Rental execution scheme analysis method and device, equipment and medium

Abstract

The invention relates to the technical field of artificial intelligence and financial science and technology, and discloses a lease execution scheme analysis method, device, equipment and medium, and the method comprises the steps: obtaining the rent attribute data, and extracting the cash flow in the rent attribute data and the rent payment date corresponding to the cash flow; calculating a first cash analysis value corresponding to the cash flow according to the cash flow and the rent payment date, and determining a cash flow initial value according to the first cash analysis value; calculating a first income analysis value according to the cash flow initial value and a predetermined iterative formula; generating a constraint function according to the rent attribute data, and constraining the first income analysis value by using the constraint function to obtain a second income analysis value; and obtaining a repayment condition of the target user, and generating a lease execution scheme according to the second income analysis value, a predetermined monthly interest rate and the repayment condition. According to the invention, the efficiency of lease execution scheme formulation and execution processes can be improved.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence and financial technology, and in particular to a lease execution plan analysis method, device, equipment and medium. Background Art

[0002] In the financial leasing business, the rent quotation involved in the lease execution plan is the core content agreed upon by the lessee and the leasing company. The lease execution plan stipulates the rent payment date, period and rent amount, among which the rent includes the current principal and interest. The lessee needs to pay the leasing company the same amount of rent on the payment date agreed upon in the lease contract based on the lease execution plan.

[0003] Existing rent calculation products are usually calculated based on the lessee's financing amount, as well as the monthly interest rate and number of periods agreed upon by both parties. The calculation is then combined into a cash flow based on the lease execution plan. The cash flow includes the lessee's repayment date, the rent amount, and the amount of money received and the corresponding date. The cash flow is substituted into the XIRR (Extended Internal Rate of Return) calculation formula to calculate XIRR. However, this simple substitution of a fixed formula into the calculation method is not flexible enough, and the accuracy is difficult to meet the requirements, which often results in the calculated XIRR not matching the actual situation. Therefore, the lease execution plan has to be frequently readjusted manually, which leads to frequent changes in the lease execution plan. The formulation and execution process of the lease execution plan is inefficient, and the accuracy and flexibility are low. Summary of the invention

[0004] The present invention provides a lease execution plan analysis method, device, equipment and medium to solve the technical problems of low efficiency, low accuracy and low flexibility in the formulation and execution process of lease execution plans.

[0005] In a first aspect, a lease execution plan analysis method is provided, comprising:

[0006] Acquire rent attribute data, extract cash flow in the rent attribute data and the rent payment date corresponding to the cash flow;

[0007] Calculating a first cash analysis value corresponding to the cash flow according to the cash flow and the rent payment date, and determining an initial cash flow value according to the first cash analysis value;

[0008] Calculating a first profit analysis value according to the initial cash flow value and a predetermined iterative formula;

[0009] Generate a constraint function according to the rental attribute data, and use the constraint function to constrain the first income analysis value to obtain a second income analysis value;

[0010] The repayment conditions of the target user are obtained, and a lease execution plan is generated according to the second yield analysis value, a predetermined monthly interest rate and the repayment conditions.

[0011] In a second aspect, a lease execution plan analysis device is provided, comprising:

[0012] A rent attribute data acquisition module, used to acquire rent attribute data, extract cash flow in the rent attribute data and the rent payment date corresponding to the cash flow;

[0013] A first cash analysis value calculation module, used to calculate a first cash analysis value corresponding to the cash flow according to the cash flow and the rent payment date, and determine an initial cash flow value according to the first cash analysis value;

[0014] A first profit analysis value calculation module, used to calculate a first profit analysis value according to the initial value of the cash flow and a predetermined iterative formula;

[0015] A second income analysis value calculation module, used to generate a constraint function according to the rental attribute data, and use the constraint function to constrain the first income analysis value to obtain a second income analysis value;

[0016] The leasing execution plan generating module is used to obtain the repayment conditions of the target user and generate a leasing execution plan according to the second yield analysis value, the predetermined monthly interest rate and the repayment conditions.

[0017] In a third aspect, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned lease execution plan analysis method when executing the computer program.

[0018] In a fourth aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned lease execution plan analysis method are implemented.

[0019] The embodiment of the present invention extracts specific cash flow data from the lease contract to clearly understand the specific time and amount of rent payment; the difference between the present value of the cash flow and the initial investment is measured by the first cash analysis value to ensure that the lease contract or plan is reasonably set with the initial value from a financial perspective to avoid funding shortages or imbalances in the future; the financial health of the lease plan can be evaluated by calculating the first cash analysis value and the second yield analysis value, and the yield is optimized through the constraint function to balance risks and returns. According to the user's repayment ability and expectations, a flexible lease execution plan is formulated to ensure that the user can perform on time and the lessee can recover costs and obtain benefits. Therefore, the lease execution plan analysis method, device, equipment and medium proposed in the present invention can solve the problems of low efficiency, low accuracy and flexibility in the formulation and execution process of the lease execution plan. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0021] Figure 1 is a schematic diagram of an application environment of a lease execution scheme analysis method in an embodiment of the present invention;

[0022] Figure 2 is a flow chart of a lease execution scheme analysis method according to an embodiment of the present invention;

[0023] Figure 3 yes Figure 1 A schematic flow chart of a specific implementation of step S1;

