Research into behavioral traits of the susceptibility to the risk of significant financial misstatements

2020 ◽  
Vol 23 (3) ◽  
pp. 262-275
Author(s):  
S.V. Arzhenovskii ◽  
T.G. Sinyavskaya ◽  
A.V. Bakhteev
Keyword(s):  
Risk Assessment ◽  
Statistical Analysis ◽  
High Risk ◽  
Financial Reporting ◽  
Influential Factors ◽  
Assessment Model ◽  
Expert Survey ◽  
Personal Traits ◽  
Behavioral Traits ◽  
The Impact

Subject. The article identifies behavioral signs of the susceptibility to the risk of material misstatements through the expert survey of professional auditors. Objectives. We do empirical research into the impact five behavioral traits have, which we discovered through the two parameter risk assessment model, i.e. tolerance to violation of laws, money pathology, susceptibility to high risk, aspiration of impunity and legislative illiteracy in finance. Method.s We performed the expert survey of professional auditors to discover what determines the susceptibility to fraud among those charged with financial reporting. The expert group was made on the basis of an unbiased approach and documentation. We applied the Rasch model to rank personal traits. The collected data were processed with methods of descriptive statistics and multivariate statistical analysis. Results. Carrying out the statistical analysis of experts’ opinions, we found that their significantly correlated. Personal traits were sorted by their impact on risk assessment. Money pathology, susceptibility to high risk, aspiration of impunity and legislative illiteracy in finance were acknowledged as the most influential factors in terms of the susceptibility to misstatements of financial reporting. Conclusions and Relevance. We empirically proved the importance of factors influencing the propensity to risk of misstating financial reports. We used our own theoretical concept. The findings can be useful to auditing forms to detect the customers’ propensity to the risk of manipulating financial reporting.

A Validated Risk Model for Prediction of Early Readmission in Patients with Hepatic Encephalopathy

2018 ◽  
Vol 17 (5) ◽  
pp. 0-10
Author(s):  
Andrew J. Kruger ◽  
Fasika Aberra ◽  
Sylvester M. Black ◽  
Alice Hinton ◽  
James Hanje ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Hepatic Encephalopathy ◽  
High Risk ◽  
Risk Model ◽  
Cox Regression ◽  
Low Risk ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Early Readmission ◽  
The Impact

Introduction and aim. Hepatic encephalopathy (HE) is a common complication in cirrhotics and is associated with an increased healthcare burden. Our aim was to study independent predictors of 30-day readmission and develop a readmission risk model in patients with HE. Secondary aims included studying readmission rates, cost, and the impact of readmission on mortality. Material and methods. We utilized the 2013 Nationwide Readmission Database (NRD) for hospitalized patients with HE. A risk assessment model based on index hospitalization variables for predicting 30-day readmission was developed using multivariate logistic regression and validated with the 2014 NRD. Patients were stratified into Low Risk and High Risk groups. Cox regression models were fit to identify predictors of calendar-year mortality. Results. Of 24,473 cirrhosis patients hospitalized with HE, 32.4% were readmitted within 30-days. Predictors of readmission included presence of ascites (OR: 1.19; 95% CI: 1.06-1.33), receiving paracentesis (OR: 1.43; 95% CI: 1.26-1.62) and acute kidney injury (OR: 1.11; 95% CI: 1.00-1.22). Our validated model stratified patients into Low Risk and High Risk of 30-day readmissions (29% and 40%, respectively). The cost of the first readmission was higher than index admission in the 30-day readmission cohort ($14,198 vs. $10,386; p-value < 0.001). Thirty-day readmission was the strongest predictor of calendar-year mortality (HR: 4.03; 95% CI: 3.49-4.65). Conclusions. Nearly one-third of patients with HE were readmitted within 30-days, and early readmission adversely impacted healthcare utilization and calendar-year mortality. With our proposed simple risk assessment model, patients at high risk for early readmissions can be identified to potentially avert poor outcomes.

