Data analysis model-based unhealthy asset package valuation method and system

Abstract

The invention is suitable for the field of financial engineering, and provides a data analysis model-based unhealthy asset package valuation method and system, and the system comprises a comprehensive data collection module, a cost income analysis module, a decline trend analysis module, an asset present value analysis module, an expected value adjustment module, a potential risk identification module, and a result generation module. According to the method, the decline and disposal stages are analyzed through the life cycle, the future expected value can be adjusted in time, the asset depreciation trend is reflected, and the risk is reduced. By flexibly constructing the discount cash flow model, the discount rate can be adjusted according to market conditions, and a more accurate asset present value is provided. Finally, according to the method, evaluation results of all stages are integrated, a comprehensive asset package evaluation value report is generated, an effective management strategy is provided, and the practicability and perspectiveness of the report are enhanced. Due to the characteristics, the evaluation accuracy and decision support capability of asset life cycle analysis in the non-performing asset management are remarkably improved.

Description

Technical Field

[0001] The present invention belongs to the field of financial engineering, and in particular relates to a method and system for valuing a non-performing asset package based on a data analysis model. Background Art

[0002] The valuation of distressed asset packages in the field of financial engineering is a complex and critical process that aims to assess the value of distressed assets using mathematical models and computational techniques. It involves building quantitative models to predict future cash flows and estimate associated risks, including the probability of default and potential losses. Through the analysis of historical data and the study of market trends, financial engineers are able to dynamically adjust valuation assumptions, such as discount rates, to more accurately reflect market changes and the true value of assets. At the same time, scenario analysis is used to evaluate the performance of assets under different market conditions, helping to understand the sensitivity of their value and risk exposure. Ultimately, these analyses and models provide scientific decision support for investors and managers, enabling them to formulate reasonable investment, disposal or restructuring strategies. Overall, financial engineering provides a systematic approach to the valuation of distressed asset packages, making asset valuation more accurate and efficient.

[0003] Many traditional methods rely mainly on historical data and current financial indicators in the valuation process, lacking in-depth analysis of the dynamic changes of assets at different stages of their life cycle. The value of an asset is not only affected by the initial investment cost, but also by the combined effects of multiple factors such as operating efficiency, maintenance costs, and changes in market demand during its use. This static assessment often leads to missed potential risks and opportunities and fails to accurately reflect the actual economic status of the asset.

[0004] Therefore, traditional valuation methods, due to their reliance on static data, fail to effectively capture the dynamic changes of assets during their life cycle. In addition, the use of a fixed discount rate leads to insufficient adaptability to market changes. These defects greatly reduce their accuracy and reliability in the valuation of non-performing asset packages. Summary of the invention

[0005] The purpose of the present invention is to provide a method and system for valuing a non-performing asset package based on a data analysis model, aiming to solve the technical problems existing in the prior art identified in the background technology.

[0006] The present invention is implemented by a method for valuing a non-performing asset package based on a data analysis model, the method comprising: Collect historical data of each asset in the non-performing asset package and obtain market trend data, the historical data includes acquisition cost, maintenance cost, operating income, disposal price; the market trend data includes industry growth rate and market price fluctuation; Divide the life cycle of each asset into five stages: introduction, use, maintenance, decline and disposal, analyze the characteristics of each stage, and parse out the costs and benefits of the asset at each stage; Calculate direct and indirect costs at each stage, assess capital expenditures and operating expenses during the use stage and maintenance stage, and assess the operating income generated by the asset during the use stage, conduct trend analysis based on historical income data, and determine the income potential during the decline stage and disposal stage; Based on the revenue and cost data of each life cycle stage, a discounted cash flow model is constructed to calculate the present value of each stage. By assuming different discount rates, the impact of market conditions on the present value of assets is analyzed; In the recession phase, analyze the downward trend of asset value based on historical data and dynamically adjust future expectations; Identify potential risks at different life cycle stages and adjust recovery value forecasts based on risk assessment results; Integrate the evaluation results of each stage to generate a comprehensive asset package valuation report.

[0007] As a further solution of the present invention, the life cycle of each asset is divided into five stages: introduction, use, maintenance, decline and disposal, where: The introduction phase represents the preparation phase before the asset is put into use; The use stage refers to the stage when the asset is officially put into use and generates operating income; The maintenance phase represents the phase during which assets are regularly maintained and repaired while in use; The decline stage represents the stage where the performance of the asset begins to decline, operating returns decrease, and maintenance costs increase; The disposal stage represents the stage when an asset reaches the end of its useful life and is disposed of or sold; The above analysis shows the cost and benefit of the asset at each stage, where: Introduction phase: Analyze the asset’s purchase cost, initial training, and installation costs; Use phase: Analyze operating benefits, daily maintenance costs and resource consumption; Maintenance phase: analyze maintenance frequency, maintenance cost, failure rate and repair time; Decline stage: Analyze the downward trend of revenue, the increase in maintenance costs, and the changes in failure rates; Disposal phase: analysis of disposal costs, residual value and market value.

[0008] As a further solution of the present invention, the calculation of direct and indirect costs at each stage, the evaluation of capital expenditures and operating expenses at the use stage and the maintenance stage, and the evaluation of the operating income generated by the asset at the use stage, combined with historical income data for trend analysis, and the determination of the income potential at the decline stage and the disposal stage specifically include: Calculate the direct costs and direct benefits of each stage; By integrating the cost and benefit data of each stage, a life cycle cost-benefit analysis model is constructed, and the net present value and internal rate of return of each stage are calculated. Specifically; Calculate the industry growth rate through historical industry data, and combine it with price fluctuation trends to evaluate the potential benefits of assets in the recession stage, analyze the disposal price of assets, and predict the income that can be obtained in the disposal stage.