[0024] Figure 4 yes Figure 1 A schematic flow chart of a specific implementation method of step S2;

[0025] Figure 5 is a structural schematic diagram of a lease execution scheme analysis device in one embodiment of the present invention;

[0026] Figure 6 is a schematic diagram of a structure of a computer device in one embodiment of the present invention;

[0027] Figure 7 It is another structural schematic diagram of a computer device in one embodiment of the present invention. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] The lease execution scheme analysis method provided in the embodiment of the present invention can be applied in the following aspects: Figure 1 In an application environment, the client communicates with the server through a network. The server can obtain the rental attribute data through the client, extract the cash flow in the rental attribute data and the rental payment date corresponding to the cash flow; calculate the first cash analysis value corresponding to the cash flow according to the cash flow and the rental payment date, and determine the initial value of the cash flow according to the first cash analysis value; calculate the first income analysis value according to the initial value of the cash flow and a predetermined iterative formula; generate a constraint function according to the rental attribute data, use the constraint function to constrain the first income analysis value, and obtain the second income analysis value; obtain the repayment conditions of the target user, analyze the second income analysis value, the predetermined monthly interest rate and the repayment conditions to generate a lease execution plan, and feedback the lease execution plan Back to the client, in the present invention, specific cash flow data is extracted from the lease contract to clearly understand the specific time and amount of rent payment; the difference between the present value of the cash flow and the initial investment is measured by the first cash analysis value to ensure that the lease contract or plan is reasonably set from a financial perspective and avoid shortages or imbalances in funds in the future; the financial health of the lease plan can be evaluated by calculating the first cash analysis value and the second yield analysis value, and the yield is optimized by the constraint function to balance risks and returns. According to the user's repayment ability and expectations, a flexible lease execution plan is formulated to ensure that the user can perform on time and the lessee can recover costs and obtain benefits. Therefore, the lease execution plan analysis method, device, equipment and medium proposed in the present invention can solve the problems of low efficiency, accuracy and flexibility in the formulation and execution process of the lease execution plan. Among them, the client can be but not limited to various personal computers, laptops, smart phones, tablet computers and portable wearable devices. The server can be implemented with an independent server or a server cluster composed of multiple servers. The present invention is described in detail below through specific embodiments.

[0030] See also Figure 2 As shown, Figure 2 A flowchart of a lease execution scheme analysis method provided by an embodiment of the present invention includes the following steps:

[0031] S1. Acquire rental attribute data, extract cash flow from the rental attribute data and the rental payment date corresponding to the cash flow.

[0032] In an embodiment of the present invention, the rental attribute data includes the rental amount that the lessee repays to the leasing company on each rental date, and the rental amount includes interest and principal, rental date, rental period, interest amount, principal amount, and the leasing company's unrecovered principal and cash flow.

[0033] In detail, the rental attribute data can be obtained from a pre-stored storage area through a computer statement with a data crawling function (such as a Java statement, a Python statement, etc.), where the storage area includes but is not limited to a database and a blockchain.

[0034] Furthermore, in order to conduct financial analysis, match cash flows, and optimize leasing plans, it is necessary to analyze the cash flow during the lease period. Through accurate cash flows and payment dates, both parties to the lease can evaluate future rental demand or income and thus optimize cash management.

[0035] In the embodiment of the present invention, the cash flow refers to the flow of funds within a specific time period; the rent payment date corresponding to the cash flow refers to the specific time when each cash flow occurs.

[0036] In the embodiment of the present invention, refer to Figure 3 As shown, the step of extracting the cash flow in the rent attribute data and the rent payment date corresponding to the cash flow includes:

[0037] S31, extracting down payment data, security deposit data and project total amount data from the rental attribute data;

[0038] S32, calculating the cash flow corresponding to the initial rent date according to the down payment data, the security deposit data and the project total amount data;

[0039] S33, determining the number of rent periods according to the initial rent date and the preset number of days between rent periods, and determining the rent payment date corresponding to the cash flow according to the number of rent periods;

[0040] S34. Determine the cash flow corresponding to the rent payment date according to the rent amount corresponding to the rent period number.

[0041] In detail, in the lease contract, the down payment data refers to the one-time amount paid before the lease starts; the deposit data refers to the deposit paid by the lessee at the beginning of the lease; the total project amount data refers to the total amount in the lease contract, including the total of all relevant expenses such as rent and fees. The cash flow calculation formula corresponding to the initial rent date is Cash Flow (Period 0) = Down Payment Data + Deposit Data - Total Project Amount.

[0042] Specifically, it is usually set on a monthly, quarterly, or yearly basis based on the number of days between rent payments. For example, if the rent interval is 30 days, the rent is paid every 30 days, and then starting from the initial rent date, the rent increases by the number of days between rent payments until the termination date of the lease contract. The rent payment date for each period is generated based on the number of periods and the number of days between rent payments. The cash flow (nth period) = the current rent amount, thereby determining the cash flow corresponding to each date. For example, the payment date for the first period is January 1, with a cash flow of 1,000; the payment date for the second period is February 1, with a cash flow of 1,000, and so on.

[0043] Furthermore, since future cash flows will be affected by the time value, the first cash analysis value converts future rent payments into today's value, which can help decision makers clarify the actual financial burden of paying rent at a certain point in time, thereby optimizing the rent payment structure based on the present value of cash flows to ensure that the payment plan is within the budget and can achieve financial goals.