Impact of Venous Thromboembolism (VTE) Prophylaxis and Risk Stratification with the Caprini Model in Hospitalized Patients with Cancer

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 364-364
Author(s):  
Joshua M Ruch ◽  
Hsou M Hu ◽  
Vinita Bahl ◽  
Suman L. Sood
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
Conflicts Of Interest ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Medical Patients ◽  
Vte Prophylaxis ◽  
Patients With Cancer ◽  
Pharmacologic Prophylaxis ◽  
The Impact

Abstract Abstract 364 Introduction: VTE is a common complication in hospitalized medical patients and the role of pharmacologic anticoagulation prophylaxis is well-established. Patients with active malignancy are at higher risk for VTE during hospitalization. However, VTE prophylaxis is underutilized in these patients due to many real and perceived contraindications to prophylaxis. To aid clinicians in determining VTE risk and guide choice of prophylaxis, our institution adopted the Caprini risk assessment model (Ann Surg, 2010; 251[2]:344–50), based on clinical factors such as age, comorbidities, and recent surgery. Our primary objective was to assess adherence to recommended VTE prophylaxis in hospitalized medical patients with solid tumors, hematological malignancies, and bone marrow transplant (BMT) patients in comparison to general medical (GM) patients, and the impact of recommended prophylaxis use on VTE outcomes. Secondary objectives were to evaluate the distribution of Caprini risk scores and the utility of the Caprini risk assessment model for guiding prophylaxis in this population. Methods: Patients admitted to the hematology/oncology (HO; oncology, malignant hematology, and BMT) and GM inpatient services at the University of Michigan between July 1, 2009 to December 31, 2011 were included in the study. After IRB approval, patient information was extracted from the electronic medical record (EMR). A point-scoring method based on the Caprini risk assessment model was used to calculate VTE risk at admission. A score of 3–4 was high risk and ≥ 5 highest risk for VTE. Type of VTE prophylaxis and VTE rate were determined. Recommended prophylaxis was 5000 units TID SQ heparin, 30–40 mg SQ enoxaparin, or 2.5 mg SQ fondaparinux, ± sequential compression devices (SCDs). Pharmacological prophylaxis administration was verified in the EMR. VTE is defined as deep venous thrombosis (DVT) or pulmonary embolism (PE) occurring during hospitalization or within 90 days, confirmed by Doppler, CT or V/Q scan. Adherence was defined as the percentage of patients at high or highest risk for VTE with a length of stay ≥ 2 days who received guideline recommended prophylaxis within 2 days of admission. Patients with a contraindication to prophylaxis were excluded. A retrospective cohort study was performed. Chi-squared test was used to test differences in proportions and Cochran-Armitage test for trends. Results: 4300 patients were admitted to HO and 18,347 to GM services. Compared to GM patients (86.8%), the rate of adherence to recommended VTE prophylaxis was similar for oncology (87.6%), hematology (85.4%), and lower (45.6%) for BMT patients (p<0.0001). The overall VTE rate on HO services was 2.77%. Compared with 1.45% in GM, VTE rate was 3.02% in oncology (p=0.070), 2.01% in hematology (p=0.220), and 3.61% for BMT (p=0.001). Over half (51.3%) of VTE in HO patients occurred in patients who did not receive pharmacologic prophylaxis. In HO patients with a VTE, ordered prophylaxis included 16.0% combined pharmacological and SCD, 32.8% pharmacological alone, 32.8% SCD alone, and 18.5% none. Use of combined or pharmacologic prophylaxis alone was non-significantly increased in the non-VTE HO patients. By the Caprini risk assessment model, 33.3% of all patients on HO services were high and 62.2% highest risk, with less oncology (p=0.0001) and more BMT (p=0.0003) patients classified as high or highest risk. VTE rate in HO patients rose as Caprini risk score increased: score (n, % with VTE) 0–1 (23, 4.35%,); 2 (169, 0.59%); 3–4 (1434, 1.67%); 5–6 (1691, 2.90%); 7–8 (745, 3.76%); and 9 (238, 6.72%), p<0.0001 for trend. Conclusions: Adherence to recommended VTE prophylaxis was high in medical patients with cancer, resulting in low overall rates of VTE during and following discharge. The majority of patients with VTE did not receive recommended pharmacologic prophylaxis. Most VTE occurred in patients at highest risk (Caprini risk assessment score ≥ 5), with a trend to higher VTE rate as individual score increased. These data suggest that the individual Caprini score may provide more detailed VTE risk assessment and may help inform the need for prophylaxis despite perceived relative contraindications in this high risk cancer population. Further study is needed to understand the barriers to ordering VTE prophylaxis in this population and encourage increased prophylaxis use. Disclosures: No relevant conflicts of interest to declare.