[0009] As a further solution of the present invention, based on the revenue and cost data of each life cycle stage, a discounted cash flow model is constructed to calculate the present value of each stage, and by assuming different discount rates, the impact of market conditions on the present value of assets is analyzed, which specifically includes: Collect historical cash flow data for each asset, including revenue and cost data at each stage, and forecast future operating income based on historical data and market trends; According to the life cycle of the asset, the cash flow data is organized into an annual schedule by timeline, and the annual schedule is divided into the introduction, use, maintenance, decline and disposal stages, while marking the start and end time of each stage; Based on changes in market conditions and risk assessment, multiple discount rates are set and the impact of changes in discount rates on present value calculations is recorded.

[0010] As a further solution of the present invention, in the recession phase, the downward trend of asset value is analyzed based on historical data to dynamically adjust the expected value in the future; Develop different scenarios, dynamically adjust the expected future value of assets based on market conditions and internal factors, and determine the expected disposal price of the assets under each scenario.

[0011] Another object of the present invention is to provide a non-performing asset package valuation system based on a data analysis model, the system comprising: A comprehensive data collection module is used to collect historical data of each asset in the non-performing asset package and obtain market trend data, wherein the historical data includes acquisition cost, maintenance cost, operating income, and disposal price; the market trend data includes industry growth rate and market price fluctuation; The cost-benefit analysis module is used to divide the life cycle of each asset into five stages: introduction, use, maintenance, decline and disposal, and analyze the characteristics of each stage to parse out the cost and benefit of the asset at each stage; The decline trend analysis module is used to calculate the direct and indirect costs of each stage, evaluate the capital expenditure and operating expenses in the use stage and the maintenance stage, and evaluate the operating income generated by the asset in the use stage, and conduct trend analysis based on historical income data to determine the income potential in the decline stage and the disposal stage; The asset present value analysis module is used to build a discounted cash flow model based on the revenue and cost data of each life cycle stage, calculate the present value of each stage, and analyze the impact of market conditions on the asset present value by assuming different discount rates; The expected value adjustment module is used to analyze the downward trend of asset value based on historical data during the recession stage and dynamically adjust the expected value in the future; Potential risk identification module, which is used to identify potential risks at different life cycle stages, including market risks, legal risks and technical risks, and adjust the recovery value forecast based on the results of risk assessment; The result generation module is used to integrate the evaluation results of each stage and generate a comprehensive asset package valuation report.

[0012] As a further solution of the present invention, the decline trend analysis module includes: The cost-benefit calculation unit is used to calculate the direct cost and direct benefit of each stage. At the same time, by integrating the cost and benefit data of each stage, a life cycle cost-benefit analysis model is constructed, and the net present value and internal rate of return of each stage are calculated; The disposal income analysis unit is used to calculate the industry growth rate through historical industry data, and combined with the price fluctuation trend, evaluate the potential benefits of assets in the recession stage, analyze the disposal price of assets, and predict the income that can be obtained in the disposal stage.

[0013] As a further solution of the present invention, the asset present value analysis module includes: A timetable arrangement unit is used to arrange the cash flow data into an annual timetable according to the life cycle of the asset, and divide the annual timetable into the stages of introduction, use, maintenance, decline and disposal, while marking the start and end time of each stage; The impact value calculation unit is used to perform discount calculations on the cash flows at each stage, set multiple discount rates based on changes in market conditions and risk assessment, and record the impact of changes in discount rates on present value calculations.

[0014] As a further solution of the present invention, the expected value adjustment module includes: The recession analysis unit is used to identify the shape and phase interval of the downward trend through an annual timetable and calculate the recession rate to obtain the average depreciation of assets during the recession phase; The disposal price analysis unit is used to develop different scenarios, dynamically adjust the expected future value of the assets based on market conditions and internal factors, and determine the expected disposal price of the assets under each scenario; The final value analysis unit is used to calculate the adjusted expected value of assets. It combines the dynamically adjusted future expected value with the historical depreciation rate to obtain the adjusted asset value at each stage.

[0015] The beneficial effects of the present invention are: This method divides assets into the stages of introduction, use, maintenance, decline and disposal, and helps decision makers identify potential problems and opportunities by deeply studying the characteristics, costs and benefits of each stage. Especially in the use and maintenance stages, this method can fully consider direct and indirect costs, ensure the accurate quantification of capital expenditures and operating expenses, and accurately determine the true economic value of assets.

[0016] In addition, life cycle analysis focuses on the decline and disposal stages, and can timely adjust future expected values ​​to reflect asset depreciation trends and reduce risks. By flexibly constructing a discounted cash flow model, the discount rate can be adjusted according to market conditions to provide a more accurate asset present value. Ultimately, this method integrates the evaluation results of each stage, generates a comprehensive asset package valuation report, proposes effective management strategies, and enhances the practicality and foresight of the report. These features enable asset life cycle analysis to significantly improve valuation accuracy and decision support capabilities in non-performing asset management. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A flowchart of a method for valuing a non-performing asset package based on a data analysis model provided by an embodiment of the present invention; Figure 2 A flowchart for calculating direct and indirect costs at each stage, evaluating capital expenditures and operating expenses at the use stage and the maintenance stage, evaluating the operating income generated by the asset at the use stage, performing trend analysis in combination with historical income data, and determining the income potential at the decline stage and the disposal stage provided by an embodiment of the present invention; Figure 3 A flowchart for constructing a discounted cash flow model based on the revenue and cost data of each life cycle stage, calculating the present value of each stage, and analyzing the impact of market conditions on the present value of assets by assuming different discount rates provided by an embodiment of the present invention; Figure 4 A flowchart of analyzing the downward trend of asset value based on historical data and dynamically adjusting future expected values ​​in a recession phase provided by an embodiment of the present invention; Figure 5 A structural block diagram of a non-performing asset package valuation system based on a data analysis model provided by an embodiment of the present invention; Figure 6A structural block diagram of a decline trend analysis module provided by an embodiment of the present invention; Figure 7 A structural block diagram of an asset present value analysis module provided in an embodiment of the present invention; Figure 8 This is a structural block diagram of an expected value adjustment module provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0019] It is understood that the terms "first", "second", etc. used in this application may be used herein to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish a first element from another element. For example, without departing from the scope of this application, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script.

