Logistics deposit pricing method based on intelligent risk assessment

Abstract

The invention belongs to the technical field of logistics platforms, and relates to a logistics guarantee deposit pricing method based on intelligent risk assessment, which comprises the steps of introducing a weighted risk assessment model to assess a risk level, introducing a business basic guarantee deposit calculation model to support a pricing interval of guarantee deposit, determining an appropriate overall risk coefficient according to the risk level, and calculating the risk level according to the overall risk coefficient. And finally, combining the overall risk coefficient with a business basic guarantee deposit calculation model, thereby matching a proper pricing guarantee deposit. The evaluation of the weighted risk evaluation model comprehensively considers each risk factor, and identifies and determines key factors affecting the transportation risk. The key factors of the transportation risk comprise the cargo value, the transportation distance, the cargo quantity, the transportation mode risk coefficient and the driver reputation, and the weighted risk assessment model performs analysis by taking the key factors as evaluation indexes and finally assesses the transportation risk. According to the invention, through analysis of logistics transaction data, the actual risk level of the transaction can be accurately assessed, and personalized requirements of deposit setting are met.

Description

Technical Field

[0001] The present invention belongs to the technical field of logistics platforms, and specifically relates to a logistics deposit pricing method based on intelligent risk assessment. Background Art

[0002] In the modern logistics industry, as transactions become increasingly frequent and complex, logistics platforms generally require the transaction parties to provide a certain amount of deposit before the completion of logistics transactions to cope with the risk of transaction failure. However, since logistics transactions involve many influencing factors, such as the amount of goods, transportation distance, and driver credibility, many of which the platform can only evaluate through past historical data and cannot obtain accurate data, how to scientifically, reasonably, and efficiently set logistics deposits has become a common concern within and outside the industry. Summary of the invention

[0003] The purpose of the present invention is to provide a logistics deposit pricing method based on intelligent risk assessment, which is used to solve the technical problem that it is difficult for the existing technology to correctly assess the risks of logistics transactions based on multiple influencing factors, especially the influencing factors that cannot be directly collected or calculated affect the platform's assessment of logistics transaction risks, resulting in the platform being unable to set logistics deposits scientifically, reasonably and efficiently.

[0004] The logistics deposit pricing method based on intelligent risk assessment includes: introducing a weighted risk assessment model to assess the risk level, introducing a business-based deposit calculation model to support the deposit pricing range, determining a suitable overall risk coefficient according to the risk level, and finally combining the overall risk coefficient with the business-based deposit calculation model to match a suitable pricing deposit.

[0005] The weighted risk assessment model comprehensively considers various risk factors, identifies and determines the key factors that affect transportation risks. The key factors of transportation risk include: cargo value, transportation distance, cargo quantity, transportation mode risk factor, and driver reputation. The weighted risk assessment model uses the above key factors as evaluation indicators to analyze and ultimately assess transportation risks.

[0006] Preferably, the risk assessment model uses a weighted sum algorithm to calculate the risk score, and the specific calculation formula is as follows: RiskScore = W V ×V+W D ×D+W Q ×Q+W R ×R+W C ×C,

[0007] Among them, V represents the value of the goods, D represents the transportation distance, Q represents the quantity of goods, R represents the risk factor of the transportation method, C represents the reputation of the driver, RiskScore represents the risk score, and W represents the risk factor of the transportation method. V, W D , W Q , W R , W C The corresponding weights represent the key factors such as cargo value, transportation distance, cargo quantity, transportation method risk coefficient and driver reputation. After calculating the risk score, the risk level is divided and the risk level is set according to the threshold range of the risk score.

[0008] Preferably, the business basic deposit calculation model uses the following formula to calculate the pricing range: Deposit = β 0 +β 1 ×GoodsValue+β 2 ×CompetitionIndex+β 3 ×MarketDemandIndex, where GoodsValue represents the value of goods, CompetitionIndex represents the competition index, which is a dimensionless value; MarketDemandIndex represents the market demand index, which is also a dimensionless value. The market demand index is calculated based on factors such as industry growth rate and market demand; β 0 represents the constant term, β 1 , β 2 and β 3 The coefficients represent the value of goods, competition index and market demand index respectively; historical data is collected for relevant data involved in the business basic deposit calculation model, and regression analysis is performed based on these historical data to determine the coefficients of the value of goods, competition index and market demand index as well as the constant term.

