CN102376067A - Scorecard system based on financial credit loan and realization method for scorecard system - Google Patents
Scorecard system based on financial credit loan and realization method for scorecard system Download PDFInfo
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- CN102376067A CN102376067A CN2010102590240A CN201010259024A CN102376067A CN 102376067 A CN102376067 A CN 102376067A CN 2010102590240 A CN2010102590240 A CN 2010102590240A CN 201010259024 A CN201010259024 A CN 201010259024A CN 102376067 A CN102376067 A CN 102376067A
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Abstract
The invention provides a scorecard system based on a financial credit load and a realization method for the scorecard system, which belong to the technical field of finance. By the system and the method, a financial mechanism can establish a scorecard model which comprises grading systems of bonus point and deduction items according to the conventional customer data; lost data in the customer data, such as a customer who is rejected to be supplied with credit service or has incomplete data records, is calculated and reasonably blended into a primary scorecard model by using the system provided by the invention so as to establish a complete scorecard model and complete credit bonus point and deduction items; and during credit service, the financial mechanism has a complete grading level for reviewing the credit qualification of a new customer. By the system and the method, the conventional data can be classified again to find a credit customer with potential risks out, so that the credit criterion and the scorecard model of the financial mechanism are changed along with a financial environment, and credit risks are reduced; therefore, a safe and effective risk estimation system is provided for the financial mechanism.
Description
Technical field
The invention belongs to the financial technology field, relate to the technology that the investee is estimated and grades, a kind of especially scoring card system and implementation method based on the financial credit loan.
Background technology
Along with market economy increasing development; The quickening of the open paces of finance, the further aggravation of financial market competition, each tame financial institution is through provide the financing and the credit services of credit underwriting or other form each other; Particularly the service of financing assurance class is provided to the small financial client; Thereby enlarge financial institution self service range, the income of financial company is finally improved in the source of raising profits.
Yet; Under fast changing and intense market competition environment; Financial company has no peace and tranquility the upheaval of international financial market, the problem of credit overexpansion, debt crisis and financial institution self control and management aspect in the face of international, domestic financial market; Possibly cause the credit crisis of financial institution at random, even cause the concuss in whole financial market.How, realize oneself's control through effective means; How to pass through scientific analysis method, select the best client of credit; How set a quantizating index that can bear risk for each client; Be financial institution utilizing customer resources, carry out provide financing services, when enlarging income; Realize effectively dividing control earlier; Guarantee the fund security of self, the impact that reduces and avoid crisis to cause is that pendulum is in global financial market and each tame financial institution difficult problem in front.At present, each tame financial institution generally lacks the means and the operating mechanism of related management experience, internal control aspect Financial Risk Control.They lack effective analytical approach and quantitative criteria; Lack quantizating index and the monitoring regime that self risk is born; Lack the overall plan of dealing with problems and effective support of system aspects.
Summary of the invention
The present invention is intended to solve ubiquitous problem of the financial institution that mentions in the above-mentioned background technology and deficiency, is exactly specifically, provides a kind of system and implementation method of carrying out scientific grading quantification to its client.This method be flexibly, adjustable; Can regulate the various parameters of grading quantization system at any time according to the change of financial environment, client's credit rating, set up rational rating system, instruct financial institution in credit operation; Relative clients is rationally graded, evade credit risk.
The purpose of this invention is to provide a kind of scoring card system based on the financial credit loan, said scoring card system based on the financial credit loan comprises:
DBM, it is the structure that is used to store and provide the historical data source, said DBM is provided with storage and the partial data submodule of partial data is provided, and stores and provide the missing data submodule of the missing data that need carry out model analysis;
The partial data analysis module; It is useful on analyzes the partial data of storing in the above-mentioned partial data submodule, sets the preliminary FOM bonus point and the factor inferior and subtracts the branch code of points, and raw score card structure of models is set; Said partial data diversity module; Also be provided with said raw score snap gauge type,, be divided into the elementary scoring card classification submodule of some grading systems according to ascending order;
The missing data analysis module; It is the missing data that is used for aforesaid missing data submodule, carries out analyses and prediction according to above-mentioned raw score rule, improves above-mentioned raw score card structure of models; Said missing data packing module also is provided with and is used for according to above-mentioned grading system; And missing data distribution situation in corresponding each grading system, calculate the missing data of missing data loss probability in each grade and lose calculating sub module, and be used for losing probability according to said missing data; Existence in each grading system of simulation missing data, the missing data completion module of the said loss probability of completion;
Standard scoring card module; It is to be used for raw score snap gauge type that above-mentioned partial data analysis module analytic process is set up, adds the supplementary data that is obtained by the analysis of missing data analysis module, sets up standard scoring card structure of models; Said standard scoring card module also is provided with the FOM that is used for evaluating customer information; Carry out the bonus point rule submodule of bonus point, and be used for evaluating the factor inferior of customer information, what subtract branch subtracts the regular submodule of branch;
Risk evaluation module, it is to be used for through above-mentioned standard scoring card module, bonus point rule submodule and to subtract the regular submodule of branch, new application user is carried out the structure of assessing credit risks.