[0020] Figure 1 A flowchart of a method for valuing a non-performing asset package based on a data analysis model provided by an embodiment of the present invention, such as Figure 1 As shown, the method includes: S100, collecting historical data of each asset in the non-performing asset package and obtaining market trend data, wherein the historical data includes acquisition cost, maintenance cost, operating income, and disposal price; the market trend data includes industry growth rate and market price fluctuation; By systematically collecting historical data and market trend data of assets, we ensure that the evaluation process is based on accurate and comprehensive information, reducing the deviation caused by subjective judgment. In addition, all evaluations and forecasts are based on real historical data and market trends, making the decision-making process more data-driven and improving the scientificity and reliability of decision-making. Collecting market trend data enables the model to dynamically adjust to market changes and timely reflect the impact of the external environment on asset value. By analyzing industry growth rates and market fluctuations, potential market opportunities and risks can be identified, providing a basis for subsequent risk assessment and profit forecasting. At the same time, data collection and organization in S100 provide necessary data support for subsequent life cycle analysis, cost and benefit assessment, present value calculation and other steps, ensuring the consistency and effectiveness of the entire evaluation process. Finally, through the comparative analysis of historical data and market trends, the accuracy of the valuation of non-performing asset packages can be improved, helping investors and managers make more informed decisions.

[0021] S200 divides the life cycle of each asset into five stages: introduction, use, maintenance, decline and disposal, and analyzes the characteristics of each stage to parse out the costs and benefits of the asset at each stage; in: Introduction phase: This phase includes preparations before the asset is put into use, involving analysis of procurement decisions, initial training and installation costs. At this stage, it is necessary to pay attention to the expenditure on procurement costs, after-sales services and initial training. These costs will directly affect the initial investment of the asset and the expected future returns.

[0022] Use phase: In this phase, the asset is officially put into use and begins to generate operating income. It is necessary to analyze the sources of operating income, such as product sales income, service income, etc. At the same time, daily maintenance costs and resource consumption (such as labor, electricity, etc.) must also be taken into consideration to fully evaluate the profitability and efficiency of the asset.

[0023] Maintenance phase: This phase focuses on the regular maintenance and repair of assets during use. Factors such as maintenance frequency, maintenance cost, failure rate and repair time need to be analyzed to understand the impact of maintenance on overall expenses. Frequent maintenance may increase costs and affect the net income of assets, while good maintenance can extend the life of assets and improve their performance.

[0024] Decline stage: In the decline stage, the performance of the asset begins to decline, operating income decreases, and maintenance costs increase. The analysis at this stage should focus on the trend of declining income, rising maintenance costs, and changes in failure rates, so as to evaluate the economic benefits and potential risks of the asset at this stage.

[0025] Disposal phase: This phase refers to when the asset reaches the end of its useful life and needs to be disposed of or sold. Analyzing the disposal cost, residual value, and market value is key, and an appropriate disposal strategy can maximize the asset's recovery value. In addition, the market conditions at this stage also need to be considered to determine the liquidity and potential returns of the asset in the secondary market.

[0026] The above analysis shows the cost and benefit of the asset at each stage, where: Introduction phase: Analyze the asset’s purchase cost, initial training, and installation costs; Use phase: Analyze operating benefits, daily maintenance costs and resource consumption; Maintenance phase: analyze maintenance frequency, maintenance cost, failure rate and repair time; Decline stage: Analyze the downward trend of revenue, the increase in maintenance costs, and the changes in failure rates; Disposal phase: analysis of disposal costs, residual value and market value.

[0027] By dividing the life cycle of an asset into five stages, the costs and benefits of each stage can be analyzed and evaluated in more detail, thereby fully understanding the economic characteristics of the asset. This refined analysis method not only helps to identify the special needs and challenges of different stages, but also reveals potential optimization opportunities and risks. Through in-depth analysis of each stage, decision makers can formulate more targeted management strategies and investment decisions to maximize the overall value and benefits of the asset. In addition, the segmentation of the life cycle also provides a clear framework and basis for subsequent cost calculations, benefit judgments, and risk assessments, ensuring the scientificity and accuracy of the entire valuation process. Ultimately, this systematic approach helps to improve the valuation accuracy of non-performing asset packages and provide more reliable decision support for investors and managers.

[0028] S300, calculates direct and indirect costs at each stage, evaluates capital expenditures and operating expenses during the use stage and maintenance stage, and evaluates the operating income generated by the asset during the use stage, performs trend analysis based on historical income data, and determines the income potential during the decline stage and disposal stage; like Figure 2 As shown, the direct and indirect costs of each stage are calculated, the capital expenditure and operating expenses in the use stage and the maintenance stage are evaluated, and the operating income generated by the asset in the use stage is evaluated. Trend analysis is performed in combination with historical income data to determine the income potential in the decline stage and the disposal stage, including: S310, calculate the direct costs and direct benefits of each stage; S320, calculates the industry growth rate through historical industry data, and combines price fluctuation trends to evaluate the potential returns of assets in the recession stage, analyzes the disposal price of assets, and predicts the income that can be obtained in the disposal stage; By integrating the cost and benefit data of each stage, a life cycle cost-benefit analysis model is constructed, and the net present value and internal rate of return of each stage are calculated. The specific steps are as follows: The expected cash flow is obtained through direct costs and direct benefits. The corresponding process has the following relationship: ; in, Indicates Annual revenue, Indicates The annual cost, Indicates The probability weight of the year, Indicates The expected value of the probability weight of the year, Indicates Expected cash flow for the year; Based on the discount rate, the volatility of the discount rate is obtained, and the discount factor is obtained through the discount rate and the volatility of the discount rate. The corresponding relationship in the process is: ; in, represents the discount rate, represents the volatility of the discount rate, represents a random variable with standard normal distribution, Indicates Discount factor for the year; Combining the expected cash flow and the discount factor to get the net present value, the corresponding process relationship is: ; in, represents the net present value, represents the total period; Based on the net present value, the internal rate of return is obtained, and the corresponding process has the following relationship: ; in, Represents the internal rate of return.

