Question

Why is it difficult to include financial enterprises in the list of firms while performing a financial structure analysis of firms? Also why the firms with an abnormality in data statistics are difficult to be analyzed for financial analysis?

Answer 1

Financial structure refers to the mix of debt and equity that a company uses to finance its operations. This composition directly affects the risk and value of the associated business. The financial managers of the business have the responsibility of deciding the best mixture of debt and equity for optimizing the financial structure.

In general, the financial structure of a company can also be referred to as the capital structure. In some cases, evaluating the financial structure may also include the decision between managing a private or public business and the capital opportunities that come with each.

Understanding Financial Structure

Companies have several choices when it comes to setting up the business structure of their business. Companies can be either private or public. In each case, the framework for managing the capital structure is primarily the same but the financing options differ greatly.

Debt capital is received from credit investors and paid back over time with some form of interest. Equity capital is raised from shareholders giving them ownership in the business for their investment and a return on their equity that can come in the form of market value gains or distributions. Each business has a different mix of debt and equity depending on its needs, expenses, and investor demand.

Private versus Public

Private and public companies have the same framework for developing their structure but several differences that distinguish the two. Both types of companies can issue equity. Private equity is created and offered using the same concepts as public equity but private equity is only available to select investors rather than the public market on a stock exchange. As such the equity fundraising process is much different than a formal initial public offering (IPO). Private companies can also go through multiple rounds of equity financing over time which affects their market valuation. Companies that mature and choose to issue shares in the public market do so through the support of an investment bank that helps them to pre-market the offering and value the initial shares. All shareholders are converted to public shareholders after an IPO and the market capitalization of the company is then valued based on shares outstanding times market price.

Debt capital follows similar processes in the credit market with private debt primarily only offered to select investors. In general, public companies are more closely followed by rating agencies with public ratings helping to classify debt investments for investors and the market at large. The debt obligations of a company take priority over equity for both private and public companies. Even though this helps debt to come with lower risks, private market companies can still usually expect to pay higher levels of interest because their businesses and cash flows are less established which increases risk.

Debt versus Equity

In building the financial structure of a company, financial managers can choose between either debt or equity. Investor demand for both classes of capital can heavily influence a company’s financial structure. Ultimately, financial management seeks to finance the company at the lowest rate possible, reducing its capital obligations and allowing for greater capital investment in the business.

Overall, financial managers consider and evaluate the capital structure by seeking to optimize the weighted average cost of capital (WACC). WACC is a calculation that derives the average percentage of payout required by the company to its investors for all of its capital. A simplified determination of WACC is calculated by using a weighted average methodology that combines the payout rates of all of the company’s debt and equity capital.

Metrics for Analyzing Financial Structure

The key metrics for analyzing the financial structure are primarily the same for both private and public companies. Public companies are required to file public filings with the Securities and Exchange Commission which provides transparency for investors in analyzing financial structure. Private companies typically only provide financial statement reporting to their investors which makes their financial reporting more difficult to analyze.

Data for calculating capital structure metrics usually come from the balance sheet. A primary metric used in evaluating financial structure is a debt to total capital. This provides quick insight on how much of the company’s capital is debt and how much is equity. Debt may include all of the liabilities on a company’s balance sheet or just long-term debt. Equity is found in the shareholders’ equity portion of the balance sheet. Overall, the higher the debt to capital ratio the more a company is relying on debt.

Debt to equity is also used to identify capital structuring. The more debt a company has the higher this ratio will be and vice versa.

As technology continues to evolve, it promotes changes to business models and surprises those who are unprepared. Businesses change their strategies and the way they operate. New threats and opportunities arise. In an increasingly data-driven world, CPAs need to be able to adapt to these technological disruptions.

CPAs now often find themselves performing tasks that require skills in data analytics:

• Both internal and external auditors are using data analytics to enable practices such as continuous monitoring, continuous auditing, and analysis of full data sets in situations where only samples were audited.
• Financial planning and analysis professionals analyze data in hopes of discovering the best course of action for their companies.
• CFOs and finance leaders use Big Data to find patterns in customer behavior and market trends to drive company strategy.

In an effort to advance the use of analytics in auditing, the AICPA and Rutgers Business School in December 2015 announced a research initiative (raw.rutgers.edu/radar.html) focusing on integrating analytics into the audit process and on defining how analytics can be used to enhance audit quality. Potential improvements include producing higher-quality audit evidence, reducing repetitive tasks, and better correlating audit tasks to risks and assertions. The AICPA will use the findings from this initiative to inform guidance on audit data analytics for CPA firms of all sizes.

A joint AICPA Assurance Services Executive Committee/Auditing Standards Board Task Force is developing a new Audit Data Analytics Guide, which will supersede the current Analytical Procedures guide. This new guide will carry forward much of the content included within the Analytical Procedures guide but will also include guidance on using audit data analytics throughout the audit process. Related projects are also underway to create voluntary audit data standards, which help with the extraction of data and facilitate the use of audit data analytics, and a tool to help illustrate where audit data analytics can be used in a typical audit program.

Meanwhile, mastery of data analytics can help businesses generate a higher profit margin and gain a meaningful competitive advantage. Some experts even predict that companies ignoring data analytics may be forced out of business in the long run. As data analytics is an area where change may occur more quickly than companies or CPAs may adapt, change management concepts should be considered to take advantage of the opportunities data analytics can bring.

Given that the price of computer hardware and cloud services has been ever-decreasing, what exactly stands in the way of companies being more data-driven? It is the human element.

"The human element of data analytics is the most critical factor in building a successful program," said Roshan Ramlukan, EY principal and global assurance analytics leader. "But it's also the least understood and an impediment to further growth in this area. Leaders must also recognize that analytical skills must be developed in all of their people, not just a few data analysts." (See the chart "Importance of Analytics Skills" for CFOs' ranking of the importance of data analytics skills for accounting and finance staff.)