Further, said scoring card system based on the financial credit loan also includes:
Described risk evaluation module also is provided with credit and looks into new submodule, is the user and be rejected loan user's the credit structure of reappraising of providing a loan who is used for the data with existing library module.
Said standard scoring card module is provided with the scoring card and improves submodule; It is the new application user's data that is used for according to the acceptance of risk evaluation module application assessment submodule; And look into new submodule to data library module data updated according to credit; Rearrange, improve standard scoring card structure of models.
Said system is provided with the scoring display module, is to be used to show that new application user and credit looks into the structure of new appraisal result.
Another object of the present invention provides a kind of implementation method of the scoring card system based on financial credit loan, it is characterized in that this method may further comprise the steps:
Step 1 is set up the raw score snap gauge type based on partial data X, and the corresponding relation of said scoring snap gauge type and missing data Y, and wherein missing data Y is the missing data that need carry out model analysis;
Step 2 will according to ascending order, be divided into the i grade based on the raw score snap gauge type of partial data X, infer the ratio that does not contain the corresponding numerical value of missing data Y in each grade;
Step 3, in the step 2 by scoring card grade based on the scoring snap gauge type of X, and infer the ratio that does not contain the corresponding numerical value of missing data Y in each grade, add up all observation station numbers of missing data Y in each grade;
Step 4 according to the observation station number of the missing data Y data that obtain in the step 3, defines the prior distribution in the bayesian theory, calculates the loss probability of missing data Y in all grades;
Step 5 according to the loss probability of the missing data Y that draws in the step 4, is simulated missing data Y possibly exist in each grade, handles, and is not contained the sample of any missing data, sets up the scoring card and the code of points of standard.
Further, the implementation method of said scoring card system based on financial credit loan also includes:
In step 1, said scoring snap gauge type reaches external scoring snap gauge type for through the raw score snap gauge type based on partial data X, according to certain weight, and the mix mode scoring snap gauge type that weighting forms.
In step 2, do not contain the ratio of the corresponding numerical value of missing data Y in each grade, comprise in the grade that can not get any observation station about Y, the calculating of said ratio, step is following:
Step 3.1 is added up observation point value A known in the said scoring card grade
1(1), A
1(2) ..., set up A=(A
1(1), A
1(2) ...);
Step 3.2 is according to the known observation point value A in the step 3.1
1(1), A
1(2) ..., set up corresponding scoring card mean value
Step 3.3; Set up regressive prediction model
and utilize said model, prediction can not get the observation station of missing data Y in the grade of any observation station about missing data Y.
In step 4; The loss probability of missing data Y in said all grades; To scoring card grade i wherein, the loss probability
when loss probability when including Y=1
and Y=0
In step 5, said simulation missing data Y possibly exist in each grade is to obtain according to following steps:
Step 5.1 is according to the scoring card grade i wherein that is directed against that draws in the step 4; Loss probability during Y=1
is set up model [0,
];
Step 5.2, in scoring card grade i, the observation station of Y disappearance is provided with random digit R;
Step 5.3; If R is at model [0;
] in; Then said observation station belongs to Y=1
Otherwise said observation station belongs to Y=0.
