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Data Mining and Financial Data Analysis
Most marketers understand the value of collecting financial data, but also understand the challenges of using that knowledge to create intelligent, proactive paths back to the customer. Data mining – technologies and techniques for recognizing and tracking patterns in data – helps businesses sift through layers of seemingly unrelated data for meaningful relationships where they can anticipate, rather than simply react to, customer and financial needs. In this accessible introduction, we provide a business and technology overview of data mining and show how, together with robust business processes and complementary technologies, data mining can enhance and redefine financial analysis.
1. The main purpose of the methods of intellectual analysis is to discuss how to develop individual tools for the analysis of financial data.
2. The pattern of use in terms of purpose can be a category according to the need of financial analysis.
3. Develop a tool for financial analysis using data mining techniques.
Data mining is the procedure of extracting or mining knowledge for large amount of data or we can say data mining is “Knowledge Mining for Data” or we can say Knowledge Discovery in Database (KDD). Data mining means: data collection, database creation, data management, data analysis and understanding.
There are several steps in the knowledge discovery process in a database, e.g
1. Data cleaning. (To remove nose and conflicting data)
2. Data integration. (Where multiple data sources can be combined.)
3. Data selection. (Where the data relevant to the analysis task is retrieved from the database.)
4. Data conversion. (When data is transformed or consolidated into forms suitable for mining by performing summarization or aggregation operations, for example)
5. Intelligent data analysis. (A process that uses intelligent techniques to extract data patterns is required.)
6. Pattern evaluation. (To identify really interesting models that represent knowledge based on some interesting metrics.)
7. Presentation of knowledge. (Visualization and knowledge representation techniques are used to present the acquired knowledge to the user.)
A data warehouse is a repository of information collected from a variety of sources, stored in a common schema, and usually located at a single site.
Most banks and financial institutions offer a wide range of banking services such as checking, savings, business and individual transactions, credit and investment services such as mutual funds, etc. Some also offer insurance and stock investment services.
There are different types of analysis, but in this case we want to provide one analysis known as Evolution Analysis.
Data evolution analysis is used for an object whose behavior changes over time. Although this may involve characterizing, discriminating, associating, classifying or clustering time-related data, it means that we can say that this evolutionary analysis is carried out through time series data analysis, sequence pattern matching or periodicity and similarity-based data analysis.
The data collected in the banking and finance sectors is often relatively complete, reliable and of high quality, providing opportunities for data analysis and mining. Here we discuss several cases like,
For example, 1. Suppose we have stock market data for the past few years. And we would like to invest in stocks of the best companies. Investigating stock exchange data mining can identify patterns in the evolution of stocks as a whole and for stocks of individual companies. Such patterns can help predict future trends in stock market prices, helping inform our stock investment decisions.
For example, 2. You can view changes in debt and income by month, by region, and by other factors, along with minimum, maximum, total, average, and other statistical information. Data warehouses that enable benchmarking and outlier analysis play an important role in financial data analysis and mining.
For example, 3. Loan payment forecasting and customer creditworthiness analysis are critical to the bank’s operations. There are many factors that can greatly affect the performance of loan payments and a customer’s credit rating. Data mining can help identify important factors and eliminate irrelevant ones.
Factors related to the risk of loan payments, such as the term of the loan, debt-to-income ratio, payment-to-income ratio, credit history, and many others. Banks then decide whose profile shows relatively low risks according to the critical factor analysis.
We can complete the task faster and create a more sophisticated presentation with the help of financial analysis software. These products condense complex data analysis into easy-to-understand graphical presentations. And there is a bonus: such software can take our practice to a more advanced level of business consulting and help us attract new clients.
To help us find the program that best fits our needs and our budget, we’ve researched some of the leading packages that vendors estimate make up more than 90% of the market. Although all packages are marketed as financial analysis software, not all of them provide all the features required for full-spectrum analysis. This should enable us to provide unique services to customers.
ACCPAC CFO (Comprehensive Financial Optimizer) is designed for small and medium-sized enterprises and can help make business planning decisions by simulating the impact of different options. This is achieved by demonstrating the results of small changes every now and then. The roll-ahead feature prepares budgets or forecast reports in minutes. The program also creates a financial scorecard of key financial information and metrics.
A custom financial analysis from 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 ratios that require improvement and an annual trend analysis. The unique Back Calculation feature calculates a target profit or an appropriate asset base to support existing sales and profitability. An analysis of the DuPont model demonstrates how each ratio affects return on capital.
CS financial analysis examines and compares a client’s financial position to business peers or industry standards. It can also compare multiple locations of the same business to determine which are the most profitable. Users who subscribe to the RMA option can integrate with Financial Analysis CS, which then allows them to provide peer or industry benchmark financial summary, showing clients how their business compares.
iLumen regularly collects customer financial information for ongoing analysis. It also provides comparative information by comparing the client’s financial performance with industry peers. The system is web-based and can monitor client performance on a monthly, quarterly and annual basis. A trial balance file can be uploaded to the network directly from any accounting software and charts, graphs and ratios can be provided that show the company’s performance over a period. Analysis tools are viewed through customized control panels.
New Horizon Technologies’ PlanGuru can create client-ready integrated balance sheets, income statements, and cash flow statements. The program includes tools for data analysis, forecasting, forecasting and budgeting. It also supports multiple output scripts. The system can calculate up to 21 financial ratios, as well as the break-even point. PlanGuru uses a spreadsheet-style interface and wizards that guide users through data entry. It can import from Excel, QuickBooks, Peachtree and plain text files. It comes in professional and advisory editions. An add-on called Business Analyzer calculates benchmarks.
ProfitCents by Sageworks is web-based, so no software or updates are required. It integrates with QuickBooks, CCH, Caseware, Creative Solutions and Best Software. It also provides a wide range of business analysis for non-profit organizations and sole traders. The company offers free consultation, training and customer support. It is also available in Spanish.
ProfitSystem fx Profit Driver from CCH Tax and Accounting provides a wide range of financial diagnostics and analytics. It provides data in the form of spreadsheets and can calculate comparisons with industry standards. The program can track up to 40 periods.
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