[0009] Preferably, the overall risk coefficient is set according to the risk level obtained from the previous assessment. The risk adjustment factor is set based on the overall risk coefficient to adjust the business basic deposit calculation model. After the risk adjustment factor RiskAdjustmentFactor is introduced into the business basic deposit calculation model, a new deposit calculation formula is obtained:

[0010] Based on the above adjusted deposit calculation formula, this method obtains the deposit amount under different circumstances through simulation or actual calculation; then, according to business needs and market practices, the deposit range corresponding to different risk levels is set.

[0011] Preferably, the evaluation steps of the weighted risk assessment model are as follows.

[0012] S1.1. Assess the risk factor of the mode of transportation.

[0013] S1.2. Evaluate the driver's reputation.

[0014] S1.3. Collect and calculate cargo value, transportation distance and cargo quantity.

[0015] S1.4. Use a weighted approach to construct a risk assessment model and assign reasonable weights to several key factors that affect transportation risks.

[0016] S1.5. Use the risk assessment model to calculate the risk score and classify the risk level.

[0017] The cargo value and the driver's reputation are assigned high weights, the cargo quantity is assigned low weights, the weight of the transportation distance is between high weights and low weights, and the weight assigned to the transportation mode risk coefficient is determined according to the specific transportation mode.

[0018] Preferably, the method for evaluating the risk factor of a transportation mode includes:

[0019] S1.1.1. Historical data analysis: By analyzing the historical data of different modes of transportation, including accident rates and delay rates, we can understand the risk performance of various modes of transportation.

[0020] S1.1.2. Collect and evaluate real-time information. Collect real-time information such as weather forecasts and traffic conditions and use it to assess the impact of the factors involved on the risk of transportation modes.

[0021] S1.1.3. Expert opinion survey: evaluate the risk factor of the mode of transport based on the professional insights and judgments on the risks of the mode of transport provided by experts.

[0022] S1.1.4. Calculate the transport mode risk factor R = ∑(W i ×X i ), where R represents the risk factor, which is a numerical value used to quantify the degree of risk; X i represents the value or score of the ith risk factor; W i The weight of the ith risk factor reflects the importance of the risk factor in the overall risk. The weight of each risk factor is determined based on expert opinions, historical data or statistical methods, and the sum of all weights should be 1, that is, ∑W i =1.

[0023] Preferably, the specific method for determining the weight Wi in step S1.1.4 includes: 1) preliminarily determining the relative weight according to the degree of influence of the risk factor on the risk; 2) collecting data on the risk factor through expert evaluation, questionnaire survey, and historical data analysis; 3) scoring or assigning a value to each risk factor based on the collected data to represent its basic weight; 4) normalizing the basic weight to unify all weights to a unified scale; 5) in practical applications, the weight Wi needs to be dynamically adjusted according to the specific situation; the value or score X of the i-th risk factor in step S1.1.4 i The specific determination methods include: 1) Direct numerical method: directly use numerical values ​​to measure risk factors; 2) Rating or scoring method: formulate clear scoring standards and guidelines, and rate or score risk factors through expert evaluation or questionnaire survey; 3) Historical data analysis method: determine the value of risk factors by analyzing historical data; 4) Fuzzy evaluation method: use fuzzy evaluation method based on fuzzy mathematics theory to determine the value of risk factors.

[0024] Preferably, when evaluating the reputation of a driver, the various dimensional indicators that affect the reputation of the driver are sorted and analyzed, and appropriate weights are assigned to the indicators based on their importance. The scores of each dimension are added together to obtain the total reputation score of the driver, which is calculated as follows: Total Score = ∑ (Base-Score i ×Weight i ), where i represents different dimensions, Weight i Indicates the weight of the i-th dimension, Base-Score i It represents the basic score of the i-th dimension; the score of each dimension is obtained by deducting points from the basic score according to the deduction items; the weight setting is adjusted according to the actual situation to reflect the importance of different dimensions to the driver's reputation; the basic score and deduction items are set according to specific needs.

[0025] Preferably, specific steps for evaluating the driver's reputation include:

[0026] S1.2.1. Evaluate historical records, including on-time rate, cargo damage rate and accident records.

[0027] S1.2.2. Evaluate customer feedback. Customer feedback includes customer ratings and text reviews. Text reviews analyze the keywords related to the evaluation in customer reviews and assign corresponding scores to the keywords.

