Abstract

Financialization has contributed to economic growth but has caused scandals, misselling, rogue trading, tax evasion, and market speculation. To a certain extent, it has also created problems in social and economic instability. It is an important aspect of Enterprise Security, Privacy, and Risk (ESPR), particularly in risk research and analysis. In order to minimize the damaging impacts caused by the lack of regulatory compliance, governance, ethical responsibilities, and trust, we propose a Business Integrity Modeling and Analysis (BIMA) framework to unify business integrity with performance using big data predictive analytics and business intelligence. Comprehensive services include modeling risk and asset prices, and consequently, aligning them with business strategies, making our services, according to market trend analysis, both transparent and fair. The BIMA framework uses Monte Carlo simulation, the Black–Scholes–Merton model, and the Heston model for performing financial, operational, and liquidity risk analysis and present outputs in the form of analytics and visualization. Our results and analysis demonstrate supplier bankruptcy modeling, risk pricing, high-frequency pricing simulations, London Interbank Offered Rate (LIBOR) rate simulation, and speculation detection results to provide a variety of critical risk analysis. Our approaches to tackle problems caused by financial services and the operational risk clearly demonstrate that the BIMA framework, as the outputs of our data analytics research, can effectively combine integrity and risk analysis together with overall business performance and can contribute to operational risk research.

Highlights

  • Financialization describes an economic system or process that attempts to transform all value exchanged, whether it is tangible or intangible, into a financial instrument [1]

  • Gorton [4,54] describes a lightweight with a risk reduction approach to significant data analytics process and architecture, which is known as Lightweight Evaluation and Architecture Prototyping for Business Integrity Modeling and Analysis (BIMA) framework (LEAP4BD)

  • As in as Heston model istheoretical a specialized type of which stochastic model that can use thepresented market volatility an3,input rather input for BSM, which tends used the market volatility anasinput rather thanthan the the theoretical input for BSM, tends totobebe used in use the market volatility as an input rather than the theoretical input for BSM, which tends to be used in predicting the outcomes after a period of expiry time

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Summary

Introduction

Financialization describes an economic system or process that attempts to transform all value exchanged, whether it is tangible or intangible, into a financial instrument [1]. We propose the Business Integrity Management and Analytics (BIMA) framework to provide risk analysis and optimization services for ESPR. This framework formalizes a new layer of abstraction for the business to offer true values in financial risk analysis for ESPR. We propose the use of an integrated method to identify sources of risk, put and call prices, market volatility, and prediction of market trends based on the historical and recent financial data. This integrated method consists of the Monte Carlo method, the Black–Scholes–Merton model, the Heston model, and analytics/visualization.

Business Analytics
Background
What Is Managing Business Integrity Mean in the Context Today?
Big Data
Monte Carlo Simulations
Heston Model
Visualization and Analytics
The Architecture and the Core Components
Network Infrastructure
Architecture Guidelines for the BIMA Framework
SOA Based Soft Compute Platform Supporting WAAF Matrix
SOA-Based for BIMA
Discussion
Probability
Weand used a high-end computer cluster consisting of aWe total of between
The Heston Model with Visualization and Analytics
Managing Business Integrity
Findings
Summary of Discussion
Conclusions

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