A novel financial risk assessment model for companies based on heterogeneous information and aggregated historical data

Conventional financial risk assessment is not accurate and its adaptive assessment ability is low. In order to solve this problem, a financial risk assessment model based on big data is proposed. In this method, the quantitative analysis method is adopted to analyze the explanatory variable model and the control variable model of financial risk assessment. The market-to-book ratio, asset–liability ratio, cash flow ratio and financing structure model are adopted as constraint parameters to construct a big data analysis model for financial risk assessment. On this basis, the adaptive fuzzy weighted control method is adopted for information fusion of financial risk assessment data and big data classification, and the asset income control and innovative evaluation model are adopted for linear planning and square fitting during financial risk assessment. Based on the intervention factors of financial market participants, quantitative regression analysis is performed, and according to the economic game theory, big data analysis and prediction of financial risk assessment are performed through the regression analysis method. Then the big data fusion and clustering algorithms are adopted for financial risk assessment. The simulation results show that this method can provide a relatively high accuracy in financial risk assessment, and has relatively strong adaptive evaluation capability to the risk coefficient, so it has a good application value in the prevention and control of risk factors in financial systems.

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Financial Risk Assessment Model Based on Stochastic Forest and Decision Tree Hybrid Algorithm

10.1109/ecice52819.2021.9645735 ◽

2021 ◽

Author(s):

Peipei Pan

Keyword(s):

Risk Assessment ◽

Decision Tree ◽

Hybrid Algorithm ◽

Financial Risk ◽

Assessment Model ◽

Risk Assessment Model ◽

Model Based

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Risk assessment model for venous thromboembolism in hospitalized surgical and non-surgical patients in the 4th Hungarian Antithrombotic Guidelines entitled “Diminution and Treatment of Venous Thromboembolism”

Orvosi Hetilap ◽

10.1556/oh.2010.28944 ◽

2010 ◽

Vol 151 (34) ◽

pp. 1365-1374 ◽

Cited By ~ 1

Author(s):

Marianna Dávid ◽

Hajna Losonczy ◽

Miklós Udvardy ◽

Zoltán Boda ◽

György Blaskó ◽

...

Keyword(s):

Risk Assessment ◽

Venous Thromboembolism ◽

Assessment Model ◽

Surgical Patients ◽

Risk Assessment Model

A kórházban kezelt sebészeti és belgyógyászati betegekben jelentős a vénásthromboembolia-rizikó. Profilaxis nélkül, a műtét típusától függően, a sebészeti beavatkozások kapcsán a betegek 15–60%-ában alakul ki mélyvénás trombózis vagy tüdőembólia, és az utóbbi ma is vezető kórházi halálok. Bár a vénás thromboemboliát leggyakrabban a közelmúltban végzett műtéttel vagy traumával hozzák kapcsolatba, a szimptómás thromboemboliás események 50–70%-a és a fatális tüdőembóliák 70–80%-a nem a sebészeti betegekben alakul ki. Nemzetközi és hazai felmérések alapján a nagy kockázattal rendelkező sebészeti betegek többsége megkapja a szükséges trombózisprofilaxist. Azonban profilaxis nélkül marad a rizikóval rendelkező belgyógyászati betegek jelentős része, a konszenzuson alapuló nemzetközi és hazai irányelvi ajánlások ellenére. A belgyógyászati betegek körében növelni kell a profilaxisban részesülők arányát és el kell érni, hogy trombózisrizikó esetén a betegek megkapják a hatásos megelőzést. A beteg trombóziskockázatának felmérése fontos eszköze a vénás thromboembolia által veszélyeztetett betegek felderítésének, megkönnyíti a döntést a profilaxis elrendeléséről és javítja az irányelvi ajánlások betartását. A trombózisveszély megállapításakor, ha nem ellenjavallt, profilaxist kell alkalmazni. „A thromboemboliák kockázatának csökkentése és kezelése” című, 4. magyar antithromboticus irányelv felhívja a figyelmet a vénástrombózis-rizikó felmérésének szükségességére, és elsőként tartalmazza a kórházban fekvő belgyógyászati és sebészeti betegek kockázati kérdőívét. Ismertetjük a kockázatbecslő kérdőíveket és áttekintjük a kérdőívekben szereplő rizikófaktorokra vonatkozó bizonyítékokon alapuló adatokat.

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Signature Analysis: Statistical Models and Their Application to FA

ISTFA 1996: Conference Proceedings from the 22nd International Symposium for Testing and Failure Analysis ◽

10.31399/asm.cp.istfa1996p0183 ◽

1996 ◽

Author(s):

C.K. Lakshminarayan ◽

S. Pabbisetty ◽

O. Adams ◽

F. Pires ◽

M. Thomas ◽

...

Keyword(s):

Risk Assessment ◽

Failure Analysis ◽

Statistical Models ◽

Essential Elements ◽

Assessment Model ◽

Signature Analysis ◽

Risk Assessment Model ◽

Sample Sizes ◽

Reliability Engineering ◽

Semiconductor Chips

Abstract This paper deals with the basic concepts of Signature Analysis and the application of statistical models for its implementation. It develops a scheme for computing sample sizes when the failures are random. It also introduces statistical models that comprehend correlations among failures that fail due to the same failure mechanism. The idea of correlation is important because semiconductor chips are processed in batches. Also any risk assessment model should comprehend correlations over time. The statistical models developed will provide the required sample sizes for the Failure Analysis lab to state "We are A% confident that B% of future parts will fail due to the same signature." The paper provides tables and graphs for the evaluation of such a risk assessment. The implementation of Signature Analysis will achieve the dual objective of improved customer satisfaction and reduced cycle time. This paper will also highlight it's applicability as well as the essential elements that need to be in place for it to be effective. Different examples have been illustrated of how the concept is being used by Failure Analysis Operations (FA) and Customer Quality and Reliability Engineering groups.

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