scholarly journals An Alternative Risk Assessment Model of Urban Waterlogging: A Case Study of Ningbo City

2021 ◽  
Vol 13 (2) ◽  
pp. 826
Author(s):  
Meiling Zhou ◽  
Xiuli Feng ◽  
Kaikai Liu ◽  
Chi Zhang ◽  
Lijian Xie ◽  
...  
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
Assessment Model ◽  
Risk Assessments ◽  
Risk Assessment Model ◽  
Risk Area ◽  
The North ◽  
Coastal Cities ◽  
Risk Areas ◽  
The City

Influenced by climate change, extreme weather events occur frequently, and bring huge impacts to urban areas, including urban waterlogging. Conducting risk assessments of urban waterlogging is a critical step to diagnose problems, improve infrastructure and achieve sustainable development facing extreme weathers. This study takes Ningbo, a typical coastal city in the Yangtze River Delta, as an example to conduct a risk assessment of urban waterlogging with high-resolution remote sensing images and high-precision digital elevation models to further analyze the spatial distribution characteristics of waterlogging risk. Results indicate that waterlogging risk in the city proper of Ningbo is mainly low risk, accounting for 36.9%. The higher-risk and medium-risk areas have the same proportions, accounting for 18.7%. They are followed by the lower-risk and high-risk areas, accounting for 15.5% and 9.6%, respectively. In terms of space, waterlogging risk in the city proper of Ningbo is high in the south and low in the north. The high-risk area is mainly located to the west of Jiangdong district and the middle of Haishu district. The low-risk area is mainly distributed in the north of Jiangbei district. These results are consistent with the historical situation of waterlogging in Ningbo, which prove the effectiveness of the risk assessment model and provide an important reference for the government to prevent and mitigate waterlogging. The optimized risk assessment model is also of importance for waterlogging risk assessments in coastal cities. Based on this model, the waterlogging risk of coastal cities can be quickly assessed, combining with local characteristics, which will help improve the city’s capability of responding to waterlogging disasters and reduce socio-economic loss.

scholarly journals Breast cancer risk assessment: How risk models can “overdiagnose” risk.

2013 ◽  
Vol 31 (31_suppl) ◽  
pp. 184-184
Author(s):  
Elissa Ozanne ◽  
Brian Drohan ◽  
Kevin S. Hughes
Keyword(s):  
Breast Cancer ◽  
Risk Assessment ◽  
High Risk ◽  
Resource Utilization ◽  
Management Strategies ◽  
Cancer Risk Assessment ◽  
Cancer Society ◽  
Total Study Population ◽  
Breast Cancer Risk Assessment ◽  
The Impact

184 Background: Overdiagnosis is commonly defined as a diagnosis of "disease" which will never cause symptoms or death during a patient's lifetime. Similarly, overdiagnosis can also happen when individuals are given the diagnosis of being at risk for a disease, such as being at high-risk for developing breast cancer. Women can be given such a diagnosis by meeting a set of risk assessment criteria, which are often accompanied by recommended management strategies. We sought to identify the extent and consequences of overdiagnosis for individuals being at high risk for breast cancer using the American Cancer Society (ACS) guidelines for the appropriate use of Magnetic Resonance Imaging (MRI). Methods: We identified women who fit the ACS criteria in a population based sample at a community hospital. The ACS criteria mentions three risk assessment models for determining a woman’s risk, and these criteria were reviewed to determine the extent of possible overdiagnosis in this population. The expected resource utilization resulting from this overdiagnosis, and the impact on patient quality of life are extrapolated. Results: 5,894 women who received mammography screening at the study site were included. 342 (5.8%) of the women were diagnosed as high risk by at least one model. However, only 0.2% of the total study population were diagnosed as high risk by all three models. One model identified 330 (5.6%) to be at high risk, while the other two models identified many fewer eligible women (25, 0.4% and 54, 0.9% respectively). Conclusions: Using different models to evaluation the ACS criteria identifies very different populations, implying a large potential for overdiagnosis. Further, this overdiagnosis is likely to result in the outcome of screening too many women, incurring false positives and unnecessary resource utilization.