[0028] S1.2.3. Real-time monitoring and scoring. Real-time monitoring includes monitoring driving behavior, setting deduction items according to the driving behavior data recorded by the on-board equipment, and scoring based on the monitoring results of driving behavior.

[0029] S1.2.4. Evaluate the completeness of the credentials, which includes the type of credentials, the validity of the credentials, and the timeliness of the credentials’ updates.

[0030] S1.2.5. Calculate the evaluation score according to the driver's total credit score formula.

[0031] The present invention has the following advantages: 1. The prior art lacks the application of intelligent risk assessment technology, so that deposit pricing is often based on fixed standards or simple empirical judgments; while this method introduces intelligent risk assessment technology, and through the analysis of logistics transaction data, it can accurately assess the actual risk level of the transaction.

[0032] 2. Existing technologies ignore personalized needs. Different users, different types of goods, different transportation conditions and other factors may affect the risks of logistics transactions, and the logistics deposit pricing method in existing technologies often adopts a one-size-fits-all approach; while this method monitors the changes in risks during the transaction process in real time, dynamically adjusts the deposit amount, and ensures that the deposit and transaction risks maintain a dynamic balance. This intelligent pricing method improves the accuracy and flexibility of deposit pricing, and can therefore adapt to the personalized needs of deposit setting.

[0033] 3. The lack of transparency in deposit setting by existing technologies makes it difficult for consumers to understand the basis behind deposit pricing, leading to doubts about the rationality and necessity of the deposit amount; this method can show consumers information such as the results of intelligent risk assessment, the basis for personalized pricing, and the reasons for deposit adjustment, so that consumers can have a full understanding and cognition of their deposit amount, understand the basis and logic behind deposit pricing, and improve the transparency of deposit pricing. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 The figure is a basic flow chart of a logistics deposit pricing method based on intelligent risk assessment of the present invention.

[0035] Figure 2 This is a flow chart of the operation of a logistics deposit pricing method based on intelligent risk assessment in the system of the present invention. DETAILED DESCRIPTION

[0036] The specific implementation modes of the present invention are further explained in detail below by describing the embodiments with reference to the accompanying drawings, so as to help those skilled in the art to have a more complete, accurate and in-depth understanding of the inventive concept and technical solution of the present invention.

[0037] like Figure 1 , Figure 2As shown, the present invention provides a logistics deposit pricing method based on intelligent risk assessment, including: introducing a weighted risk assessment model to assess the risk level, introducing a business-based deposit calculation model to support the deposit pricing range, determining a suitable overall risk coefficient according to the risk level, and finally combining the overall risk coefficient with the business-based deposit calculation model to match a suitable pricing deposit.

[0038] The logistics deposit pricing method specifically includes the following steps.

[0039] S1. Construct a weighted risk assessment model to assess transportation risks.

[0040] The evaluation steps and methods of the weighted risk assessment model focus on comprehensive consideration of various risk factors, identifying and determining the key factors that affect transportation risks. The key factors of transportation risk include: cargo value (V), transportation distance (D), cargo quantity (Q), transportation mode risk factor (R), driver reputation (C), etc. Therefore, the weighted risk assessment model uses the above key factors as evaluation indicators to analyze and ultimately evaluate the transportation risk. Therefore, this step uses different methods to evaluate different evaluation indicators, as follows.

[0041] S1.1. Assess the risk factor (R) of the mode of transport.

[0042] The assessment of the risk factor (R) of a transport mode is a comprehensive assessment process that requires consideration of multiple factors, including the following sub-steps.

[0043] S1.1.1. Historical data analysis.

[0044] By analyzing historical data such as accident rates and delay rates of different modes of transportation over a period of time, we can understand the risk performance of various modes of transportation.

[0045] S1.1.2. Collect real-time information and conduct evaluation.

[0046] Real-time information, such as weather forecasts and traffic conditions, is crucial for assessing transportation risks within a specific time period. In the case of bad weather or traffic congestion, the risk of certain modes of transportation may increase significantly. This step collects real-time information such as weather forecasts and traffic conditions and uses it to assess the impact of the factors involved on the risk of transportation modes.

[0047] S1.1.3. Expert opinion survey.

[0048] Experts in the fields of logistics, transportation and risk management are invited to participate in the process of identifying the possible risks of various modes of transportation through expert discussions and opinion surveys. Expert opinions can provide professional insights and judgments on the risks of transportation modes, which will help to more accurately assess the risk factors of transportation modes.