[0029] Furthermore, by introducing the expected value of the random variables of the standard normal distribution and the probability weight, the calculation of the net present value and the internal rate of return can better reflect the uncertainty of the market and the dynamic changes of the asset status; The calculation of direct costs includes acquisition costs, maintenance costs, and operating expenses. Acquisition costs refer to the total expenditure when purchasing an asset, including the purchase price, taxes, and transportation costs. Maintenance costs cover the cost of maintaining and repairing the asset during its use, which usually increases as the asset ages. Operating expenses include human resource costs, energy consumption, material costs, etc. in daily operations. The calculation of these direct costs provides basic data for subsequent profit analysis.

[0030] In terms of direct income, direct income is calculated by subtracting disposal income from operating income. Operating income refers to the economic benefits generated by the asset during the use phase, such as service income, sales income, etc. Disposal income is the income obtained when the asset is disposed of, which is usually directly related to the market price and asset status. By analyzing direct income, you can better evaluate the profitability of the asset.

[0031] When conducting a life cycle analysis, the industry growth rate (CAGR) should also be calculated through historical industry data, and combined with price fluctuation trends to evaluate the potential benefits of assets in the recession stage. This part of the analysis will help understand the impact of the market on assets and provide a basis for future profit forecasts. By analyzing market price fluctuations, it is possible to more accurately predict the benefits that can be obtained from assets in the disposal stage, thereby providing decision support for investors.

[0032] By fully calculating direct costs and direct benefits, we can gain a deeper understanding of the economic performance of assets at different stages of their life cycle, ensuring that decisions are based on accurate financial data. After building a life cycle cost-benefit analysis model, the calculation of net present value and internal rate of return can not only evaluate the profit potential of assets, but also provide investors with clear return expectations.

[0033] The establishment of the model allows the dynamic visualization of cash flow at different stages, providing a scientific basis for decision makers, thereby improving the transparency and reliability of investment decisions. In addition, combined with the analysis of industry growth rates and price fluctuations, it helps to identify market trends and potential risks, making asset evaluation more comprehensive and accurate. This meticulous analysis method helps to identify asset optimization opportunities and ultimately achieve effective management and value maximization of non-performing asset packages.

[0034] S400, based on the revenue and cost data of each life cycle stage, constructs a discounted cash flow model, calculates the present value of each stage, and analyzes the impact of market conditions on the present value of assets by assuming different discount rates; like Figure 3 As shown, based on the revenue and cost data of each life cycle stage, a discounted cash flow model is constructed to calculate the present value of each stage. By assuming different discount rates, the impact of market conditions on the present value of assets is analyzed, including: S410, collect historical cash flow data for each asset, including revenue and cost data at each stage, and predict future operating income based on historical data and market trends; S420, according to the life cycle of the asset, organize the cash flow data into an annual schedule by timeline, and divide the annual schedule into the introduction, use, maintenance, decline and disposal stages, and mark the start and end time of each stage; Based on the revenue and cost data of each life cycle stage, a discounted cash flow model is constructed to calculate the present value of each stage. By assuming different discount rates, the specific steps are as follows: Based on the market trend, the market volatility term is obtained in advance. By assuming different discount rates and market volatility terms, the discount factor of the cash flow is obtained. The corresponding relationship in the process is: ; in, represents the discount rate assumed based on market conditions, represents the market volatility term; represents the standard Brownian motion, Indicates Discount factor for the stage; Based on the historical cash flow data, the cash flow at the predetermined stage is obtained, and the cash flow decay rate is obtained based on the life cycle of the asset. The future cash flow is obtained through the cash flow at the predetermined period and the cash flow decay rate. The corresponding process has the following relationship: ; in, represents the decay rate of cash flow, Indicated in Cash flow at the stage represents future cash flows; The Brownian motion value is obtained based on historical cash flow data, and the expected value of the Brownian motion is obtained by the volatility of the Brownian motion value and the discount rate. The relationship between the corresponding process is: ; in, represents the expected value of the Brownian motion, represents the expected value based on the collective Brownian motion, represents the Brownian motion value, Represents the long-term average rate of cash flow growth; The present value is obtained by combining the discount factor of the comprehensive cash flow, the future cash flow and the expected value of the Brownian motion. The relationship between the corresponding process is: ; in, Indicates The present value of the stage, Indicates the total number of stages.

[0035] Furthermore, the present invention introduces geometric Brownian motion and Brownian motion process, so that the present value calculation of cash flow takes into account random growth and market fluctuations; the randomness of cash flow is simulated by geometric Brownian motion, making the cash flow forecast closer to reality, and the dynamic adjustment of the discount rate reflects the changes in market conditions, which improves the reliability of valuation; Based on changes in market conditions and risk assessment, multiple discount rates are set and the impact of changes in discount rates on present value calculations is recorded.

[0036] The main task of this step is to collect and analyze the historical cash flow data of each asset, build a discounted cash flow model, and calculate the present value of each stage. This process provides a financial basis for the accurate evaluation of the non-performing asset package and ensures the scientific nature of the decision.