Leveraging HCA Results in an Advanced Pipeline Risk Assessment Model

2014 ◽  
Author(s):  
Otto Huisman ◽  
Ricardo Almandoz ◽  
Thomas Schuster ◽  
Adriana Andrade Caballero ◽  
Leonardo Martinez Forero
Keyword(s):  
Risk Assessment ◽  
American Petroleum Institute ◽  
Assessment Model ◽  
Mitigation Measures ◽  
South American ◽  
Risk Assessment Model ◽  
Industry Standards ◽  
Management Approaches ◽  
American Society ◽  
The Impact

Pipeline risk analysis is a common step carried out by operators in their overall Pipeline Integrity Management Process. There is a growing realization among operators of the need to adopt more proactive risk management approaches. This has brought about increased demand for more quantitative models to support risk reduction decision-making. Consequences of failure are a key component of these models where enhanced quantitative approaches can be deployed. Impacts to the environment and upon populations are key issues which both operators and regulatory bodies seek to minimize. Pipeline risk models and High Consequence Area (HCA) analyses play an increasingly important role in this context by allowing operators to identify a range of potential scenarios and the relative impact to receptors based upon the best available data sources. This paper presents the process and results of an HCA analysis project carried out by ROSEN for a major South American state-owned pipeline operator (hereafter referred to as ‘the Client’). This analysis was implemented using automated GIS processing methods and includes HCA analyses for approximately 2354 km of pipeline. The analysis was based on industry standards for both liquid and gas pipelines (i.e. American Petroleum Institute (API) and American Society of mechanical Engineers (ASME)), but customized for the specific needs of the Client and the South American geographical context. A key use for the results of this analysis is to serve as input for the pipeline risk assessment model jointly developed by ROSEN Integrity Solutions, MACAW Engineering and the Client. The methodology for development of this model is briefly discussed, and operational uses of HCA results are illustrated. The benefits of this project include, but are not limited to, identifying areas that could be severely impacted should a pipeline failure occur, being able to assess the risk profile of credible threats in HCAs, but also being able to prioritize preventative and mitigation measures at HCAs to either reduce the likelihood of failure or the impact of failure upon various receptors.

scholarly journals On the Risk Assessment of Terrorist Attacks Coupled with Multi-Source Factors

2018 ◽  
Vol 7 (9) ◽  
pp. 354 ◽  
Author(s):  
Xun Zhang ◽  
Min Jin ◽  
Jingying Fu ◽  
Mengmeng Hao ◽  
Chongchong Yu ◽  
...  
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
Southeast Asia ◽  
The Philippines ◽  
Assessment Model ◽  
Terrorist Attacks ◽  
Recommendation Algorithm ◽  
Spatial Risk ◽  
Risk Areas ◽  
F Measure

Terrorism has wreaked havoc on today’s society and people. The discovery of the regularity of terrorist attacks is of great significance to the global counterterrorism strategy. In this study, we improve the traditional location recommendation algorithm coupled with multi-source factors and spatial characteristics. We used the data of terrorist attacks in Southeast Asia from 1970 to 2016, and comprehensively considered 17 influencing factors, including socioeconomic and natural resource factors. The improved recommendation algorithm is used to build a spatial risk assessment model of terrorist attacks, and the effectiveness is tested. The model trained in this study is tested with precision, recall, and F-Measure. The results show that, when the threshold is 0.4, the precision is as high as 88%, and the F-Measure is the highest. We assess the spatial risk of the terrorist attacks in Southeast Asia through experiments. It can be seen that the southernmost part of the Indochina peninsula and the Philippines are high-risk areas and that the medium-risk and high-risk areas are mainly distributed in the coastal areas. Therefore, future anti-terrorism measures should pay more attention to these areas.

Risk assessment of post-wildfire hydrological response in semiarid basins: the effects of varying rainfall representations in the KINEROS2/AGWA model

2016 ◽  
Vol 25 (3) ◽  
pp. 268 ◽  
Author(s):  
Gabriel Sidman ◽  
D. Phillip Guertin ◽  
David C. Goodrich ◽  
Carl L. Unkrich ◽  
I. Shea Burns
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
Peak Flow ◽  
Radar Data ◽  
Burned Area ◽  
Rainfall Runoff ◽  
National Monument ◽  
Bandelier National Monument ◽  
The Impact ◽  
Runoff Events