[0049] S1.1.4. Based on the analysis results of steps S1.1.1 to S1.1.3, calculate the transport mode risk factor R = ∑(W i ×X i ), where R represents the risk factor, which is a numerical value used to quantify the degree of risk; X i represents the value or score of the ith risk factor; W i The weight of the ith risk factor reflects the importance of the risk factor in the overall risk. The weight of each risk factor is determined based on expert opinions, historical data or statistical methods, and the sum of all weights should be 1, that is, ∑W i =1.

[0050] The determination of the weight Wi of the ith risk factor is an evaluation process based on the importance and impact of the risk factor. Data is collected through methods such as questionnaires, and then the basic weight is calculated and normalized to finally obtain the specific weight value of each risk factor.

[0051] The specific methods for determining the weights include:

[0052] 1) Different risk factors have different impacts on the overall risk. Some factors have a decisive impact on the risk, while others only play a minor role. Therefore, it is necessary to evaluate the importance of each risk factor to preliminarily determine its relative weight in the overall risk assessment. The relative weight focuses on the relative size relationship between the weights of different risk factors.

[0053] 2) To determine the weights, first collect data on risk factors through expert evaluation, questionnaire surveys, historical data analysis, etc. The data collection process aims to obtain information about the importance, impact and relative relationship of risk factors, so the authenticity and reliability of the data must be ensured in the process.

[0054] 3) Based on the collected data, score or assign a value to each risk factor to indicate its basic weight. This scoring or assignment can be done based on one of the following methods, including expert judgment, statistical results of historical data, or other appropriate criteria.

[0055] 4) Since different risk factors have different scores or value ranges, these basic weights need to be normalized for comparison and combination. The purpose of normalization is to adjust all weights to a unified scale so that they can be compared and weighted.

[0056] 5) In practical applications, the weight Wi needs to be adjusted dynamically according to the specific situation. Therefore, as the business environment changes or new risk factors emerge, the weight needs to be re-evaluated and adjusted.

[0057] In summary, the calculation of Wi is an assessment process based on the importance and impact of risk factors, aiming to determine the relative weight of each risk factor in the overall risk assessment.

[0058] Xi is the specific value, grade or score corresponding to the ith risk factor. It is usually a key step in risk assessment to quantify risk factors. Its calculation method depends on the characteristics of the risk factor and the type of available data. The following are some common methods for calculating the ith risk factor Xi.

[0059] 1) Direct numerical method: If the risk factors can be directly measured by numerical values, such as the value of the goods, the transportation distance, the weight of the goods, etc., then these numerical values ​​can be directly used as the value of Xi.

[0060] 2) Rating or scoring method: When risk factors cannot be directly measured numerically, a rating or scoring method can be used. Risk factors are rated (e.g., 1-5) or scored (e.g., 1-10) through expert evaluation or questionnaire survey. In the rating or scoring process, it may be necessary to establish clear scoring criteria and guidelines to ensure consistency and accuracy of the scoring.

[0061] 3) Historical data analysis method: If relevant historical data exists, the value of Xi can be determined by analyzing the historical data. The risk factor data of similar events in the past can be analyzed, and the risk factor value of the current event can be estimated based on these data. Statistical analysis methods can be used to process historical data to obtain more representative risk factor values.

[0062] 4) Fuzzy evaluation method: For some fuzzy and difficult to accurately quantify risk factors, fuzzy evaluation method can be used to calculate Xi. This method usually involves dividing risk factors into different fuzzy sets (such as "low", "medium", "high" risk, etc.) and determining the risk factor value based on fuzzy mathematical theory.

[0063] S1.2. Evaluate driver's reputation (C).

[0064] When making an overall score for the driver's reputation (C), this step uses the weighted average method. By sorting out and analyzing the various dimensional indicators that affect the driver's reputation, appropriate weights are assigned to the indicators based on their importance, and the scores of each dimension are added together to obtain the driver's total reputation score.

[0065] This step analyzes the components of the driver's credit score, and the components of the driver's credit score include the following parts.

[0066] Safety: including the driver's driving record, accident record, etc., which are important indicators for evaluating its safety.

[0067] Service quality: This includes passengers’ evaluation of the driver’s service attitude, punctuality, communication skills, etc. This type of evaluation is also an important part of the credit score.