[0044] S2. Calculate a first cash analysis value corresponding to the cash flow according to the cash flow and the rent payment date, and determine an initial cash flow value according to the first cash analysis value.

[0045] In the embodiment of the present invention, the first cash analysis value refers to the net present value, which is a financial indicator for measuring investment projects or cash flows and is used to evaluate the sum of the present values ​​of future cash flows minus the result of the initial investment.

[0046] In the embodiment of the present invention, refer to Figure 4 As shown, the first cash analysis value corresponding to the cash flow is calculated according to the cash flow and the rent payment date, including:

[0047] S41, calculating the time difference of the cash flow according to the initial rent date among the rent payment dates;

[0048] S42, discounting the cash flow corresponding to each rent payment date according to a preset discount rate and the time difference to obtain a discounted cash flow;

[0049] S43. Superimpose the discounted cash flows corresponding to all rent payment dates to obtain a first cash analysis value corresponding to the cash flows.

[0050] In detail, the time difference between the date on which each cash flow occurs and the initial rent date is determined based on the rent payment date and the cash flow corresponding to each rent payment date. If a cash flow occurs on July 1, 2024, and the initial date is January 1, 2024, then the time difference is 6 months, in order to accurately discount each cash flow, because the cash flows at different time points have different values ​​to investors.

[0051] Specifically, the first cash analysis value is calculated by the internal function npv(rate). Under the preset discount rate (rate) condition, the first cash analysis value of all cash flows is calculated, that is, for each cash flow, its present value under the given discount rate is calculated. Then Among them, CF is the cash flow amount, rate is the discount rate, t is the time difference of cash flow occurrence (in years), and the calculation formula for the time difference of each cash flow (starting from the earliest cash flow date, calculated in years) is t = (date-dates[0]).days / 365.0, and then the present values ​​of all cash flows are added together to obtain the total first cash analysis value (NPV).

[0052] Furthermore, the initial_guess attribute sets an equal value for the cash flow of each stage, which is total_repayment / num_periods (i.e., the average repayment amount of each stage). The num_stages attribute indicates the number of stages of cash flow. The optimization will adjust the cash flow of each stage. round(total_repayment / num_periods) means that the initial guess of the cash flow of each stage is the total repayment amount total_repayment evenly distributed to each stage, thereby selecting an initial guess value X based on the first cash analysis value. 0 , used for the preset XIRR (Internal Rate of Return), based on the initial value of cash flow X 0 Get the best XIRR.

[0053] S3. Calculate a first profit analysis value according to the initial cash flow value and a predetermined iterative formula.

[0054] In the embodiment of the present invention, the first yield analysis value refers to XIRR (Extended Internal Rate of Return). XIRR represents the internal rate of return under a set of non-equally spaced cash flows (i.e., cash flows occur on different dates). Different from the traditional IRR calculation method, XIRR takes into account the specific dates on which the cash flows occur, rather than assuming that the cash flows occur at equal intervals.

[0055] In the embodiment of the present invention, the calculating of the first benefit analysis value according to the initial cash flow value and a predetermined iterative formula includes:

[0056] Inputting the initial value of the cash flow into a predetermined iterative formula to obtain an updated rate of return;

[0057] Calculating the absolute difference between the updated rate of return and a preset target rate of return;

[0058] When the absolute difference is greater than or equal to the preset target accuracy, the initial cash flow value is updated to the updated rate of return, and the process returns to the step of inputting the initial cash flow value into a predetermined iterative formula to obtain an updated rate of return, until the absolute difference is less than the preset target accuracy;

[0059] When the absolute difference is less than a preset target accuracy or the function value of the objective function in the iterative formula is greater than a preset target value, the updated rate of return is used as the first rate of return analysis value.

[0060] In detail, the iterative formula is Newton's solution method, and the Newton's solution method scipy.optimize.newton is used to find the roots of the equation. Newton's method is an iterative method in numerical analysis, which is used to solve the roots of the equation. Then the iterative formula of Newton's method is X n+1 =X n -f(X n ) / f(X n ), where X n is the current estimated XIRR value, f(X n ) is at point X n The function value at n ) is at point X n The derivative (i.e. slope) at , and f(X n ) is the npv(rate) function, that is, scipy.optimize.newton(npv,0.1) is a numerical method for solving equations, used to find the roots of functions. Here it is used to solve the discount rate with a first cash analysis value of zero, that is, the internal rate of return (IRR), where npv is the first cash analysis value calculation function, which accepts a discount rate rat e As input, 0.1 is the initial guess value, indicating that the initial assumed discount rate is 10%. Then scipy.optimize.newton will try to find a discount rate that makes npv(rate) = 0, that is, a discount rate that makes the first cash analysis value zero. The final return is XIRR. Newton's method is a method of numerical optimization. By continuously adjusting the guessed discount rate, the final value that makes the first cash analysis value zero is found.