Representation of precipitation is one of the most difficult aspects of modelling post-fire runoff and erosion and also one of the most sensitive input parameters to rainfall-runoff models. The impact of post-fire convective rainstorms, especially in semiarid watersheds, depends on the overlap between locations of high-intensity rainfall and areas of high-severity burns. One of the most useful applications of models in post-fire situations is risk assessment to quantify peak flow and identify areas at high risk of flooding and erosion. This study used the KINEROS2/AGWA model to compare several spatial and temporal rainfall representations of post-fire rainfall-runoff events to determine the effect of differing representations on modelled peak flow and determine at-risk locations within a watershed. Post-fire rainfall-runoff events at Zion National Park in Utah and Bandelier National Monument in New Mexico were modelled. Representations considered included both uniform and Soil Conservation Service Type II hyetographs, applying rain over the entire watershed and applying rain only on the burned area, and varying rainfall both temporally and spatially according to radar data. Results showed that rainfall representation greatly affected modelled peak flow, but did not significantly alter the model’s predictions for high-risk locations. This has important implications for post-fire assessments before a flood-inducing rainfall event, or for post-storm assessments in areas with low-gauge density or lack of radar data due to mountain beam blockage.

Prevalence of Risk Factors for VTE In Hospitalized Medical and Surgical Patients. Data From the Comparison of Methods for Thromboembolic Risk Assessment with Clinical Perceptions and AwareneSS In Real Life Surgical and Medical Patients (COMPASS) Study

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 3337-3337
Author(s):  
Grigoris T Gerotziafas ◽  
Miltos Chrysanthidis ◽  
Reda Isaad ◽  
Hela Baccouche ◽  
Chrysoula Papageorgiou ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Gastrointestinal Disease ◽  
Real Life ◽  
Bleeding Risk ◽  
Hospitalized Patients ◽  
Assessment Model ◽  
Surgical Patients ◽  
Medical Patients ◽  
The Impact

Abstract Abstract 3337 Introduction: Risk assessment models (RAM) are helpful tools for the screening VTE risk in hospitalized patients. Most of the available RAMs have been constructed on a disease-based or surgery-based approach and include some of the most relevant risk factors for VTE. There is limited information on the impact and importance of individual and comorbidity related risk factors for VTE present during hospitalization on the global VTE risk. Incorporation of the most frequent VTE risk and bleeding risk factors related to comorbidities might improve the ability of RAM to detect real-life patients at risk VTE and to evaluate drawbacks for the application of thromboprophylaxis. Aim of the study: The primary aim of the COMPASS programme was to evaluate the prevalence of the all known VTE and bleeding risk factors reported in the literature in real-life surgical and medical hospitalized patients. Methods: A prospective multicenter cross-sectional observational study was conducted in 6 hospitals in Greece and 1 in France. All inpatients aged >40 years hospitalised for medical diseases and inpatients aged >18 years admitted due to a surgical procedure and hospitalisation for a period exceeding three days were included. Patients and their treating physicians were interviewed with standardised questionnaire including all VTE and bleeding risk factors described in literature (130 items) on the third day of hospitalisation. Patients not giving informed consent, or receiving anticoagulant treatment for any reason or hospitalised in order to undergo diagnostic investigation without any further therapeutic intervention were excluded. Results: A total of 806 patients were enrolled in the study (414 medical and 392 surgical). Most frequent causes of hospitalisation in medical patients were infection (42%), ischemic stroke (14%), cancer (13%), gastrointestinal disease (9%), pulmonary disease (4%), renal disease (3%) and rheumatologic disease (1,4%). Surgical patients were hospitalised for vascular disease (22%) cancer (19,4%) gastrointestinal disease (12,5%), infection (8%), orthopaedic surgery and trauma (14%) or minor surgery (7%). Analysis of the frequency of risk factors for VTE showed that active cancer, recent hospitalisation, venous insufficiency and total bed rest without bathroom privileges were frequent in both groups. Medical patients had significantly more frequently than surgical patients several important predisposing risk factors for VTE. Moreover, medical patient had more frequently than surgical ones bleeding risk factors. The data for the most frequent risk factors are summarised in Table 1. Conclusion: COMPASS is the first registry that provides key data on the prevalence of all known VTE and bleeding risk factors in real life medical and surgical patients hospitalised in two countries of European Union. The analysis of the data shows that in addition to risk stemin from the disease or surgical act both medical and surgical patients share common VTE risk factors. The careful analysis of the most frequent and relevant VTE risk factors will allow the derivation of a practical VTE and bleeding risk assessment model taken into account these factors. Disclosures: Chrysanthidis: Sanofi-Aventis: Employment.