The invention has the advantages that: through this described scoring card system and implementation method based on the financial credit loan; Financial institution can be according to customer data in the past; Comprise customer data, the refusal granting credit operation of providing credit operation; But the customer data that data recording is arranged is set up elementary scoring snap gauge type, comprises bonus point and subtracts the scoring system of sub-item.Data to losing in the customer data again, as be rejected and provide credit operation and do not have data recording, or the incomplete client of data recording; Utilize system provided by the present invention; Calculate also reasonably to incorporate in the elementary scoring snap gauge type, set up complete scoring snap gauge type, reach complete credit bonus point and subtract sub-item; When financial institution carries out credit operation, new client's credit qualification evaluation had complete grading system.And through system of the present invention, can carry out combing again, find out the credit user who has potential danger data in the past; Perhaps credit terms define its credit grade again in the past, perhaps can add other effective customer data, and are constantly perfect; Make the credit criterion of financial institution, reach scoring snap gauge type, follow the variation of financial environment; Reduce credit risk, for financial institution provides risk evaluation system safely and effectively.
Description of drawings
The present invention will be described in more detail below in conjunction with accompanying drawing.
Fig. 1 is the structured flowchart of the scoring card system based on financial credit loan according to the invention.
Fig. 2 is the process flow diagram of the implementation method of the scoring card system based on financial credit loan according to the invention.
Fig. 3 is the scoring card system implementation synoptic diagram based on the financial credit loan of the present invention, is an embodiment.
Embodiment
Accompanying drawing in following reference, in conjunction with specific embodiment the present invention is done further explanation.
At first join shown in Figure 1ly, one-piece construction of the present invention is done explanation.
As shown in Figure 1; For the scoring card system 100 based on the financial credit loan of the present invention, be provided with DBM 210, it is the structure that is used to store and provide the historical data source; Customer data like financial company credit operation aspect; Can be specially the interior customer data of section sometime, said DBM 210 is provided with storage and the partial data submodule of partial data is provided, and stores and provide the missing data submodule 212 of the missing data that need carry out model analysis.Said partial data can be for obtaining the customer data of said financial institution credit operation; Perhaps do not obtain said financial institution of institute credit operation; But the customer data that specifying information is also preserved; Said missing data is for not obtaining said financial institution of institute credit operation, also for preserving the customer data of specifying information.
Said system 100 also is provided with partial data analysis module 220; It is useful on analyzes the partial data of storing in the above-mentioned partial data submodule, sets the preliminary FOM bonus point and the factor inferior and subtracts the branch code of points, and raw score card structure of models is set; Said partial data diversity module 220; Also be provided with said raw score snap gauge type,, be divided into the elementary scoring card classification submodule 221 of some grading systems according to ascending order.Said partial data analysis module 220, the related data that can provide when the demand for credit according to the user is like client's financial strength; Asset quality, each item index, economic benefit; The liquidation paying ability; Enterprise is absorbed in the possibility of Financial Distress etc., according to its segmentation grade, and the bonus point of positive negative variance Design Fundamentals and subtract the branch rule.And,,, be divided into several grades with said raw score snap gauge type according to ascending putting in order through scoring card classification submodule 221, like 20 grades, other division of level not necessarily will be gone evenly, must be in order ascending but arrange.
Said system 100 also is provided with missing data analysis module 230; It is the missing data that is used for aforesaid missing data submodule, carries out analyses and prediction according to above-mentioned raw score rule, improves above-mentioned raw score card structure of models; Said missing data packing module also is provided with and is used for according to above-mentioned grading system; And missing data distribution situation in corresponding each grading system, calculate the missing data of missing data loss probability in each grade and lose calculating sub module 231, and be used for losing probability according to said missing data; Existence in each grading system of simulation missing data, the missing data completion module 232 of the said loss probability of completion.Because missing data can't evenly distribute in all grades, the missing data that has just begun to analyze can have a plurality of observation point numbers the 10th grade; Can not find an observation point number the 11st grade, therefore need to lose calculating sub module 231, through certain algorithm through missing data; Like the prior distribution in the bayesian theory; Calculate the loss probability of missing data in all grades, and through missing data completion module 232, simulation missing data possibly exist in each grade; Handle, do not contained the sample of any missing data.