[0061] Specifically, we first define a function xirr according to the XIRR mathematical formula, then define an objective function objective, and then iterate the objective function through minimize to make the calculated_xirr value close to the preset target_xirr. If they are not close, the input parameter value of stage_cash_flows will be automatically adjusted to continue iterating until they are close. The final stage_cash_flows is the cash flow that we need to obtain to meet the specific xirr. That is, if |X n+1 -X n | Smaller than a preset precision (such as 10 -6 ), or |f(X n+1 )|Close enough to zero, stop iterating and return X n+1 as an approximate root; otherwise, set X n =X n+1 And repeat the calculation, where initial_guess is the initial value of the cash flow, which is used as the starting point of the iteration. The external function xirr(cash_flows, dates) calculates XIRR (internal rate of return) based on the given cash flow (cash_flows) and the corresponding date (dates), that is, the input cash flow list (cash_flows) and the date (dates) of the corresponding cash flow are used to calculate XIRR (internal rate of return), where the cash flow list contains the amount of all cash flows, which can be negative (indicating expenditure) or positive (indicating income), and each element represents a cash flow of a stage. The goal is to optimize these cash flows to make XIRR close to the target value, and the process_cash_flows(stage_cash_flows) function converts the staged cash flow into a complete cash flow sequence, which may include initial investment, periodic cash flow, end cash flow, etc. The date (dates) of the corresponding cash flow is usually a list of datetime type.

[0062] Furthermore, the try-except statement is used to handle the convergence problem of Newton's method. If Newton's method cannot converge, that is, it cannot find a suitable solution within the set maximum number of iterations, it will throw a RuntimeError exception. At this time, it will prompt the user "XIRR calculation did not converge" through raise ValueError. If Newton's method successfully converges, it will return the final XIRR value, even if the discount rate is zero when the first cash analysis value.

[0063] For example, assume the following cash flows and dates: cash_flows = [-1000, 200, 300, 400, 500], the initial investment is negative 1000, followed by positive cash flows, and the dates of the cash flows are dates = [datetime(2024, 1, 1), datetime(2025, 1, 1), datetime(2026, 1, 1), datetime(2027, 1, 1), datetime(2028, 1, 1)], when the xirr(cash_flows, dates) function is called, the code will use Newton's method to solve the discount rate (XIRR) so that the first cash analysis value of the cash flow sequence is zero, and then calculate the internal rate of return.

[0064] Furthermore, when generating the internal rate of return, constraints need to be met. Even if the final calculated XIRR is close to the expected XIRR, its cash flow is not in line with the actual business situation. Therefore, constraints need to be generated to constrain the calculated internal rate of return.

[0065] S4. Generate a constraint function according to the rental attribute data, and use the constraint function to constrain the first income analysis value to obtain a second income analysis value.

[0066] In the embodiment of the present invention, the constraint function includes an array of 7 custom constraint functions. The constraint function here mainly constrains the repayment ratio of the cash flow, the maximum and minimum repayments per period. For example, the repayment ratio fluctuates within 1.1 to 1.2 times, and the repayment per period cannot be a negative number.

[0067] In the embodiment of the present invention, the step of generating a constraint function according to the rent attribute data includes:

[0068] Determine the maximum and minimum values ​​of cash flow according to the rental attribute data;

[0069] Generate a first constraint condition for the cash flow according to the maximum value and the minimum value;

[0070] Generating a second constraint condition of the cash flow through a preset cash flow attribute;

[0071] The third constraint condition of the first yield analysis value is generated by obtaining the yield upper limit and the yield lower limit in advance;

[0072] The first constraint condition, the second constraint condition, and the third constraint condition are combined into a constraint function.

[0073] In detail, in the iterative solution process, the scipy.optimize.minimize function is used to perform constrained optimization using the SLSQP (Sequential Least Squares Programming) method. By optimizing a set of periodic cash flows, the actual calculated XIRR (extended internal rate of return) is close to a given target XIRR, that is, an objective function (objective) is defined. The objective function is to calculate the difference between the XIRR corresponding to the current cash flow sequence and the target XIRR (target_xirr). The return value of the objective function is the square of the XIRR error, that is, the square of the difference between the currently calculated XIRR and the target XIRR. The goal of the optimization algorithm is to minimize this value, and use constraints (cons) and boundaries (bounds) to limit the behavior of the optimization process. Finally, the scipy.optimize.minimize function will optimize according to these conditions.

[0074] Specifically, bounds sets the value range for the cash flow of each stage. The cash flow of each stage is limited between min_value and max_value. min_value and max_value are the minimum and maximum possible values ​​set for each cash flow. These values ​​ensure the reasonable range of cash flow during the optimization process and prevent the cash flow value from exceeding the actual tolerable range. The given constraints are used to limit the cash flow behavior during the optimization process. Each constraint defines a specific restriction. The first constraint is that the cash flow of each stage is not less than a minimum value and the cash flow of each stage does not exceed a maximum value. The second constraint is that the cash flow of each stage is positive, that is, there is no negative cash flow, and the stage cash flow is decreasing, that is, as time goes by, the cash flow cannot increase and the cash flow growth rate cannot exceed a certain proportion. The third constraint is to limit the calculated XIRR (extended internal rate of return) to not be lower than a lower limit and to limit the calculated XIRR (extended internal rate of return) to not be higher than an upper limit. Therefore, the constraint uses the form of {'type':'ineq','fun':...}, indicating that the constraint is an inequality constraint, and the constraint function fun must return a non-negative number to satisfy the constraint.