[0037] First, historical cash flow data, including revenue and costs, should be collected for each asset at each stage of its life cycle. The accuracy of these data directly affects subsequent analysis and valuation. Therefore, the collection of historical cash flows should cover all relevant financial data for the introduction, use, maintenance, decline and disposal stages. Revenue data includes operating income and disposal income, while cost data covers acquisition costs, maintenance costs and operating expenses. Subsequently, the collected cash flow data is organized into an annual schedule according to the timeline, marking the start and end time of each stage. This step ensures the visualization of cash flow over time, making the financial information of different stages clearly visible, which is conducive to subsequent analysis. The annual schedule will help understand the cash flow trend of each stage and its impact on the overall asset package.

[0038] Through cash flow discounting calculation, future cash flows can be discounted to current values, thereby evaluating the actual value of cash flows at each stage at a given discount rate. In this step, multiple discount rates need to be set based on changes in market conditions and risk assessment. This is because the choice of discount rate will significantly affect the calculation results of the present value. Setting different discount rates and recording their impact on the present value calculation can help identify the optimal return on investment and risk management strategy. For example, three discount rates can be set: conservative, neutral, and optimistic, so as to evaluate the potential value of assets under different market conditions. This multi-dimensional analysis method provides decision makers with a more comprehensive perspective and helps make more robust decisions in an environment with greater uncertainty.

[0039] By combining historical cash flow data and market trends to construct a discounted cash flow model, the economic value of the asset can be accurately reflected. The calculation of present value provides investors with a clear expectation of financial returns and helps them evaluate the feasibility and security of their investment. In addition, the time series analysis of cash flows and the multiple settings of discounting enhance the adaptability and flexibility of the model. By identifying the impact of different discount rates on present value, decision makers can better understand how changes in market conditions affect the valuation of assets and make corresponding adjustments accordingly. This data-driven analysis method can effectively reduce the subjectivity of decision-making and improve the accuracy and reliability of asset valuation.

[0040] S500, in the recession phase, analyzes the downward trend of asset value based on historical data and dynamically adjusts future expected values; like Figure 4 As shown, in the recession stage, the downward trend of asset value is analyzed based on historical data, and the expected value in the future is dynamically adjusted, specifically including: S510, identifies the shape and phase interval of the downward trend through the annual timetable, and calculates the recession rate to obtain the average depreciation of assets in the recession phase; S520, develop different scenarios, dynamically adjust the expected future value of the assets based on market conditions and internal factors, and determine the expected disposal price of the assets under each scenario; S530, calculate the adjusted expected value of assets, combine the dynamically adjusted future expected value with the historical depreciation rate, and obtain the adjusted asset value at each stage: By identifying the shape and stage interval of the downward trend through the annual timetable and calculating the recession rate, we can get the average depreciation of assets in the recession stage. The corresponding relationship is: ; in, represents the average depreciation rate of assets, Indicates the number of bases. Indicates The value of assets in the year express The expected value of assets in the year Indicates The dynamic depreciation rate of the year, Indicates The random noise term of the year, Indicates a point in time, Indicates the degree of impact on the depreciation rate in the previous year. Indicates the degree of influence on the random noise term, Indicates the degree of influence on nonlinear variation terms, It indicates the speed of adjusting the nonlinear change of the asset depreciation process. Representation calculation The average depreciation rate during the period, Indicates The asset value of the year The value after depreciation of the year, The specific steps of expressing the logistic function used to capture the nonlinear changes in asset depreciation are as follows: ; in, Indicates The dynamic depreciation rate of the year, Indicates The dynamic depreciation rate of the year, Indicates The random noise term of the year, It indicates the speed of adjusting the nonlinear change of the asset depreciation process. represents the total number of cycles in the recession phase, represents the weight of the impact on the depreciation rate in the previous year, Indicates the degree of influence on the random noise term, Represents the influence weight on nonlinear change terms; The asset value corresponding to the dynamic depreciation rate is obtained through the dynamic depreciation rate. The relationship between the corresponding process is: ; in, Indicates The value of assets in the year Indicates The value of the assets in the year; Combining the asset value with the total cycle of the recession phase, we get the average depreciation rate. The relationship between the corresponding process is: ; in, Represents the average depreciation rate of an asset.

[0041] Furthermore, the present invention dynamically simulates the complex depreciation process of assets in the recession stage by introducing logical functions and random noise terms; at the same time, the logical function is used to capture nonlinear changes, making the depreciation process closer to reality, while the introduction of random noise terms increases the flexibility of the model and can better reflect the impact of market fluctuations on asset depreciation.

[0042] In the step of integrating the evaluation results of each stage and generating a comprehensive asset package valuation report, the corresponding process has the following relationship: ; in, represents the comprehensive valuation of the asset package, Indicates The net present value of the assets per year, Indicates the number of assets in the asset package. Indicates The actual rate of return on an asset, Indicates The average rate of return on assets, Indicates The standard deviation of annual asset returns, represents the discount factor for continuous time, Indicates Annual cash flow, represents a natural constant, represents pi, Indicates small changes in time. represents the standard Brownian motion, Represents the continuously discounted value of cash flows that vary over time; represents the weight factor based on normal distribution, taking into account and The difference between Indicates that the project is in The discounted value of the year.

[0043] Furthermore, the present invention improves the accuracy and detail of the comprehensive valuation of the asset package by introducing Gaussian distribution weights and a continuous cash flow discounting model; at the same time, the Gaussian distribution weights take into account the volatility of asset returns, while the continuous time discounting model more accurately reflects the value of cash flow at different time points, providing a more comprehensive valuation.

[0044] Identify the shape and phase of the downward trend through the annual timetable and analyze the performance of assets in the recession stage. It is necessary to consider a variety of factors, including market environment, policy changes, and internal management factors, which will directly affect the depreciation of assets. Through systematic data analysis, early signs of trends can be identified, thus providing early warnings to management.