Said system also is provided with standard scoring card module 240, risk evaluation module 250, scoring display module 260.Wherein, Standard scoring card module 240 is to be used for raw score snap gauge type that above-mentioned partial data analysis module analytic process is set up, adds the supplementary data that is obtained by the analysis of missing data analysis module, sets up standard scoring card structure of models; Said standard scoring card module also is provided with the FOM that is used for evaluating customer information; Carry out the bonus point rule submodule 241 of bonus point, be used for evaluating the factor inferior of customer information, what subtract branch subtracts the regular submodule 242 of branch; And be used for applying for the new application user's data that the assessment submodule is accepted according to risk evaluation module; And look into new submodule to data library module data updated according to credit, and rearranging, the scoring card that improves standard scoring snap gauge type improves submodule 343; Risk evaluation module 250; It is to be used for through above-mentioned standard scoring card module 241, bonus point rule submodule and to subtract the regular submodule 242 of branch; New application user is carried out the structure of assessing credit risks, and described risk evaluation module 250 also is provided with the user and be rejected the credit that loan user's credit reappraises and look into new submodule of providing a loan who is used for the data with existing library module; The scoring display module is to be used to show that new application user and credit looks into the structure of new appraisal result.
Concrete; Said standard scoring card module 240 is according to the sample that does not contain any missing data after the completion that is obtained by missing data analysis module 230; Reach the elementary scoring snap gauge type of setting up by partial data analysis module 220; Set up the standard scoring snap gauge type that does not contain any missing data, and new positive or negative points rule, like the standards of grading of economic benefit during the refinement client gives information more.After the scoring criterion is set up, just can instruct financial institution that the professional client of new demand for credit is carried out the credit scoring,, choose mark according to concrete marking project.
Like full marks is 100 minutes, and grading system is following:
More than 90 minutes and 90 minutes: prestige is fabulous, almost devoid of risk
80 minutes: prestige was good, basic devoid of risk
70 minutes: prestige was better, possessed paying ability, and risk is less
60 minutes: prestige was general, possessed paying ability basically, and is risky slightly
50 minutes: prestige was not good enough, and paying ability is unstable, and certain risk is arranged
Below 50 minutes: prestige is relatively poor, and paying ability is unstable at no distant date, and great risk is arranged
Provide a loan immediately: 80-100 credit is examined very: 50-80 refuses loan: below 50 minutes
And this new client's scoring is 80 minutes, and then according to above-mentioned grading system, this user can obtain loan.And, through these standards of grading, can carry out credit to the existing user data of financial institution and look into newly, reject the user of loan with potential risk, the user who refuses is evaluated its credit qualification again.According to above-mentioned Data Update, perhaps following newly of positive or negative points project followed new scoring snap gauge type again.
Launch explanation below in conjunction with some specific embodiments.
The explanation of Fig. 3: Fig. 3 is the scoring card system implementation synoptic diagram based on the financial credit loan of the present invention, is an embodiment.
Join shown in Figure 3ly, financial institution has set up standard scoring snap gauge type through the scoring card system based on financial credit loan of the present invention, comprises authorization client application materials, confirms the code of points of positive or negative points project.
Have this moment new client professional to said financial institution apply for loan, his application materials are provided, said financial institution just can carry out credit scoring to this client through the code of points of setting up in advance.If this client's credit scoring surpasses 80 fens, then according to above-mentioned regular direct loan, perhaps this client's credit scoring is lower than 50 fens, the refusal loan.Whether no matter offer loans for said client, this client's data can be increased in the database.
Simultaneously, said financial institution can carry out credit to existing customer data in the database and look into new reappraising, and as to the client who obtains fiduciary loan, can reject the client with credit risk, carries out emphasis and keeps watch on; To the client who does not obtain fiduciary loan, can look into newly, find out potential client with loan qualification.
Above-mentioned Data Update comprises new client's data typing, has the new change of looking into of customer data; All be aggregated into database at last, set up more perfect data information, then; According to new database, can instruct the foundation snap gauge type of marking more specifically, accurately.
The explanation of Fig. 2:
It is the process flow diagram of the implementation method of the scoring card system based on financial credit loan according to the invention.
Step 1 is set up the raw score snap gauge type based on partial data X, and the corresponding relation of said scoring snap gauge type and missing data Y, and wherein missing data Y is the missing data that need carry out model analysis;
As shown in Figure 2; Database includes partial data X and missing data Y, and is concrete, and said database can be the data sample of certain 2006-2009 of financial institution; In order to guarantee the representativeness of new established model sample, said database comprises the customer information of all 3000 records.The risk manager need utilize loan customer information (containing promise breaking information) and the application in the database to be rejected customer information, makes up new scoring snap gauge type.Apply for loan but be rejected in 800 customer informations of loan, 750 information do not contain the credit quality data, are missing data Y, and 2150 remaining information are partial data X.