[0075] Furthermore, by optimizing a set of periodic cash flows, the calculated XIRR is made closest to a given target XIRR. The input of the optimization algorithm is the initial cash flow guess and constraints, and the output is the optimized cash flow sequence. The constraints include the positive and decreasing requirements of cash flows, the maximum and minimum values ​​of periodic cash flows, and the upper and lower limits related to XIRR. Finally, the optimization function `minimize` will find the optimal solution based on the objective function and constraints.

[0076] Furthermore, it is necessary to ensure that the calculated internal rate of return meets the constraints in order to obtain the best internal rate of return and make the cash flow consistent with the actual business situation.

[0077] In the embodiment of the present invention, the second profit analysis value refers to the final internal rate of return obtained after the calculated internal rate of return meets the constraint condition.

[0078] In the embodiment of the present invention, the step of constraining the first benefit analysis value by using the constraint function to obtain the second benefit analysis value includes:

[0079] Comparing the first benefit analysis value with the constraint conditions in the constraint function one by one;

[0080] When the first benefit analysis value meets the constraint condition in the constraint function, the first benefit analysis value is used to determine the second benefit analysis value.

[0081] In detail, the first benefit analysis value is compared with each constraint one by one. If the target rate of return meets all constraints, it means that the target rate of return is feasible and meets the investment requirements. If the target XIRR does not meet certain constraints, it needs to be adjusted or optimized. If the target XIRR does not meet all constraints, the target XIRR can be directly determined as the second benefit analysis value. If the target XIRR does not meet certain constraints, it may be necessary to adjust the target XIRR by adjusting the investment plan, optimizing the project structure or modifying the strategy to make it meet the constraints, thereby obtaining a new second benefit analysis value.

[0082] Furthermore, in order to calculate the monthly repayment amount or rental amount more accurately, it is necessary to generate a lease execution plan based on the repayment conditions of the target user (such as repayment period, repayment method, etc.) and combined with the second yield analysis value and the monthly interest rate to ensure that the user can repay or pay the rent on time without incurring the risk of default or overdue due to excessive repayment pressure.

[0083] S5. Obtain the repayment conditions of the target user, and generate a lease execution plan according to the second yield analysis value, a predetermined monthly interest rate and the repayment conditions.

[0084] In the embodiment of the present invention, the repayment conditions refer to those customized by the target user, such as unrecovered principal, interest amount, principal amount, rental amount, cash flow, XIRR, PMT, etc., as well as interest rate expression (whether implicit interest rate is included), rent calculation method (equal periods / unequal periods), rent calculation method (equal amounts / unequal amounts), rent repayment method (pay first / pay later), interest calculation method (monthly / daily), etc.

[0085] In detail, the repayment condition data of the target user can be obtained from a pre-stored storage area through a computer statement with a data capture function (such as a Java statement, a Python statement, etc.), where the storage area includes but is not limited to a database and a blockchain.

[0086] Furthermore, tailoring the lease execution plan based on the user's repayment conditions (such as income level, repayment expectations, etc.) can ensure that the monthly payment amount is within the user's payment ability, providing the user with a personalized, flexible and affordable repayment plan.

[0087] In an embodiment of the present invention, the lease execution plan refers to a payment arrangement or plan formulated in a lease contract based on the lease terms (such as the lease term, rent payment frequency, payment amount, etc. of the leased item or property), covering the amount that the user needs to pay during the lease period, the payment schedule, and other relevant terms to ensure that the two parties to the lease have clear agreements and perform on time.

[0088] In the embodiment of the present invention, generating a lease execution plan according to the second yield analysis value, the predetermined monthly interest rate and the repayment condition includes:

[0089] Calculate the rental payment amount based on a predetermined monthly interest rate and number of lease terms;

[0090] The rental payment amount is adjusted according to the second income analysis value to obtain a target rental amount;

[0091] Generate a cash flow sequence according to the target rental amount and the repayment conditions;

[0092] A lease execution plan is generated according to the cash flow sequence.

[0093] In detail, the user can generate a lease execution plan that meets the needs of both parties based on the expected XIRR value, monthly interest rate and other repayment conditions (such as payment in advance or in arrears, whether to accept acceptance bills, etc.), first based on the expected XIRR value, monthly interest rate, lease term, initial investment or asset value, payment method, payment in advance or in arrears, the choice of acceptance bills, and rent adjustment conditions, where the XIRR value is the target annualized internal rate of return set by the user, usually entered in the form of a percentage. For example, if the expected annualized rate of return is 6%, then XIRR = 0.06. The monthly interest rate can be derived from the annual interest rate, or directly entered by the user, monthly interest rate = annual interest Rate / 12. The lease term refers to the term of the lease in months, for example, the lease term is 24 months. The initial investment or asset value refers to the asset value or total amount at the beginning of the lease contract. The payment method refers to advance payment or post payment, and advance payment means the first rent payment of the lease term is paid at the beginning of the lease, and post payment means the first rent payment of the lease term is paid after the end of the first rent term. The choice of acceptance bill refers to whether the user accepts the use of acceptance bill to pay the rent (usually used in large transactions). If acceptance bill is selected, the rent payment will be adjusted according to the acceptance period of the bill. The rent adjustment conditions refer to whether the rent is allowed to gradually increase or decrease during the lease term.