[0045] Based on market conditions and internal factors, multiple scenario models are constructed to evaluate the expected future value of assets under different assumptions. The scenario model should include not only conservative expectations under the worst-case scenario, but also baseline and optimistic scenarios to ensure a comprehensive understanding of various possible market conditions. This scenario analysis can help management prepare response strategies and optimize asset disposal plans under different conditions.

[0046] The dynamic adjustment of the calculation process of the expected value of assets combines historical depreciation rates and current market data to make the forecast more accurate. This methodology introduces a real-time data feedback mechanism for asset valuation, ensuring that the valuation always reflects the latest market dynamics by continuously updating the expected value. This flexibility enables decision makers to make timely and effective decisions in a rapidly changing market environment.

[0047] Combining historical data with real-time market information can accurately identify the extent of asset depreciation during the recession phase, providing a scientific basis for future value expectations. The dynamically adjusted expected value not only takes into account the historical depreciation rate, but also combines the real-time data of the market, further improving the reliability of the assessment. In addition, by clarifying the expected disposal price under different scenarios, decision makers can better plan asset management and disposal strategies to maximize value. This systematic analysis method provides solid support for decision-making in complex market environments and helps investors make more informed choices.

[0048] S600, identifying potential risks at different life cycle stages and adjusting the recovery value forecast based on the results of the risk assessment; Effective risk management is an important part of ensuring that the valuation of non-performing asset packages is accurate and reliable. In this process, it is necessary to first systematically identify various risks, including market risk, operational risk, financial risk, and legal and compliance risk. Market risk involves market price fluctuations, industry trends, and changes in the economic environment, while operational risk focuses on potential operational errors in the asset management process, such as improper maintenance and poor management. Financial risk involves factors that affect cash flow, such as financing costs and liquidity risks, while legal and compliance risk requires examining the potential impact of changes in laws and regulations on asset disposal and value assessment.

[0049] Next, we use quantitative and qualitative analysis methods to evaluate the identified risks, clarify the impact level (such as high, medium, and low), and analyze its possible impact on revenue and cost. Based on the evaluation, we dynamically adjust the recovery value of each asset. For high-risk assets, it may be necessary to reduce their expected disposal value, while assets with lower risks can maintain or moderately increase their expected value. At the same time, we combine historical data and market trends to ensure that the forecast value is more in line with the actual situation.

[0050] In addition, we formulate countermeasures and strategies for the major risks identified, such as developing diversified investment portfolios or hedging strategies for market risks, to ensure that potential risks are always monitored during asset management and disposal so that timely adjustments can be made. By systematically identifying and evaluating potential risks, the forecast of asset recovery value is more accurate, thereby improving the reliability of the overall valuation. This in-depth risk analysis enhances management's understanding of assets and enables them to make more informed decisions in a changing market environment.

[0051] It allows for continuous monitoring and dynamic adjustment of risks, so that the management of asset packages can flexibly respond to external changes and maintain the sustainability of assets. Through comprehensive risk identification and response strategies, this step enhances transparency to investors and reduces concerns about non-performing asset packages, thereby helping to attract more investment. In addition, this step introduces a systematic risk management framework to the asset management process, making the overall management of non-performing asset packages more scientific and standardized, and providing a solid foundation for subsequent steps (such as integrating assessment results and generating reports).

[0052] S700 integrates the evaluation results of each stage to generate a comprehensive asset package valuation report.

[0053] Figure 5 The structural diagram of the bad asset package valuation system based on the data analysis model is as follows: Figure 5 As shown, the system comprises: The comprehensive data collection module 100 is used to collect historical data of each asset in the non-performing asset package and obtain market trend data, wherein the historical data includes acquisition cost, maintenance cost, operating income, and disposal price; the market trend data includes industry growth rate and market price fluctuation; The cost-benefit analysis module 200 is used to divide the life cycle of each asset into five stages: introduction, use, maintenance, decline and disposal, and analyze the characteristics of each stage to parse out the cost and benefit of the asset in each stage; The decline trend analysis module 300 is used to calculate the direct and indirect costs of each stage, evaluate the capital expenditure and operating expenses in the use stage and the maintenance stage, and evaluate the operating income generated by the asset in the use stage, and conduct trend analysis in combination with historical income data to determine the income potential in the decline stage and the disposal stage; The asset present value analysis module 400 is used to construct a discounted cash flow model based on the revenue and cost data of each life cycle stage, calculate the present value of each stage, and analyze the impact of market conditions on the asset present value by assuming different discount rates; The expected value adjustment module 500 is used to analyze the downward trend of asset value based on historical data during the recession stage and dynamically adjust the expected value in the future; Potential risk identification module 600, used to identify potential risks at different life cycle stages, including market risks, legal risks and technical risks, and adjust the recovery value forecast according to the results of risk assessment; The result generation module 700 is used to integrate the evaluation results of each stage and generate a comprehensive asset package valuation report.

[0054] like Figure 6 As shown, the decline trend analysis module 300 includes: The cost-benefit calculation unit 310 is used to calculate the direct cost and direct benefit of each stage, and at the same time, by integrating the cost and benefit data of each stage, construct a life cycle cost-benefit analysis model, and calculate the net present value and internal rate of return of each stage; The disposal income analysis unit 320 is used to calculate the industry growth rate through the industry historical data, and in combination with the price fluctuation trend, evaluate the potential income of the asset in the recession stage, analyze the disposal price of the asset, and predict the income that can be obtained in the disposal stage.