If there is external scoring card; Can reflect said external scoring card and the relation of missing data Y; We also can directly utilize said external scoring card so; Perhaps we make up one with external scoring card with based on the raw score card of partial data X, and weighting is built up and mixed the scoring card.
Step 2 will according to ascending order, be divided into the i grade based on the raw score snap gauge type of partial data X, infer the ratio that does not contain the corresponding numerical value of missing data Y in each grade;
Concrete, for example, the scoring of raw score card is 0 to 100, we are divided into 20 five equilibriums with it.Other division of level not necessarily will be gone evenly, must be in order ascending but arrange.
Step 3, in the step 2 by scoring card grade based on the scoring snap gauge type of X, and infer the ratio that does not contain the corresponding numerical value of missing data Y in each grade, add up all observation station numbers of missing data Y in each grade;
Concrete, the deduction method of ratio that does not contain the corresponding numerical value of missing data Y in said each grade is following:
1. add up observation point value A known in the said scoring card grade
1(1), A
1(2) ..., set up A=(A
1(1), A
1(2) ...);
2. according to the known observation point value A in the step 3.1
1(1), A
1(2) ..., set up corresponding scoring card mean value
3. set up regressive prediction model
and utilize said model, prediction can not get the observation station of missing data Y in the grade of any observation station about missing data Y.
Step 4 according to the observation station number of the missing data Y data that obtain in the step 3, defines the prior distribution in the bayesian theory, calculates the loss probability of missing data Y in all grades;
In this step; The loss probability of missing data Y in said all grades; To scoring card grade i wherein, the loss probability
when loss probability when including Y=1
and Y=0
Step 5 according to the loss probability of the missing data Y that draws in the step 4, is simulated missing data Y possibly exist in each grade, handles, and is not contained the sample of any missing data, sets up the scoring card and the code of points of standard.
In step 5, said simulation missing data Y possibly exist in each grade is to obtain according to following steps:
1. according to the scoring card grade i wherein that is directed against that draws in the step 4; Loss probability during Y=1
is set up model [0,
];
2. among the scoring card grade i, the observation station of Y disappearance is provided with random digit R;
3. if R is at model [0;
] in; Then said observation station belongs to Y=1, otherwise said observation station belongs to Y=0.
More than be the description of this invention and non-limiting, based on other embodiment of inventive concept, all among protection scope of the present invention.
Claims (9)
1. the scoring card system based on the financial credit loan is characterized in that, said scoring card system based on the financial credit loan comprises:
DBM, it is the structure that is used to store and provide the historical data source, said DBM is provided with storage and the partial data submodule of partial data is provided, and stores and provide the missing data submodule of the missing data that need carry out model analysis;
The partial data analysis module; It is useful on analyzes the partial data of storing in the above-mentioned partial data submodule, sets the preliminary FOM bonus point and the factor inferior and subtracts the branch code of points, and raw score card structure of models is set; Said partial data diversity module; Also be provided with said raw score snap gauge type,, be divided into the elementary scoring card classification submodule of some grading systems according to ascending order;
The missing data analysis module; It is the missing data that is used for aforesaid missing data submodule, carries out analyses and prediction according to above-mentioned raw score rule, improves above-mentioned raw score card structure of models; Said missing data packing module also is provided with and is used for according to above-mentioned grading system; And missing data distribution situation in corresponding each grading system, calculate the missing data of missing data loss probability in each grade and lose calculating sub module, and be used for losing probability according to said missing data; Existence in each grading system of simulation missing data, the missing data completion module of the said loss probability of completion;
Standard scoring card module; It is to be used for raw score snap gauge type that above-mentioned partial data analysis module analytic process is set up, adds the supplementary data that is obtained by the analysis of missing data analysis module, sets up standard scoring card structure of models; Said standard scoring card module also is provided with the FOM that is used for evaluating customer information; Carry out the bonus point rule submodule of bonus point, and be used for evaluating the factor inferior of customer information, what subtract branch subtracts the regular submodule of branch;
Risk evaluation module, it is to be used for through above-mentioned standard scoring card module, bonus point rule submodule and to subtract the regular submodule of branch, new application user is carried out the structure of assessing credit risks.