[0094] Specifically, the monthly rent is calculated. Assuming that the rent is paid in equal installments, the rent payment amount is calculated based on the monthly interest rate and the number of lease terms. Then, based on the user's input, different processing is required to calculate the appropriate lease execution plan. After calculating and adjusting the rent, the system will generate the final lease execution plan, including: the amount of rent paid each month, the cash flow sequence during the lease term, ensuring that the XIRR matches the target XIRR, and if there is an increasing or decreasing rent, the rent change trend is listed.

[0095] For example, assuming that the conditions entered by the user are as follows: expected XIRR is 6% annualized, monthly interest rate is 0.005 (i.e., annual interest rate is 6%), lease term is 24 months, initial investment is 100,000 yuan, payment method is advance payment, and whether to accept acceptance bills is no. The rent for each period is first calculated and adjusted to ensure that the XIRR is 6% annualized. Assuming that the final calculated rent is 4,400 yuan per month, a lease execution plan is finally generated, and the amount paid for each period and cash flow are output. The lease execution plan includes the monthly rent payment amount, the cash flow sequence during the lease term, and displays the amount paid for each period (including the initial negative cash flow and subsequent rent payments), and the XIRR calculation results to ensure that it meets the target XIRR set by the user, so that a satisfactory lease execution plan can be generated based on the conditions set by the user to ensure that the expectations of both parties are met.

[0096] Furthermore, rent quotation is an important part of leasing projects. An effective quotation strategy can help maximize profits, and accurate and transparent quotations can enhance customer trust and satisfaction. At the same time, reasonable quotations meet regulatory compliance requirements and help assess and manage risks. For new account managers, they don’t know how much monthly repayments can reach XIRR for financing 1 million yuan. Usually, they need to consult account managers with quotation experience or keep trying, which will be changed. For experienced account managers, their quotations can meet the monthly interest rate and XIRR, but whether the benefits are maximized cannot be verified manually. This calculator can do this. Obviously, this will improve the efficiency of account managers, especially in complex business scenarios, such as complex repayment methods: unequal amounts + step repayment + acceptance + deposit deduction, or special financial products recurring lease renewal, etc.

[0097] It can be seen that in the above scheme, specific cash flow data is extracted from the lease contract to clearly understand the specific time and amount of rent payment; the difference between the present value of cash flow and the initial investment is measured by the first cash analysis value to ensure that the lease contract or plan is reasonably set from a financial perspective and avoid funding shortages or imbalances in the future; through the calculation of the first cash analysis value and the second yield analysis value, the financial health of the lease plan can be evaluated, and the yield is optimized through the constraint function to balance risks and returns. According to the user's repayment ability and expectations, a flexible lease execution plan is formulated to ensure that the user can perform on time and the lessee can recover costs and obtain benefits. Therefore, the lease execution plan analysis method, device, equipment and medium proposed in the present invention can solve the problems of low efficiency, low accuracy and flexibility in the formulation and execution process of the lease execution plan.

[0098] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0099] In one embodiment, a lease execution plan analysis device is provided, and the lease execution plan analysis device corresponds one-to-one to the lease execution plan analysis method in the above embodiment. Figure 5 As shown, the lease execution plan analysis device includes a rent attribute data acquisition module 101, a first cash analysis value calculation module 102, a first income analysis value calculation module 103, a second income analysis value calculation module 104 and a lease execution plan generation module 105. The functional modules are described in detail as follows:

[0100] The rent attribute data acquisition module 101 is used to acquire rent attribute data, extract the cash flow in the rent attribute data and the rent payment date corresponding to the cash flow;

[0101] A first cash analysis value calculation module 102, configured to calculate a first cash analysis value corresponding to the cash flow according to the cash flow and the rent payment date, and determine an initial cash flow value according to the first cash analysis value;

[0102] A first profit analysis value calculation module 103, used to calculate a first profit analysis value according to the initial value of the cash flow and a predetermined iterative formula;

[0103] A second benefit analysis value calculation module 104, configured to generate a constraint function according to the rental attribute data, and use the constraint function to constrain the first benefit analysis value to obtain a second benefit analysis value;

[0104] The lease execution plan generating module 105 is used to obtain the repayment conditions of the target user and generate a lease execution plan according to the second yield analysis value, the predetermined monthly interest rate and the repayment conditions.

[0105] In one embodiment, the rent attribute data acquisition module 101, when extracting the cash flow in the rent attribute data and the rent payment date corresponding to the cash flow, is used to:

[0106] Extracting down payment data, security deposit data and project total amount data from the rental attribute data;

[0107] Calculate the cash flow corresponding to the initial rent date based on the down payment data, the security deposit data and the project total amount data;

[0108] Determine the number of rent periods according to the initial rent date and the preset number of days between rent periods, and determine the rent payment date corresponding to the cash flow according to the number of rent periods;

[0109] The cash flow corresponding to the rent payment date is determined based on the rent amount corresponding to the rent period number.

[0110] In one embodiment, the first cash analysis value calculation module 102, when calculating the first cash analysis value corresponding to the cash flow according to the cash flow and the rent payment date, is used to:

[0111] Calculate the timing difference of the cash flow according to the initial rent date among the rent payment dates;

[0112] Discounting the cash flow corresponding to each rent payment date according to a preset discount rate and the time difference to obtain a discounted cash flow;

[0113] The discounted cash flows corresponding to all rent payment dates are superimposed to obtain a first cash analysis value corresponding to the cash flows.