[0068] Compliance: This includes aspects such as the completeness of the driver’s credentials and compliance with traffic rules, which can also be used as a basis for evaluating their compliance.

[0069] Specifically, this step includes the following sub-steps.

[0070] S1.2.1. Assessment history.

[0071] The history records include the following information.

[0072] Punctuality rate: records the ratio of the number of times a driver arrives at the destination within a specified time to the total number of times.

[0073] Cargo damage rate: the ratio of the number of times the cargo is damaged during transportation to the total number of times.

[0074] Accident log: records the number and severity of accidents a driver has had

[0075] S1.2.2. Evaluate customer feedback.

[0076] Customer feedback includes the following information.

[0077] Customer ratings: Collect customer ratings of drivers. Ratings can be set from 1 to 5 points.

[0078] Text reviews: Analyze customer reviews for evaluation-related keywords, such as "friendly" and "professional", and assign corresponding scores to them.

[0079] S1.2.3. Real-time monitoring and scoring.

[0080] Real-time monitoring includes the following information.

[0081] Monitor driving behavior: Set deduction items based on driving behavior data recorded by on-board equipment, such as speeding, sudden braking, etc., and calculate points based on the monitoring results of driving behavior.

[0082] S1.2.4. Evaluate the completeness of the documents.

[0083] The completeness of the certificate includes the following information.

[0084] Type of certificate: Score based on the type and number of certificates the driver holds, such as driver's license, professional qualification certificate, etc.

[0085] Validity of certificate: Check whether the certificate is within the validity period. Points will be deducted for expired certificates.

[0086] Timeliness of document updating: For documents that need to be updated regularly, such as annual inspections, insurance, etc., timely updates will add points, and failure to update after the expiration date will deduct points.

[0087] S1.2.5. Calculate the evaluation score.

[0088] Score calculation: Each dimension has a base score and a corresponding weight. The formula for calculating the driver's total credit score is as follows:

[0089] Total Score = ∑ (Base-Score i ×Weight i )

[0090] Among them, i represents different dimensions, Weight i Indicates the weight of the i-th dimension, Base-Score i Indicates the basic score of the i-th dimension. The following example illustrates how to calculate the corresponding score for a specific dimension.

[0091] Punctuality: The base score is 100 points, and the weight is 0.15. Assuming that the driver arrives on time 95 times out of 100 deliveries, the score is 100×0.15×(95 / 100)=14.25 (rounded to 14).

[0092] Cargo damage rate: The basic score is 100 points, and the weight is 0.1. Assuming that the driver has 1 damaged cargo in 100 transports, the score is 100×0.1×(99 / 100)=9.9 (rounded to 10).

[0093] Customer rating: The basic score is 100 points, and the weight is 0.2. Assuming the average rating is 4.5 (full score is 5), the score is 100×0.2×(4.5 / 5)=18.

[0094] Certificate completeness: The basic score is 100 points, with a weight of 0.25. Scoring is based on the type, validity, and timeliness of updating of the certificate, assuming the score is 85.

[0095] Real-time monitoring: The basic score is 100 points, with a weight of 0.3. Based on the driving behavior data, if the driver performs well, the score is 100 × 0.3 = 30; if there is bad behavior, points will be deducted accordingly.

[0096] Add up the scores of the above dimensions to get the driver's total credit score, which is 14+10+18+85+30=157.

[0097] In the above content, the weight setting is adjusted according to the actual situation to reflect the importance of different dimensions to the driver's reputation. The basic score and deduction items are set according to specific needs to ensure the fairness and accuracy of the score. After completing the above settings, the system is also regularly updated and maintained during use to reflect changes in driver reputation and the addition of new data. The specific scoring criteria for the completeness of the certificate need to be formulated according to the actual situation to ensure that it can reflect the degree of completeness of the certificate and ensure the objectivity and fairness of the score.

[0098] S1.3. Collect and calculate cargo value (V), transportation distance (D) and cargo quantity (Q).

[0099] The value of goods (V), transportation distance (D) and quantity of goods (Q) can generally be directly calculated or obtained based on logistics information.

[0100] S1.4. Use a weighted approach to build a risk assessment model and assign reasonable weights to several key factors that affect transportation risks. The details are as follows.

[0101] 1) Cargo value (V): Cargo value is usually directly related to potential losses, so its weight is relatively high; in this embodiment, a weight of not less than 0.2 is assigned to the cargo value (V).

