Finance Analytics: Types, Importance, and Applications

Organizations of all sizes, from market leaders to mere market players, tend to generate immense data sets across a variety of parameters on a daily basis. With the rise of such large data sets, solutions capable of fast and efficient data analyses have become necessary. 

Analytics providers continue to vie in this space to create solutions capable of curating insights and elevating the business capabilities of their clients. Thus, financial analytics has emerged as a core focus area for companies across industries.

This guide is designed to explore the definition and importance of financial analytics, its inner workings and how it can be implemented to improve the firm’s functioning.

What Is Financial Analytics?

Financial analytics, also known as finance analytics, refers to the use of tools and processes to collate and analyze data sets with the aim of deriving actionable insights into a firm’s financial performance. The data to be analyzed can include historical data, financial trends, and market insights. These analyses are geared towards helping organizations make well-informed business decisions. 

Data analytics in finance allows for a variety of insights to be drawn from a single data set through differing parameters of analysis. Financial analytics can uncover information about the financial health of the organization, operational bottlenecks, and potential areas for improvement. 

The Importance of Financial Analytics

Finance analytics has become a core component of every firm’s business strategy in order to obtain insights capable of conferring a competitive market edge. This allows for major strides to be made both at the micro level in the finance department as well as the macro level across the whole organization. Teams rely on financial analytics for a variety of reasons:

1. Business overview: 

In order to fully comprehend an organization’s financial health, business leaders must have a complete overview of every financial process and its impact on how the firm functions. Financial analytics makes this possible by analyzing the company’s financial data and revealing accurate and actionable insights drawn from various functions such as procurement, sales, and inventory management.

2. Market predictions: ‍

The financial space is a volatile sector that undergoes changes on a minute-to-minute basis. Companies can navigate these changes by making use of predictive analytics. These services are often powered by AI and machine learning algorithms which work more efficiently and perform deeper, more expansive analyses than human analysts. This helps enterprises stay on their feet when it comes to predicting the market.‍

3. Adaptability: 

In addition to market predictions, a company’s success is dependent on the ability to respond to uncertainties. Financial analytics forms an important part of this ability by helping spot market trends to reduce risks in real time. Additionally, the information drawn from these analytical tools allows for the creation of plans that reduce any uncertainty the firm may face in the future.

4. Process automation: 

Technology today has allowed for the integration of automation solutions across numerous organizational processes, and financial analytics is a key beneficiary of this phenomenon. By automating tasks and streamlining major finance processes, finance analytics solutions can take over repetitive tasks and prevent errors from occurring. This helps ensure that resources are efficiently utilized at all times within the firm.

5. Compliance: 

With regulations getting tighter as days go by, enterprises must ensure all their processes remain compliant. Finance analytics is an important part of this, as it ensures that all the information required to showcase compliance in the financial space is collected and organized for easy access. With better oversight, the occurrence of risks, penalties and instances of fraud can be minimized.

How Financial Analytics Works

With finance analytics serving several important functions, it is imperative that companies look to master it. Financial analytics follows a simple, linear path: first, disparate sources of data are brought together by the system. This data can be sourced both from within the organization as well as outside of it. 

The next step is to create a repository for this data after organizing and cataloging it. By creating a data warehouse, firms can have an overall view of the expanse of their business. 

The data analytics tool then parses the data for insights to create financial dashboards, market alerts, predictive sales analyses, cash flow valuations, forecasts, and more. 

All this information is presented in a readable, interactable manner to allow for maximum engagement and pattern recognition. Ultimately, by automating elements of the financial analytics process, deeper, more functionable insights can be drawn to power business decisions.

Types of Financial Analyses and Analytics

Understanding a company’s finances involves analyzing different types of data to evaluate the firm’s financial operations on the basis of set parameters. Some of the major types of financial analyses are:

1. Expense analysis: ‍

This involves the evaluation of a company’s spends across different departments over a given period of time. Itemized records of the company’s expenses are analyzed to determine their impact individually and then collectively. This delivers workable insights for better budget allocation and future market spends.  

2. Horizontal analysis: 

In this form of analysis, a company’s financial records over a period of time are compared side by side. This allows analysts to chart the trajectory of previously enacted financial strategies and observe any major shifts that may have taken place. Such an analysis allows for much faster course correction and sets the foundation for an evaluation of financial results at a later stage.

3. Vertical analysis: ‍

In vertical analysis, all aspects of financial statements are analyzed on a proportional basis. For example, every item on a balance sheet would be seen as a percentage of the total financial assets of the company. This sheds light on the distribution of impact for each item and enables adjustments as and when required.

4. Short-term analysis: ‍

Rather than look at the capital the company has generated in the long term, this type of analysis restricts itself to the working capital of a firm. Relevant data includes current inventory, accounts payable, and turnover rates for the received accounts. By shortening the time frame analyzed, aspects of finance that have the potential to cause long-term disruptions can be identified and subsequently rectified.

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Using different combinations of these analyses, various forms of data analytics in finance can be developed.

These types of analytics can be of use to provide insight into a company’s past, present, and future performance. Some of these analytics are:‍

1. Predictive analytics:

‍In this type of analytics, a combination of observable functions and past trends are evaluated to look for actionable insights. These insights take the form of market simulations that use statistical models to showcase what the future of the financial space will look like. This enables forecasting and economic projections as well. ‍

2. Prescriptive analytics:

‍Once the company is aware of the situation it is in, prescriptive analytics is used to find workable solutions that can alleviate issues or optimize performance. In this type of analytics, technologies such as ML and NLP are used to analyze data and recommend suitable courses of action based on the company’s preferred strategy.

3. Cash flow analytics:  

Here, data related to gains and expenditure are analyzed to determine capital ratio and cash conversion cycles. This gives the company an end-to-end view into how its finances work and allows for cash flow forecasting.

4. Profitability analytics:

‍This type of analytics uses data to evaluate financial behavior rather than processes. By examining how a company behaves in different scenarios, actions that contribute to greater profitability can be recognized and encouraged. Similarly, actions that lead to losses and market risks can be minimized.

Key Areas for Financial Analytics Implementation

Given its multiple functions and adaptable applications, financial analytics can be implemented in a host of different processes. Some of them have been listed below:

• Revenue analysis to determine growth and productivity
• Profit margin determination
• Operational efficiency testing
• Solvency analysis
• Performance tracking
• Budgeting and forecasting

Challenges With Financial Analytics

As with all technology, financial analytics solutions come with certain drawbacks. 

The primary concern revolves around the quality of data that the solution is given to work with. In many cases, organizations consist of complex data landscapes that are hard to navigate and generate data that is disorganized and difficult to standardize. This makes it difficult for AI and ML algorithms to analyze this data and deliver high quality results. 

To combat these issues, financial departments can opt for cloud-based financial analytics software that can integrate a wider variety of data types and sources. This addresses the issues of both data quality and data diversity. 

Historically, the predictive models used for market analysis have been complex and difficult to understand. They placed heavy workloads on manual analysts to generate actionable insights. However, by using ML and cloud-scale analytics, workflows can be automated and optimized to quickly provide readable dashboards that showcase insights on a single platform.

Gain the Savant Advantage

Organizations today are constantly on the lookout for tools that can provide the right insights for financial success. Modern financial analytics software must work to meet organizational demands and provide these insights. 

Savant’s cloud-native analytics automation solution integrates industry-leading technology into enterprises’ financial analytics processes to ensure they are always one step ahead of their competition.

To learn more about financial analytics and how your company can best utilize its advantages, contact our team today.