External validation of the IMPROVE Bleeding Risk Assessment Model in medical patients

2016 ◽  
Vol 116 (09) ◽  
pp. 530-536 ◽  
Author(s):  
David J. Rosenberg ◽  
Anne Press ◽  
Joanna Fishbein ◽  
Martin Lesser ◽  
Lauren McCullagh ◽  
...  
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
High Risk Patient ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Validation Sample ◽  
Medical Patients ◽  
Medically Ill ◽  
Major Bleed ◽  
Hospitalised Patients

SummaryThe IMPROVE Bleed Risk Assessment Model (RAM) remains the only bleed RAM in hospitalised medical patients using 11 clinical and laboratory factors. The aim of our study was to externally validate the IMPROVE Bleed RAM. A retrospective chart review was conducted between October 1, 2012 and July 31, 2014. We applied the point scoring system to compute risk scores for each patient in the validation sample. We then dichotomised the patients into those with a score <7 (low risk) vs ≥ 7 (high risk), as outlined in the original study, and compared the rates of any bleed, non-major bleed, and major bleed. Among the 12,082 subjects, there was an overall 2.6 % rate of any bleed within 14 days of admission. There was a 2.12 % rate of any bleed in those patients with a score of < 7 and a 4.68 % rate in those with a score ≥ 7 [Odds Ratio (OR) 2.3 (95 % CI=1.8–2.9), p<0.0001]. MB rates were 1.5 % in the patients with a score of < 7 and 3.2 % in the patients with a score of ≥ 7, [OR 2.2 (95 % CI=1.6–2.9), p<0.0001]. The ROC curve was 0.63 for the validation sample. This study represents the largest externally validated Bleed RAM in a hospitalised medically ill patient population. A cut-off point score of 7 or above was able to identify a high-risk patient group for MB and any bleed. The IMPROVE Bleed RAM has the potential to allow for more tailored approaches to thromboprophylaxis in medically ill hospitalised patients.Supplementary Material to this article is available online at www.thrombosis-online.com.

scholarly journals Toolset for financial risk strategic assessment in corporations based on stochastic modeling

2020 ◽  
Vol 9 (28) ◽  
pp. 451-464
Author(s):  
Viktoriya Manuylenko ◽  
Denis Ryzin ◽  
Natalia Gryzunova ◽  
Olga Bigday ◽  
Olga Mandrytsa
Keyword(s):  
Risk Assessment ◽  
Risk Management ◽  
Financial Risk ◽  
Assessment Model ◽  
Financial Risks ◽  
Financial Leverage ◽  
Financial Risk Management ◽  
Environment Factors ◽  
Target Values ◽  
The Impact

The study substantiates the need to develop and test a model for assessment of strategic financial risk level in corporations. It implies modeling for two indicators: relative (financial leverage) and absolute (external capital of indicators). The model should also take into account influence of emergent environment factors and most stakeholder groups’ interests when building scenarios for their behaviors in the financial markets –Implementation of the model allows establishing financial risk target values considering deviation calculations between the indicators’ modeled and actual values simultaneously determining both tactical and strategic guidelines for Financial Risk Management Policy in corporations, which should involve stakeholders into financial risk-taking process. The model implementation also should be the basis for development and improvement of risk-based forecasting tools, business planning and stress testing. The toolkit for assessing level of current and strategic financial risks in corporations based on simulation modeling was developed and implemented with attraction of general scientific and special methods. Direct results of the study are as follows: in theoretical block of the research – essentially, main attributes of financial risks classification for corporations are identified; they are recognized by time as retrospective, current and strategic financial risks, and correct classification of the latter allows their identification, evaluation and regulation; in practical block of the research – evaluation of financial risk in corporations reveals that the risk apart from other internal factors is highly affected by the level of financial leverage, where its high value increases financial risk; still, corporations do not take into account the influence of environmental factors on its level; the role of tax risk as a part of financial risk is not significant, still it is unfortunate that the Russian legislation system allows double taxation on income tax in the form of dividends, and dividend policy of Russian corporations is unstable; in methodological block of the research –financial risk assessment model for corporations was developed and tested on a platform of a special new software product that determines the target level of financial risk; the model differs from standard approaches to financial risk assessment as it carries strategic forecasting nature and takes into account the impact of emergent environment factors; thus it promotes new areas in strategic financial risk management.

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