[0102] 2) Transportation distance (D): The longer the transportation distance, the higher the uncertainty and risk that may be faced during transportation. Therefore, its weight is also higher, but lower than the value of the goods. In this embodiment, a weight of 0.15 to 0.2 is assigned to the transportation distance (D).

[0103] 3) Cargo quantity (Q): The impact of cargo quantity on risk is small, because the cargo quantity is more related to the amount of loss rather than the probability of risk. However, in some cases (such as fragile or high-value goods), the cargo quantity can also have a significant impact on risk. Therefore, this example assigns a weight of 0.1 to the cargo quantity (Q).

[0104] 4) Transport mode risk coefficient (R): Different transport modes have different risk characteristics. Air transport may be faster but more expensive and riskier (such as weather impact), while sea transport may be slower but less expensive and riskier. Therefore, the weight of the transport mode risk coefficient should be allocated according to the specific needs of logistics. This embodiment allocates a weight of 0.15 to 0.25 to the transport mode risk coefficient (R).

[0105] 5) Driver reputation (C): Driver reputation has an important impact on transportation risk because the driver's driving skills, experience, attitude and compliance may affect transportation safety. Therefore, the weight of driver reputation is also relatively high. In this embodiment, a weight of 0.2 to 0.25 is assigned to driver reputation (C).

[0106] In general, the value of the goods and the reputation of the driver are assigned high weights, the quantity of the goods is assigned low weights, the weight of the transportation distance is between high and low weights, and the weight assigned to the transportation mode risk coefficient is determined according to the specific transportation mode.

[0107] S1.5. Use the risk assessment model to calculate the risk score and classify the risk level.

[0108] The risk assessment model uses a weighted sum algorithm to calculate the risk score. The specific calculation formula is as follows: RiskScore = W V ×V+W D ×D+W Q ×Q+W R ×R+W C ×C,

[0109] Among them, V represents the value of the goods, D represents the transportation distance, Q represents the quantity of goods, R represents the risk factor of the transportation method, C represents the reputation of the driver, RiskScore represents the risk score, and W represents the risk factor of the transportation method. V , W D , W Q , W R , W C They correspond in turn to the weights of key factors such as cargo value, transportation distance, cargo quantity, transportation method risk factor and driver reputation.

[0110] After calculating the risk score, the risk level is divided and the risk level (such as low, medium, and high) is set according to the threshold range of the risk score. In this embodiment, the following three risk levels are set: RiskScore≤30 is low risk, 30<RiskScore≤70 is medium risk, and 70<RiskScore is high risk.

[0111] S2. Build a business-based deposit calculation model to support the deposit pricing range.

[0112] The business basic deposit calculation model uses the following formula to calculate the pricing range: Deposit = β 0 +β 1 ×GoodsValue+β 2 ×CompetitionIndex+β 3 ×MarketDemandIndex, GoodsValue represents the value of goods, in RMB, CompetitionIndex represents the competition index, which is a dimensionless value; MarketDemandIndex represents the market demand index, which is also a dimensionless value. The market demand index is calculated based on factors such as industry growth rate and market demand; β 0 represents the constant term, β 1 , β 2 and β 3 The coefficients representing the value of goods, the competition index and the market demand index respectively.

[0113] Collect historical data related to the business basic deposit calculation model, and perform regression analysis based on these historical data to determine the coefficients and constant terms of the goods value, competition index and market demand index. Specifically, this step uses the deposit amount, goods value, competition index and market demand index collected or calculated from the historical transaction data as samples, and fits the values ​​of these coefficients through methods such as the least squares method.

[0114] S3. Determine the appropriate overall risk factor based on the risk level, and finally combine the overall risk factor with the business-based deposit calculation model to match the appropriate pricing deposit.

[0115] The business basic deposit calculation model does not take into account the overall risk factor, so this step introduces a risk adjustment factor (Risk Adjustment Factor) into the business basic deposit calculation model to obtain a new deposit calculation formula:

[0116] Deposit = β 0 +β 1 ×GoodsValue×RiskAdjustmentFactor

[0117] +β 2 ×CompetitionIndex+β 3 ×MarketDemandIndex

[0118] Among them, RiskAdjustmentFactor is the risk adjustment factor. So far, this step has completed the risk deposit setting model. The risk adjustment factor is adjusted based on the overall risk coefficient. The overall risk coefficient is set according to the risk level obtained by the previous assessment. In this embodiment, it is specifically: the overall risk coefficient corresponding to low risk is 0.5, the overall risk coefficient corresponding to medium risk is 1.0, and the overall risk coefficient corresponding to high risk is 1.5. These overall risk coefficient values ​​can also be adjusted according to actual conditions. In this embodiment, the risk adjustment factor is the same as the overall risk coefficient. In some more complex cases, the corresponding risk adjustment factor can also be calculated based on the overall risk coefficient through a more complex calculation method.