[0055] like Figure 7 As shown, the asset present value analysis module 400 includes: A timetable arrangement unit 410 is used to arrange the cash flow data into an annual timetable according to the life cycle of the asset, and divide the annual timetable into the stages of introduction, use, maintenance, decline and disposal, and mark the start and end time of each stage; The impact value calculation unit 420 is used to perform discount calculation on the cash flow of each stage, set multiple discount rates based on changes in market conditions and risk assessment, and record the impact of changes in discount rates on present value calculation.

[0056] like Figure 8 As shown, the expected value adjustment module 500 includes: The recession analysis unit 510 is used to identify the shape and phase interval of the downward trend through the annual timetable, and calculate the recession rate to obtain the average depreciation of the asset in the recession phase; a disposal price analysis unit 520 for developing different scenarios, dynamically adjusting the expected future value of the asset based on market conditions and internal factors, and determining the expected disposal price of the asset under each scenario; The final value analysis unit 530 is used to calculate the adjusted expected value of the asset, combining the dynamically adjusted future expected value with the historical depreciation rate to obtain the adjusted asset value at each stage.

[0057] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0058] 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 program can be stored in a non-volatile computer-readable storage medium. When the 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 may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (AM), synchronous AM (SAM), double data rate SAM (DSAM), enhanced SAM (ESAM), synchronous link (Synchlink) AM (SLAM), memory bus (Rambus) direct RAM (RAM), direct memory bus dynamic RAM (AM), and memory bus dynamic RAM (RAM).

[0059] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0060] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

[0061] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. The valuation method of non-performing asset package based on data analysis model is characterized by: The method comprises: Collect historical data of each asset in the non-performing asset package and obtain market trend data, the historical data includes acquisition cost, maintenance cost, operating income, disposal price; the market trend data includes industry growth rate and market price fluctuation; Divide the life cycle of each asset into five stages: introduction, use, maintenance, decline and disposal, analyze the characteristics of each stage, and parse out the costs and benefits of the asset at each stage; Calculate direct and indirect costs at each stage, assess capital expenditures and operating expenses during the use stage and maintenance stage, and assess the operating income generated by the asset during the use stage, conduct trend analysis based on historical income data, and determine the income potential during the decline stage and disposal stage; Based on the revenue and cost data of each life cycle stage, a discounted cash flow model is constructed to calculate the present value of each stage. By assuming different discount rates, the impact of market conditions on the present value of assets is analyzed; In the recession phase, analyze the downward trend of asset value based on historical data and dynamically adjust future expectations; Identify potential risks at different life cycle stages and adjust recovery value forecasts based on risk assessment results; Integrate the evaluation results of each stage to generate a comprehensive asset package valuation report.

2. The method for valuing a non-performing asset package based on a data analysis model according to claim 1, characterized in that: The life cycle of each asset is divided into five stages: introduction, use, maintenance, decline and disposal, among which: The introduction phase represents the preparation phase before the asset is put into use; The use stage refers to the stage when the asset is officially put into use and generates operating income; The maintenance phase represents the phase during which assets are regularly maintained and repaired while in use; The decline stage represents the stage where the performance of the asset begins to decline, operating returns decrease, and maintenance costs increase; The disposal stage represents the stage when an asset reaches the end of its useful life and is disposed of or sold; The above analysis shows the cost and benefit of the asset at each stage, where: Introduction phase: Analyze the asset’s purchase cost, initial training, and installation costs; Use phase: Analyze operating benefits, daily maintenance costs and resource consumption; Maintenance phase: analyze maintenance frequency, maintenance cost, failure rate and repair time; Decline stage: Analyze the downward trend of revenue, the increase in maintenance costs, and the changes in failure rates; Disposal phase: analysis of disposal costs, residual value and market value.

3. The method for valuing a non-performing asset package based on a data analysis model according to claim 2, characterized in that: The above calculation of direct and indirect costs at each stage, evaluation of capital expenditures and operating expenses during the use stage and maintenance stage, and evaluation of the operating income generated by the asset during the use stage, combined with historical income data for trend analysis, to determine the income potential during the decline stage and disposal stage, specifically including: Calculate the direct costs and direct benefits of each stage; By integrating the cost and benefit data of each stage, a life cycle cost-benefit analysis model is constructed, and the net present value and internal rate of return of each stage are calculated; Calculate the industry growth rate through historical industry data, and combine it with price fluctuation trends to evaluate the potential benefits of assets in the recession stage, analyze the disposal price of assets, and predict the income that can be obtained in the disposal stage.

4. The method for valuing a non-performing asset package based on a data analysis model according to claim 3 is characterized in that: By integrating the cost and benefit data of each stage, a life cycle cost-benefit analysis model is constructed, and the net present value and internal rate of return of each stage are calculated. The specific steps are as follows: The expected cash flow is obtained by direct costs and direct benefits. The corresponding process has the following relationship: ； in, Indicates Annual revenue, Indicates The annual cost, Indicates The probability weight of the year, Indicates The expected value of the probability weight of the year, Indicates Expected cash flow for the year; Based on the discount rate, the volatility of the discount rate is obtained, and the discount factor is obtained through the discount rate and the volatility of the discount rate. The corresponding relationship in the process is: ； in, represents the discount rate, represents the volatility of the discount rate, represents a random variable with standard normal distribution, Indicates Discount factor for the year; Combining the expected cash flow and the discount factor to get the net present value, the corresponding process relationship is: ； in, represents the net present value, represents the total period; Based on the net present value, the internal rate of return is obtained, and the corresponding process has the following relationship: ； in, Represents the internal rate of return.

5. The method for valuing a non-performing asset package based on a data analysis model according to claim 4 is characterized in that: Based on the income and cost data of each life cycle stage, a discounted cash flow model is constructed to calculate the present value of each stage. By assuming different discount rates, the impact of market conditions on the present value of assets is analyzed, including: Collect historical cash flow data for each asset, including revenue and cost data at each stage, and forecast future operating income based on historical data and market trends; According to the life cycle of the asset, the cash flow data is organized into an annual schedule by timeline, and the annual schedule is divided into the introduction, use, maintenance, decline and disposal stages, while marking the start and end time of each stage.

