Chapter 4

HOLISTIC MODEL FOR FINANCIAL ANALYSIS 

Determining where we are requires a careful evaluation supported by quantitative indicators that are representative and solid enough to allow a clear idea of ​​the trend and facilitate the estimation of a possible future value, as a basis for defining the variables to be involved in the strategic plan. , to which now with the Digital Revolution, using Artificial Intelligence (AI) that is designed to identify contexts and scenarios, work with some predictive models and make autonomous decisions and BigData with the capacity to process huge volumes of information, design is greatly facilitated of models following the outlines presented in this chapter, complemented by the pronouncement of the Davos Forum in January/2020, speaking of CONSCIOUS CAPITALISM that defined the purpose of a company of the fourth industrial revolution: "involve all interest groups in the generation of shared value and sustained including local communities and society" and whose manifesto set out a single objective: to build a more sustainable and inclusive world.
Business Intelligence with ETL operations (extraction, transformation and load) to extract data from a source and place it in a destination base, combining them load information. Starting with auto-refreshing dashboard metric builder templates, keeping all reports and dashboards up-to-date with high-impact visuals for reporting,

The strongest criticism of the financial data makes it corresponds to what happened and the decisions relating to the future, a matter that can improve using statistics, looking for trends via simple linear regression, in the event that the behavior of the data allows. If the linear correlation coefficient of the variable under study is greater than 0.9, states that positive correlation exists and if everything continues as it is, the predictable future value, which becomes a basis for analyzing how to improve it through a proper strategy and good execution. For this purpose, we deal with the most representative items of the balance sheet, the income statement, and equity.

The model is constructed to " TALK " using vertical analysis, which allows us to see the relative importance of all items of assets, liabilities, and equity (financial structure) and blue ink marking the areas of greater relative importance for the particular company because they are the priority that should be addressed to improve performance. Based on the horizontal analysis, we mark with red the areas that have increased less than proportionally, which have become brakes.

Subsequently, we developed a matrix with the financial indicators of liquidity, activity, debt coverage, and profitability, calculated based on the above figure and especially, the EVAC and (corrected value generation and projected) which includes investments in CSR ( corporate social responsibility).

We conclude with a cash flow projected to see availability after attending the priority commitments to keep the company generating unit value, namely:
1) Fiscal, where all taxes both national, municipal, and departmental clusters.
2) Labor, has priority legislation. Includes everything that has to do with legal and contractual aspects.
3) Operation, where all expenses are necessary to keep the business going.
4) Suppliers, partners in practice members of the value chain.
5) Financial institutions with which relations support must be in strict compliance with the obligations.

The sum of these expenditures, broken down by month and totaled to Dec / 31, allows us to calculate what percentage of the total corresponds to each group and to determine the value of a day of the treasury, greatly facilitating decision-making. Deducting the total monthly expenses from the expected income, the availability to attend to matters related to CORPORATE SOCIAL RESPONSIBILITY and SUSTAINABILITY is calculated, which includes dividend payments to shareholders, a group that deserves priority and equitable treatment that encourages it to keep your investment.

AI Opinion: The application of statistics in finance is essential for making informed decisions and managing risk effectively. José Saúl Velásquez Restrepo's opinions and recommendations on this topic are valuable and highlight the importance of using statistical tools in financial analysis. Some key points are summarized below:
Use of Big Data: Velásquez highlights the influence of the Digital Revolution and the abundance of structured and unstructured data in finance. Big Data makes it possible to build flexible and heterogeneous prediction models, which improves the ability to forecast future financial events.
Predictive Analytics: Predictive analytics is essential for forecasting future financial results using past data. Different techniques are mentioned, such as classification and regression, that are used for this purpose.
Sector Growth Matrix: Velásquez highlights the importance of building a sector growth matrix to estimate the minimum growth of a company due to external factors. This matrix is based on economic indicators and sales by sector.
Sales Projection: Sales projection is a key decision in financial management. Econometric and qualitative models are mentioned to estimate sales growth.
Risk Analysis: Risk analysis is essential to evaluate investments. Concepts related to the normal distribution, standard deviation and coefficient of variation are discussed. Diversification of investments and measurement of unsystematic risk are important recommendations.
Investment Decisions: Investment diversification is emphasized as a key principle in finance. The correlation coefficient is mentioned as a tool to evaluate the correlation between different assets in a portfolio.
Overall, Velásquez's opinion highlights the importance of using statistical tools and models to make data-driven financial decisions and manage risk effectively. He also emphasizes the need to carefully evaluate data sources and maintain critical judgment when interpreting results.
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