[0119] The risk deposit setting model is used to evaluate the reasonable deposit setting. Based on the above adjusted deposit calculation formula, this method obtains the deposit amount in different situations through simulation or actual calculation. Then, according to business needs and market practices, the deposit range corresponding to different risk levels is set. For example: at a low risk level, the deposit amount is between 10% and 20% of the value of the goods; at a medium risk level, the deposit amount is between 20% and 35% of the value of the goods; at a high risk level, the deposit amount exceeds 35% of the value of the goods. These intervals are adjusted according to actual conditions, and it is necessary to ensure that they are coordinated with the adjusted deposit calculation formula.

[0120] The present invention is described above by way of example in conjunction with the accompanying drawings. It is obvious that the specific implementation of the present invention is not limited to the above-mentioned method. As long as various non-substantial improvements are made using the inventive concept and technical solution of the present invention, or the inventive concept and technical solution are directly applied to other occasions without improvement, they are all within the protection scope of the present invention.

Claims

1. A logistics deposit pricing method based on intelligent risk assessment, characterized by: include: A weighted risk assessment model is introduced to assess the risk level. A business-based deposit calculation model is introduced to support the deposit pricing range. The appropriate overall risk factor is determined according to the risk level. Finally, the overall risk factor is combined with the business-based deposit calculation model to match the appropriate pricing deposit. The weighted risk assessment model comprehensively considers various risk factors, identifies and determines the key factors that affect transportation risks. The key factors of transportation risk include: cargo value, transportation distance, cargo quantity, transportation mode risk factor, and driver reputation. The weighted risk assessment model uses the above key factors as evaluation indicators to analyze and ultimately assess transportation risks.

2. According to claim 1, a logistics deposit pricing method based on intelligent risk assessment is characterized by: The risk assessment model uses a weighted sum algorithm to calculate the risk score. The specific calculation formula is as follows: RiskScore = W V ×V+W D ×D+W Q ×Q+W R ×R+W C ×C, Among them, V represents the value of the goods, D represents the transportation distance, Q represents the quantity of goods, R represents the risk factor of the transportation method, C represents the reputation of the driver, RiskScore represents the risk score, and W represents the risk factor of the transportation method. V , W D , W Q , W R , W C The corresponding weights represent the key factors such as cargo value, transportation distance, cargo quantity, transportation method risk coefficient and driver reputation. After calculating the risk score, the risk level is divided and the risk level is set according to the threshold range of the risk score.

3. The logistics deposit pricing method based on intelligent risk assessment according to claim 2 is characterized by: The business basic deposit calculation model uses the following formula to calculate the pricing range: Deposit=β0+β1×GoodsValue+β2×CompetitionIndex+β3×MarketDemandIndex, where GoodsValue represents the value of goods, CompetitionIndex represents the competition index, which is a dimensionless value; MarketDemandIndex represents the market demand index, which is also a dimensionless value. The market demand index is calculated based on factors such as industry growth rate and market demand; β0 represents a constant term, and β1, β2 and β3 represent the coefficients of the value of goods, the competition index and the market demand index respectively; historical data are collected for relevant data involved in the business basic deposit calculation model, and regression analysis is performed based on these historical data to determine the coefficients of the value of goods, the competition index and the market demand index as well as the constant term.

4. According to claim 3, a logistics deposit pricing method based on intelligent risk assessment is characterized by: The overall risk coefficient is set according to the risk level obtained from the previous assessment. The risk adjustment factor is set based on the overall risk coefficient to adjust the business basic deposit calculation model. After the risk adjustment factor RiskAdjustmentFactor is introduced into the business basic deposit calculation model, a new deposit calculation formula is obtained: Based on the above adjusted deposit calculation formula, this method obtains the deposit amount under different circumstances through simulation or actual calculation; then, according to business needs and market practices, the deposit range corresponding to different risk levels is set.