[0114] In one embodiment, the first benefit analysis value calculation module 103, when calculating the first benefit analysis value according to the initial cash flow value and a predetermined iterative formula, is used to:

[0115] Inputting the initial value of the cash flow into a predetermined iterative formula to obtain an updated rate of return;

[0116] Calculating the absolute difference between the updated rate of return and a preset target rate of return;

[0117] When the absolute difference is greater than or equal to the preset target accuracy, the initial cash flow value is updated to the updated rate of return, and the process returns to the step of inputting the initial cash flow value into a predetermined iterative formula to obtain an updated rate of return, until the absolute difference is less than the preset target accuracy;

[0118] When the absolute difference is less than a preset target accuracy or the function value of the objective function in the iterative formula is greater than a preset target value, the updated rate of return is used as the first rate of return analysis value.

[0119] In one embodiment, the second benefit analysis value calculation module 104, when executing the generation of the constraint function according to the rent attribute data, is used to:

[0120] Determine the maximum and minimum values ​​of cash flow according to the rental attribute data;

[0121] Generate a first constraint condition for the cash flow according to the maximum value and the minimum value;

[0122] Generating a second constraint condition of the cash flow through a preset cash flow attribute;

[0123] The third constraint condition of the first yield analysis value is generated by obtaining the yield upper limit and the yield lower limit in advance;

[0124] The first constraint condition, the second constraint condition, and the third constraint condition are combined into a constraint function.

[0125] In one embodiment, the second benefit analysis value calculation module 104, when using the constraint function to constrain the first benefit analysis value to obtain the second benefit analysis value, is further configured to:

[0126] Comparing the first benefit analysis value with the constraint conditions in the constraint function one by one;

[0127] When the first benefit analysis value meets the constraint condition in the constraint function, the first benefit analysis value is used to determine the second benefit analysis value.

[0128] In one embodiment, the lease execution plan generating module 105 generates a lease execution plan according to the second yield analysis value, the predetermined monthly interest rate and the repayment condition, for:

[0129] Calculate the rental payment amount based on a predetermined monthly interest rate and number of lease terms;

[0130] The rental payment amount is adjusted according to the second income analysis value to obtain a target rental amount;

[0131] Generate a cash flow sequence according to the target rental amount and the repayment conditions;

[0132] A lease execution plan is generated according to the cash flow sequence.

[0133] The present invention provides a lease execution plan analysis device, which extracts specific cash flow data from a lease contract to clearly understand the specific time and amount of rent payment; measures the difference between the present value of cash flow and the initial investment through a first cash analysis value to ensure that the lease contract or plan is reasonably set with an initial value from a financial perspective to avoid funding shortages or imbalances in the future; through the calculation of the first cash analysis value and the second yield analysis value, the financial health of the lease plan can be evaluated, and the yield is optimized through a constraint function to balance risks and returns. According to the user's repayment ability and expectations, a flexible lease execution plan is formulated to ensure that the user can perform on time and the lessee can recover costs and obtain benefits. Therefore, the lease execution plan analysis method, device, equipment and medium proposed in the present invention can solve the problems of low efficiency, low accuracy and flexibility in the formulation and execution process of lease execution plans.

[0134] For the specific limitations of the lease execution plan analysis device, please refer to the limitations of the intelligent question and answer method above, which will not be repeated here. Each module in the above-mentioned lease execution plan analysis device can be implemented in whole or in part through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0135] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 6As shown. The computer device includes a processor, a memory, a network interface and a database connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile and / or volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external client via a network connection. When the computer program is executed by the processor, it implements the functions or steps on the service side of a lease execution solution analysis method.

[0136] In one embodiment, a computer device is provided. The computer device may be a client, and its internal structure diagram may be as follows: Figure 7 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external server through a network connection. When the computer program is executed by the processor, it implements the functions or steps of a client side of a lease execution scheme analysis method.

[0137] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0138] Acquire rent attribute data, extract cash flow in the rent attribute data and the rent payment date corresponding to the cash flow;

[0139] Calculating a first cash analysis value corresponding to the cash flow according to the cash flow and the rent payment date, and determining an initial cash flow value according to the first cash analysis value;

[0140] Calculating a first profit analysis value according to the initial cash flow value and a predetermined iterative formula;

[0141] Generate a constraint function according to the rental attribute data, and use the constraint function to constrain the first income analysis value to obtain a second income analysis value;

[0142] The repayment conditions of the target user are obtained, and a lease execution plan is generated according to the second yield analysis value, a predetermined monthly interest rate and the repayment conditions.

[0143] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0144] Acquire rent attribute data, extract cash flow in the rent attribute data and the rent payment date corresponding to the cash flow;

[0145] Calculating a first cash analysis value corresponding to the cash flow according to the cash flow and the rent payment date, and determining an initial cash flow value according to the first cash analysis value;

[0146] Calculating a first profit analysis value according to the initial cash flow value and a predetermined iterative formula;

[0147] Generate a constraint function according to the rental attribute data, and use the constraint function to constrain the first income analysis value to obtain a second income analysis value;

[0148] The repayment conditions of the target user are obtained, and a lease execution plan is generated according to the second yield analysis value, a predetermined monthly interest rate and the repayment conditions.

