银行业之解决方案
Predictive Modeling Solutions for Banking Industry
To understand customer needs, preferences, and behaviors, financial institutions such as banks, mortgage lenders,
credit card companies, and investment advisors are turning to the powerful data mining techniques in
STATISTICA Data Miner.
These techniques help companies in the financial sector to uncover hidden trends and explain the
patterns that affect every aspect of their overall success.
Financial institutions have long collected detailed customer data - oftentimes in many disparate databases and in
various formats. Only with the recent advances in database technology and data mining software have financial
institutions acquired the necessary tools to
manage their risks using all available information, and exploring a wide
range of scenarios. Now, business strategies in financial institutions are developed more intelligently than ever before.
Credit Scoring and Risk Management
STATISTICA Credit Scoring aids with the development, evaluation and monitoring of scorecard models.
Fraud Detection
Banking fraud attempts have seen a drastic increase in recent years, making fraud detection more important than ever.
Despite efforts on the part of financial institutions, hundreds of millions of dollars are lost to fraud every year.
STATISTICA Data Miner helps banks and financial institutions to anticipate and quickly detect fraud and take
immediate action to minimize costs. Through the use of sophisticated data mining tools, millions of transactions can
be searched to spot patterns and detect fraudulent transactions.
Identify causes of risk; create sophisticated and automated models of risk.
- Segment and predict behavior of homogeneous (similar) groups of customers.
- Uncover hidden correlations between different indicators.
- Create models to price futures, options, and stocks.
- Optimize portfolio performance.
Tools and Techniques
STATISTICA Data Miner will empower your organization to provide better services and enhance the profitability of all
aspects of your customer relationships. Predict customer behavior with
STATISTICA Data Miner's
General Classifier and Regression
tools to find rules for organizing customers into classes or groups. Find out who your most profitable,
loyal customers are and who is more likely to default on loans or miss a payment. Apply state-of-the-art techniques to
build and compare a wide variety of linear,
non-linear, decision-tree based, or
neural networks models.
Recognize patterns, segments, and clusters with
STATISTICA Data Miner's
Cluster Analysis options and Generalized
EM (Expectation Maximization) and K-means Clustering module. For example, clustering methods may help build a
customer segmentation model from large data sets. Use the various methods for mapping customers and/or
characteristics of customers and customer interactions, such as
multidimensional scaling, factor analysis,
correspondence analysis, etc., to detect the general rules that apply to your exchanges with your customers.
STATISTICA Data Miner's powerful
Neural Networks Explorer offers tools including classification, hidden structure
detection, and forecasting coupled with an Intelligent Wizard to make even the most complex problems and advanced
analyses seem easier.
Uncover the most important variables from among thousands of potential measures with Data Miner's Feature
Selection and Variable Filtering module, or simplify the data variables and fields using the Principal Components
Analysis or Partial Least Squares modules.
Advanced forecasting methods
STATISTICA Data Miner also features
Linear and Nonlinear Multiple Regression with link functions,
Neural Networks
, ARIMA, Exponentially Weighted Moving Average, Fourier Analysis, and many others. Learn from the data
available to you, provide better services, and gain competitive advantages when you apply the absolute state-of-the-art
in data mining techniques such as generalized linear and additive models,
MARSplines,
boosted trees, etc.