2. a kind of scoring card system according to claim 1 based on the financial credit loan; It is characterized in that: described risk evaluation module; Also being provided with credit and looking into new submodule, is the user and be rejected loan user's the credit structure of reappraising of providing a loan who is used for the data with existing library module.
3. according to claim 1 and 2 described a kind of scoring card systems based on the financial credit loan; It is characterized in that: said standard scoring card module is provided with the scoring card and improves submodule; It is the new application user's data that is used for according to the acceptance of risk evaluation module application assessment submodule; And look into new submodule to data library module data updated according to credit, and rearrange, improve standard scoring card structure of models.
4. a kind of scoring card system based on financial credit loan according to claim 1 and 2, it is characterized in that: said system is provided with the scoring display module, is to be used to show that new application user and credit looks into the structure of new appraisal result.
5. implementation method based on the scoring card system of financial credit loan is characterized in that this method may further comprise the steps:
Step 1 is set up the raw score snap gauge type based on partial data X, and the corresponding relation of said scoring snap gauge type and missing data Y, and wherein missing data Y is the missing data that need carry out model analysis;
Step 2 will according to ascending order, be divided into the i grade based on the raw score snap gauge type of partial data X, infer the ratio that does not contain the corresponding numerical value of missing data Y in each grade;
Step 3, in the step 2 by scoring card grade based on the scoring snap gauge type of X, and infer the ratio that does not contain the corresponding numerical value of missing data Y in each grade, add up all observation station numbers of missing data Y in each grade;
Step 4 according to the observation station number of the missing data Y data that obtain in the step 3, defines the prior distribution in the bayesian theory, calculates the loss probability of missing data Y in all grades;
Step 5 according to the loss probability of the missing data Y that draws in the step 4, is simulated missing data Y possibly exist in each grade, handles, and is not contained the sample of any missing data, sets up the scoring card and the code of points of standard.
6. according to the implementation method of the described a kind of scoring card system based on the financial credit loan of claim item 5; It is characterized in that: in step 1; Said scoring snap gauge type is for passing through the raw score snap gauge type based on partial data X; And external scoring snap gauge type, according to certain weight, the mix mode scoring snap gauge type that weighting forms.
7. according to the implementation method of the described a kind of scoring card system based on the financial credit loan of claim item 5; It is characterized in that: in step 2; The ratio that does not contain the corresponding numerical value of missing data Y in each grade; Comprise in the grade that can not get any observation station about Y, the calculating of said ratio, step is following:
Step 3.1 is added up observation point value A known in the said scoring card grade
1(1), A
1(2) ..., set up A=(A
1(1), A
1(2) ...);
Step 3.2 is according to the known observation point value A in the step 3.1
1(1), A
1(2) ..., set up corresponding scoring card mean value
Step 3.3; Set up regressive prediction model
and utilize said model, prediction can not get the observation station of missing data Y in the grade of any observation station about missing data Y.
8. according to the implementation method of the described a kind of scoring card system based on the financial credit loan of claim item 5; It is characterized in that: in step 4; The loss probability of missing data Y in said all grades; To scoring card grade i wherein, the loss probability
when loss probability when including Y=1
and Y=0
9. according to the implementation method of claim item 5 or 8 described a kind of scoring card systems based on financial credit loan, it is characterized in that: in step 5, said simulation missing data Y possibly exist in each grade is to obtain according to following steps:
Step 5.1 is according to the scoring card grade i wherein that is directed against that draws in the step 4; Loss probability during Y=1
is set up model [0,
];
Step 5.2, in scoring card grade i, the observation station of Y disappearance is provided with random digit R;
Step 5.3; If R is at model [0;
] in; Then said observation station belongs to Y=1, otherwise said observation station belongs to Y=0.
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| CN109214915A (en) * | 2018-09-06 | 2019-01-15 | 江西汉辰金融科技集团有限公司 | Borrow risk methods of marking, system and computer readable storage medium |
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| CN109800947A (en) * | 2018-12-14 | 2019-05-24 | 平安科技（深圳）有限公司 | Loan transaction processing method, device, computer equipment based on machine learning |
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| CN111932192A (en) * | 2019-05-13 | 2020-11-13 | 第四范式（北京）技术有限公司 | Decision flow configuration method executed in computer equipment and decision flow engine |
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