6. The method for valuing a non-performing asset package based on a data analysis model according to claim 5, characterized in that: Based on the revenue and cost data of each life cycle stage, a discounted cash flow model is constructed to calculate the present value of each stage. By assuming different discount rates, the specific steps are as follows: Based on the market trend, the market volatility term is obtained in advance. By assuming different discount rates and market volatility terms, the discount factor of the cash flow is obtained. The corresponding relationship in the process is: ； in, represents the discount rate assumed based on market conditions, represents the market volatility term; represents the standard Brownian motion, Indicates Discount factor for the stage; Based on the historical cash flow data, the cash flow at the predetermined stage is obtained, and the cash flow decay rate is obtained based on the life cycle of the asset. The future cash flow is obtained through the cash flow at the predetermined period and the cash flow decay rate. The corresponding process has the following relationship: ； in, represents the decay rate of cash flow, Indicated in Cash flow at the stage represents future cash flows; The Brownian motion value is obtained based on historical cash flow data, and the expected value of the Brownian motion is obtained by the volatility of the Brownian motion value and the discount rate. The relationship between the corresponding process is: ； in, represents the expected value of the Brownian motion, represents the expected value based on the collective Brownian motion, represents the Brownian motion value, Represents the long-term average rate of cash flow growth; The present value is obtained by combining the discount factor of the comprehensive cash flow, the future cash flow and the expected value of the Brownian motion. The relationship between the corresponding process is: ； in, Indicates The present value of the stage, Indicates the total number of stages.

7. The method for valuing a non-performing asset package based on a data analysis model according to claim 6, characterized in that: The above-mentioned analysis of the downward trend of asset value based on historical data during the recession stage and dynamic adjustment of future expected values ​​specifically include: Identify the shape and phases of the downward trend through an annual timeline, and calculate the recession rate to derive the average depreciation of assets during the recession phase; Develop different scenarios, dynamically adjust the expected future value of the assets based on market conditions and internal factors, and determine the expected disposal price of the assets under each scenario; Calculate the adjusted expected value of assets, combine the dynamically adjusted future expected value with the historical depreciation rate, and obtain the adjusted asset value at each stage.

8. The method for valuing a non-performing asset package based on a data analysis model according to claim 7, characterized in that: Identify the shape and phase of the downward trend through the annual timetable, calculate the recession rate, and obtain the average depreciation of assets in the recession phase. The specific steps are as follows: Get the total period of the recession phase; Based on the historical depreciation rate, the impact weight of the historical depreciation rate is obtained; The form and phase interval of the downward trend are identified through the annual timetable, and the dynamic depreciation rate is obtained by combining the impact weight of the historical depreciation rate. The specific steps are as follows: ； in, Indicates The dynamic depreciation rate of the year, Indicates The dynamic depreciation rate of the year, Indicates The random noise term of the year, It indicates the speed of adjusting the nonlinear change of the asset depreciation process. represents the total number of cycles in the recession phase, represents the weight of the impact on the depreciation rate in the previous year, Indicates the degree of influence on the random noise term, Represents the influence weight on nonlinear change terms; The asset value corresponding to the dynamic depreciation rate is obtained through the dynamic depreciation rate. The relationship between the corresponding process is: ； in, Indicates The value of assets in the year Indicates The value of the assets in the year; Combining the asset value with the total cycle of the recession phase, we get the average depreciation rate. The relationship between the corresponding process is: ； in, Represents the average depreciation rate of an asset.

9. According to the method for valuing a non-performing asset package based on a data analysis model as claimed in claim 8, in the step of integrating the evaluation results of each stage to generate a comprehensive asset package valuation report, the relationship between the corresponding process is: ； in, represents the comprehensive valuation of the asset package, Indicates The net present value of the assets per year, Indicates the number of assets in the asset package. Indicates The actual rate of return on an asset, Indicates The average rate of return on assets, Indicates The standard deviation of annual asset returns, represents the discount factor for continuous time, Indicates Annual cash flow, represents a natural constant, represents pi, Indicates small changes in time. represents standard Brownian motion.

10. The bad asset package valuation system based on the data analysis model is characterized by: The method for valuing a non-performing asset package based on a data analysis model as claimed in any one of claims 1 to 9 is applied, wherein the system comprises: A comprehensive data collection module is used to collect historical data of each asset in the non-performing asset package and obtain market trend data, wherein the historical data includes acquisition cost, maintenance cost, operating income, and disposal price; the market trend data includes industry growth rate and market price fluctuation; The cost-benefit analysis module is used to divide the life cycle of each asset into five stages: introduction, use, maintenance, decline and disposal, and analyze the characteristics of each stage to parse out the cost and benefit of the asset at each stage; The decline trend analysis module is used to calculate the direct and indirect costs of each stage, evaluate the capital expenditure and operating expenses in the use stage and the maintenance stage, and evaluate the operating income generated by the asset in the use stage, and conduct trend analysis based on historical income data to determine the income potential in the decline stage and the disposal stage; The asset present value analysis module is used to build a discounted cash flow model based on the revenue and cost data of each life cycle stage, calculate the present value of each stage, and analyze the impact of market conditions on the asset present value by assuming different discount rates; The expected value adjustment module is used to analyze the downward trend of asset value based on historical data during the recession stage and dynamically adjust the expected value in the future; Potential risk identification module, which is used to identify potential risks at different life cycle stages, including market risks, legal risks and technical risks, and adjust the recovery value forecast based on the results of risk assessment; The result generation module is used to integrate the evaluation results of each stage and generate a comprehensive asset package valuation report.

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