[0149] It should be noted that the above functions or steps that can be implemented by the computer-readable storage medium or computer device can refer to the relevant descriptions on the server side and the client side in the aforementioned method embodiment. To avoid repetition, they will not be described one by one here.

[0150] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0151] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0152] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit it. If software tools or components other than those of the company appear in the application embodiments, they are only used for illustrative purposes and do not represent actual use. Although the present invention has been described in detail with reference to the aforementioned embodiments, a person of ordinary skill in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for analyzing a lease execution plan, characterized in that: include: Acquire rent attribute data, extract cash flow in the rent attribute data and the rent payment date corresponding to the cash flow; Calculating a first cash analysis value corresponding to the cash flow according to the cash flow and the rent payment date, and determining an initial cash flow value according to the first analysis value; Calculating a first profit analysis value according to the initial cash flow value and a predetermined iterative formula; Generate a constraint function according to the rental attribute data, and use the constraint function to constrain the first income analysis value to obtain a second income analysis value; The repayment conditions of the target user are obtained, and a lease execution plan is generated according to the second yield analysis value, a predetermined monthly interest rate and the repayment conditions.

2. The lease execution plan analysis method according to claim 1, characterized in that: The step of extracting the cash flow in the rent attribute data and the rent payment date corresponding to the cash flow includes: Extracting down payment data, security deposit data and project total amount data from the rental attribute data; Calculate the cash flow corresponding to the initial rent date based on the down payment data, the security deposit data and the project total amount data; Determine the number of rent periods according to the initial rent date and the preset number of days between rent periods, and determine the rent payment date corresponding to the cash flow according to the number of rent periods; The cash flow corresponding to the rent payment date is determined based on the rent amount corresponding to the rent period number.

3. The lease execution plan analysis method according to claim 1, characterized in that: The calculating the first cash analysis value corresponding to the cash flow according to the cash flow and the rent payment date includes: Calculate the timing difference of the cash flow according to the initial rent date among the rent payment dates; Discounting the cash flow corresponding to each rent payment date according to a preset discount rate and the time difference to obtain a discounted cash flow; The discounted cash flows corresponding to all rent payment dates are superimposed to obtain a first cash analysis value corresponding to the cash flows.

4. The lease execution plan analysis method according to claim 1, characterized in that: The calculating of the first benefit analysis value according to the initial cash flow value and a predetermined iterative formula includes: Inputting the initial value of the cash flow into a predetermined iterative formula to obtain an updated rate of return; Calculating the absolute difference between the updated rate of return and a preset target rate of return; When the absolute difference is greater than or equal to the preset target accuracy, the initial cash flow value is updated to the updated rate of return, and the process returns to the step of inputting the initial cash flow value into a predetermined iterative formula to obtain an updated rate of return, until the absolute difference is less than the preset target accuracy; When the absolute difference is less than a preset target accuracy or the function value of the objective function in the iterative formula is greater than a preset target value, the updated rate of return is used as the first rate of return analysis value.

5. The lease execution plan analysis method according to claim 1, characterized in that: The step of generating a constraint function according to the rent attribute data comprises: Determine the maximum and minimum values ​​of cash flow according to the rental attribute data; Generate a first constraint condition for the cash flow according to the maximum value and the minimum value; Generating a second constraint condition of the cash flow through a preset cash flow attribute; The third constraint condition of the first yield analysis value is generated by obtaining the yield upper limit and the yield lower limit in advance; The first constraint condition, the second constraint condition, and the third constraint condition are combined into a constraint function.

6. The lease execution plan analysis method according to claim 1, characterized in that: The using the constraint function to constrain the first benefit analysis value to obtain a second benefit analysis value includes: Comparing the first benefit analysis value with the constraint conditions in the constraint function one by one; When the first benefit analysis value meets the constraint condition in the constraint function, the first benefit analysis value is used to determine the second benefit analysis value.

7. The lease execution plan analysis method according to claim 1, characterized in that: Generating a lease execution plan according to the second yield analysis value, the predetermined monthly interest rate and the repayment conditions includes: Calculate the rental payment amount based on a predetermined monthly interest rate and number of lease terms; Adjusting the rental payment amount according to the second income analysis value to obtain a target rental amount; Generate a cash flow sequence according to the target rental amount and the repayment conditions; A lease execution plan is generated according to the cash flow sequence.

8. A lease execution plan analysis device, characterized in that: include: A rent attribute data acquisition module, used to acquire rent attribute data, extract cash flow in the rent attribute data and the rent payment date corresponding to the cash flow; A first cash analysis value calculation module, used to calculate a first cash analysis value corresponding to the cash flow according to the cash flow and the rent payment date, and determine an initial cash flow value according to the first cash analysis value; A first profit analysis value calculation module, used to calculate a first profit analysis value according to the initial value of the cash flow and a predetermined iterative formula; A second income analysis value calculation module, used to generate a constraint function according to the rental attribute data, and use the constraint function to constrain the first income analysis value to obtain a second income analysis value; The leasing execution plan generating module is used to obtain the repayment conditions of the target user and generate a leasing execution plan according to the second yield analysis value, the predetermined monthly interest rate and the repayment conditions.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the lease execution plan analysis method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the lease execution plan analysis method according to any one of claims 1 to 7 are implemented.

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