Data mining and financial data analysis


Most marketers understand the value of collecting financial data, but also recognize the challenge of using that knowledge to create intelligent, proactive paths back to the customer. Data mining — technologies and techniques for identifying and tracking patterns in data — helps companies sift through layers of seemingly disjointed data for meaningful relationships in which to anticipate, rather than just react to, customer needs and financial needs. In this accessible introduction, we provide a business and technological overview of data mining and outline how data mining, coupled with sound business processes and complementary technologies, can empower and redefine financial analysis.


1. The main objective of mining techniques is to discuss how bespoke data mining tools should be developed for analyzing financial data.

2. Usage patterns related to the purpose can be categories corresponding to the need for financial analysis.

3. Development of a tool for financial analysis through data mining techniques.

Data mining:

Data Mining is the process of extracting or mining knowledge from large amounts of data, or we can say Data Mining is “Knowledge Mining for Data” or we can also say Knowledge Discovery in Database (KDD). Means data mining: data collection, database creation, data management, data analysis and understanding.

There are some steps in the process of knowledge discovery in the database, such as:

1. Data cleaning. (To remove nose and inconsistent data)

2. Data integration. (Where multiple data sources can be combined.)

3. Data selection. (When data relevant to the analysis task is retrieved from the database.)

4. Data Transformation. (Where data is transformed or consolidated into forms suitable for mining, for example by performing summarization or aggregation operations)

5. Data mining. (An essential process that uses intelligent methods to extract data patterns.)

6. Sample Evaluation. (To identify the really interesting patterns that represent knowledge based on some interesting measures.)

7. Knowledge Presentation. (Here visualization and knowledge representation techniques are used to present the knowledge gained to the user.)

data warehouse:

A data warehouse is a repository of information collected from multiple sources, stored under a consistent schema, and typically resides in a single location.


Most banks and financial institutions offer a variety of banking services such as: B. Checking, savings, business and individual customer transactions, credit and investment services such as mutual funds, etc. Some also offer insurance services and stock investment services.

There are different types of analysis available, but in this case we want to give an analysis known as “evolution analysis”.

The data evolution analysis is used for the object whose behavior changes over time. Although this may involve characterization, distinction, association, classification, or clustering of time-related data, we can say that this evolutionary analysis is done through time-series data analysis, matching of sequence or periodicity patterns, and similarity-based data analysis.

The data collected in the banking and financial sector is often relatively complete, reliable and of high quality, which offers opportunities for analysis and data mining. Here we discuss some cases such as

Eg 1. Suppose we have stock market data available for the last few years. And we want to invest in stocks of the best companies. A data mining study of stock market data can identify regularities in stock performance for overall stocks and for the stocks of specific companies. Such regularities can help predict future trends in stock market prices and inform our stock investment decision-making.

Eg 2. One may want to display the change in debt and income by month, by region and by other factors along with minimum, maximum, total, average and other statistical information. Data warehouses, which provide the capability for comparative analysis and outlier analysis, all play an important role in financial data analysis and mining.

Eg 3. Loan payment prediction and customer credit analysis are critical to the bank’s business. There are many factors that can greatly affect loan payment performance and customer creditworthiness. Data mining can help identify important factors and eliminate irrelevant factors.

Factors related to loan payment risk such as loan term, leverage ratio, payment to income ratio, credit history and more. The banks then decide whose profile shows relatively low risks according to the critical factor analysis.

With financial analysis software, we can complete the task faster and create a more sophisticated presentation. These products condense complex data analysis into easy-to-understand graphical representations. And there’s a bonus: such software can take our practice to a more advanced management consulting level and help us attract new clients.

To help us find a program that best suits our needs and budget, we’ve examined some of the leading packages, which vendors estimate account for more than 90% of the market. Although all packages are marketed as financial analysis software, they do not have all the features needed for comprehensive analysis. It should allow us to offer our customers a unique service.

The products:

Designed for small and medium-sized businesses, ACCPAC CFO (Comprehensive Financial Optimizer) can help make business planning decisions by modeling the impact of different options. This is accomplished by demonstrating the what-if results of small changes. A roll-forward function creates budgets or forecast reports in minutes. The program also generates a financial scorecard with key financial information and indicators.

Customized Financial Analysis by BizBench provides financial benchmarking to determine how a company compares to others in its industry using the Risk Management Association (RMA) database. It also highlights key metrics that need improvement and a year-over-year trend analysis. A unique feature, Back Calculation, calculates profit targets or the equivalent asset base to support existing sales and profitability. DuPont model analysis shows how each metric affects return on equity.

Financial Analysis CS reviews and compares a client’s financial position against business peers or industry standards. It can also compare multiple locations of a single business to determine which are the most profitable. Users subscribing to the RMA option can integrate with Financial Analysis CS, which allows them to then provide aggregated financial indicators from competitors or industry standards that show clients how their companies are performing.

iLumen regularly collects a customer’s financial information to provide ongoing analysis. It also provides benchmarking information, comparing the client’s financial performance to industry peers. The system is web based and can monitor a client’s performance on a monthly, quarterly and yearly basis. The network can upload a sample balance file directly from any accounting software program and provide charts, graphs and ratios that demonstrate a company’s performance for the period. Analysis tools are displayed via customized dashboards.

New Horizon Technologies’ PlanGuru can create out-of-the-box integrated balance sheets, income statements, and cash flow statements. The program includes tools for analyzing data, making forecasts, forecasting and budgeting. It also supports multiple resulting scenarios. The system can calculate up to 21 financial ratios as well as the breakeven point. PlanGuru uses a spreadsheet-style interface and wizards to guide users through data entry. It can be imported from Excel, QuickBooks, Peachtree and plain text files. It is available in Professional and Consultant editions. An add-on called Business Analyzer calculates benchmarks.

ProfitCents by Sageworks is web-based and therefore requires no software or updates. It integrates with QuickBooks, CCH, Caseware, Creative Solutions and Best Software applications. It also offers a variety of business analytics for nonprofit organizations and sole proprietorships. The company offers free consulting, training and customer support. It is also available in Spanish.

ProfitSystem fx Profit Driver by CCH Tax and Accounting offers a wide range of financial diagnostics and analysis. It provides data in tabular form and can calculate benchmarks against industry standards. The program can track up to 40 periods.