weighted average according to account age and period number, wherein the formula is as follows: sigma current month deposit amount × early compensated long term/sigma current month deposit amount.
7. The system for accurately modeling the cash flow of a consumer financial asset according to claim 1, wherein said method for extracting a return-to-life comprises the steps of:
s501, calculating a catalytic recovery period X, wherein the formula is as follows:
[ m1_c x+m2_c (x+30) +m3_c (x+60) +m4_c (x+90) ] (1+ penalty floating up ratio) xinterest rate/act=current month's penalty, wherein m1_c=current M2 loan balance-upper M1 loan balance; m2—c = current M3 loan balance-last M2 loan balance; m3—c = current M4 loan balance-last M3 loan balance; m4—c = current M5 loan balance-last M4 loan balance;
s502, eliminating abnormal values, wherein if the calculated return-to-life period is more than 31 days or less than 0 days, the abnormal values are eliminated;
s503, weighted average according to account age and period number, wherein the formula is as follows: sigma current month deposit amount × the return-to-the-long term/Σcurrentmonth deposit amount.
8. The system for accurately modeling the cash flow of a consumer financial asset according to claim 1, wherein said method for extracting normal principal coefficients comprises the steps of:
s601, solving a normal principal coefficient, wherein the formula is as follows: normal repayment in month/(normal loan balance in month+normal repayment in month);
s602, eliminating abnormal values, wherein the formula is as follows: if the normal principal coefficient of account age > account age period number+1 is not equal to 0, rejecting as an abnormal value;
s603, weighted average according to account age and period number, wherein the formula is as follows: sigma current month deposit amount normal principal coefficient/sigma current month deposit amount.
9. The system for accurately modeling the cash flow of a consumer financial asset according to claim 1, wherein said normal interest coefficient extraction method comprises the steps of:
s701, solving a normal interest coefficient, wherein the formula is as follows: normal interest in the month/(normal loan balance in the month+normal repayment in the month);
s702, eliminating abnormal values, wherein for equal fees, equal information or credit card-like repayment modes, if the calculated normal interest coefficient is more than 1, the abnormal values are eliminated; for repayment modes except for equal cost, equal cost and the like or credit card, if the calculated normal interest coefficient is more than 0.03, rejecting the repayment modes as abnormal values;
s703, weighted average according to account age and period number, wherein the formula is as follows: sigma current month deposit amount normal interest factor/sigma current month deposit amount.
10. A method of accurately simulating the cash flow of a consumer financial asset by a system according to any one of claims 1 to 9, the method comprising the steps of:
first step, standardizing input fields: obtaining standard fields according to data of a static pool caliber input by a property end, wherein the standard fields comprise a deadline, a repayment mode, a repayment month, an observation month, a current month repayment amount, a weighted average execution interest rate, a normal loan balance, an M1 loan balance, an M2 loan balance, an M3 loan balance, an M4 loan balance, an M5 loan balance, an M6 loan balance, an M6+ loan balance, a current month early compensation principal, a current month early compensation interest, a current month real principal, a current month return normal principal and a current month recovery overdue principal;
extracting parameter values of simulation factors, including newly increased overdue rate, mobility, early compensation rate, early compensation long term, return long term, normal principal coefficient and normal interest coefficient;
third, simulating cash flow of the life cycle of the asset, and calculating the following indexes for a single product: advancing payoff principal, advancing payoff interest, normal principal balance, returning normal principal, returning normal interest, recovering overdue principal, recovering overdue interest, recovering principal, recovering interest, recovering surprise, collecting default principal, overdue principal balance, M1 loan balance, M2 loan balance, M3 loan balance, M4 loan balance and D loan balance;
the fourth step, calculate the quality index of the asset, include specifically:
s901, calculating a static overdue rate vintageM3+ more than 90 days after overdue, wherein the formula is as follows:
vintagem3+ =m1_m2_m2_m3_m3_m4_m4_d Σm1i, i=1, 2 … … asset periods, asset period +1; wherein M1_M2 is the mobility from the M1 loan balance to the M2 loan balance; m2_m3 is the mobility of the M2 loan balance to the M3 loan balance; m3_m4 is the mobility of the M3 loan balance to the M4 loan balance; m4_d is the mobility of the M4 loan balance to the D loan balance; m1i is the newly increased overdue rate;
s902, calculating a long term, wherein the formula is as follows:
long-term = Σaccount age x per account age recovery principal amount/Σ per account age recovery principal amount;
s903, calculating a loss rate, wherein the formula is as follows:
loss rate= (vintagem3+) -12/long term;
s904, calculating a net valence difference:
the net price difference is obtained through iterative calculation, and the specific calculation method comprises the following steps:
wherein NCF (m) is the net cash flow of the mth account age, m is the account age; NCF (m) =withdrawal principal m +withdrawal interest m + collect the deposit of default m =pay-ahead principal m + advance repayment interest m Normal principal of return + m Normal interest return to + m +recovery of overdue principal m +recovery of overdue interest and penalty m + collect the deposit of default m ；
R calculated by an iterative algorithm is a month number;
net valence difference = r 12;
s905, calculating pricing yield: resetting the early compensation rate and the newly added overdue rate to 0, and repeating the step S904 to calculate the pricing yield;
fifth step, positioning factor offset and quantization offset value:
the proposed net price difference formula is as follows:
net price difference = pricing rate of return-loss rate = pricing rate of return-12/long term vintagem3+
Factors influence the index, which influences the net price difference; for each factor, describing the elasticity of the factor on the net price difference, wherein the elasticity=the fluctuation proportion of the dependent variable/the independent variable fluctuation proportion, calculating the elasticity of each factor on the net price difference, and quantifying model errors and factor deviations so as to calibrate a model;
s1001, selecting a reference value of a single or multiple factors;
s1002, a factor change step is formulated, and the step=factor reference value is 1%;
s1003, changing the parameter of the selected factor into a reference value plus step length, repeating the third step and the fourth step, and calculating a new net price difference;
s1004, factor elasticity= [ (new net valence difference-reference net valence difference)/reference net valence difference ]/1%.
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