5. According to claim 1, a logistics deposit pricing method based on intelligent risk assessment is characterized by: The evaluation steps of the weighted risk assessment model are as follows: S1.

1. Evaluate the risk factor of the mode of transportation; S1.2, evaluate the driver's reputation; S1.

3. Collect and calculate the value of goods, transportation distance and quantity of goods; S1.

4. Use a weighted approach to construct a risk assessment model and assign reasonable weights to several key factors that affect transportation risks; S1.

5. Calculate risk scores using risk assessment models and classify risk levels; The cargo value and the driver's reputation are assigned high weights, the cargo quantity is assigned low weights, the weight of the transportation distance is between high weights and low weights, and the weight assigned to the transportation mode risk coefficient is determined according to the specific transportation mode.

6. According to claim 5, a logistics deposit pricing method based on intelligent risk assessment is characterized by: Methods for assessing the risk factor of a transport mode include: S1.1.

1. Historical data analysis: By analyzing historical data of different modes of transportation, including accident rates and delay rates, we can understand the risk performance of various modes of transportation; S1.1.

2. Collect and evaluate real-time information, such as weather forecasts and traffic conditions, and use it to assess the impact of the factors involved on the risk of transport modes; S1.1.

3. Expert opinion survey, assessing the risk factor of the transport mode based on the professional insights and judgments on the risks of the transport mode provided by experts; S1.1.

4. Calculate the transport mode risk factor R = ∑(W i ×X i ), where R represents the risk factor, which is a numerical value used to quantify the degree of risk; X i represents the value or score of the ith risk factor; W i The weight of the ith risk factor reflects the importance of the risk factor in the overall risk. The weight of each risk factor is determined based on expert opinions, historical data or statistical methods, and the sum of all weights should be 1, that is, ∑W i =1.

7. A logistics deposit pricing method based on intelligent risk assessment according to claim 6, characterized in that: The specific method for determining the weight Wi in step S1.1.4 includes: 1) preliminarily determining the relative weight according to the degree of impact of the risk factor on the risk; 2) collecting data on the risk factor through expert evaluation, questionnaire survey, and historical data analysis; 3) scoring or assigning a value to each risk factor based on the collected data to represent its basic weight; 4) normalizing the basic weight to unify all weights to a unified scale; 5) in actual application, the weight Wi needs to be dynamically adjusted according to the specific situation; the value or score X of the ith risk factor in step S1.1.4 i The specific determination methods include: 1) Direct numerical method: directly use numerical values ​​to measure risk factors; 2) Rating or scoring method: formulate clear scoring standards and guidelines, and rate or score risk factors through expert evaluation or questionnaire survey; 3) Historical data analysis method: determine the value of risk factors by analyzing historical data; 4) Fuzzy evaluation method: use fuzzy evaluation method based on fuzzy mathematics theory to determine the value of risk factors.

8. The logistics deposit pricing method based on intelligent risk assessment according to claim 5 is characterized by: When evaluating the reputation of a driver, we sort out and analyze the various dimensional indicators that affect the reputation of the driver, assign appropriate weights to the indicators based on their importance, and add up the scores of each dimension to get the total reputation score of the driver. The formula is as follows: Total Score = ∑ (Base-Score i ×Weight i ), where i represents different dimensions, Weight i Indicates the weight of the i-th dimension, Base-Score i It represents the basic score of the i-th dimension; the score of each dimension is obtained by deducting points from the basic score according to the deduction items; the weight setting is adjusted according to the actual situation to reflect the importance of different dimensions to the driver's reputation; the basic score and deduction items are set according to specific needs.

9. The logistics deposit pricing method based on intelligent risk assessment according to claim 8 is characterized by: Specific steps to assess a driver's reputation include: S1.2.

1. Evaluate historical records, including on-time rate, cargo damage rate and accident records; S1.2.

2. Evaluate customer feedback, which includes customer ratings and text reviews. Text reviews are analyzed by analyzing the keywords related to the evaluation in customer reviews and assigning corresponding scores to the keywords; S1.2.3, real-time monitoring and scoring, real-time monitoring includes monitoring driving behavior, setting deduction items according to driving behavior data recorded by on-board equipment, and scoring based on the monitoring results of driving behavior; S1.2.

4. Evaluate the completeness of the certificate, which includes the type of certificate, the validity of the certificate and the timeliness of the certificate update; S1.2.

5. Calculate the evaluation score according to the driver's total credit score formula.

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