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.
In today’s competitive market for financial services, customers have many options. Utilization of your historical data is, or will become, one of your company’s competitive differentiators. Analytics is used to identify the characteristics of your “best” (most profitable and most loyal) customers.
The StatSoft predictive analytics platform for banking integrates with your existing data warehouses and repositories. Increase products per customer and profitability with insights about the right offer, the timing of that offer, and level of service. These recommendations are delivered to your financial consultants, customer service representatives, risk analysts, platform bankers, tellers, and marketing professionals.
A first step in increasing wallet share and loyalty with your best customers is to understand them. Your company already has the answers to the following questions embedded within historical data:
Our solutions will help you uncover these previously hidden relationships. Answers to the above questions and many others become the foundation of multi-channel programs to increase wallet share and customer retention. An understanding of your customers, through analytics, empowers all functions across your organization. Deliver the right level of customer service to increase products per customer and increase profits. These same insights also become the cornerstone of effective customer acquisition programs to target and attract loyal and profitable new customers.
With STATISTICA, the tasks of building and deploying scorecards, scoring models, and flows can now be completed in a fraction of the time, allowing more models to be managed and routinely recalibrated. More customers can be approved for credit with higher limits, without increasing the default rate. Batch scoring of all customers and accounts will be faster, and real-time scoring for on-line or other real-time applications will be more responsive.
The STATISTICA Decisioning Platform® addresses the typical array of challenges for medium and large financial services organizations:
The STATISTICA Decisioning Platform addresses these needs by:
The STATISTICA Decisioning Platform is the only enterprise predictive analytics and decision management software platform:
That combines predictive analytics, text mining, and rules to cover all aspects of evaluating and scoring claims, customers, and applicants. Text mining is beneficial for making use of adjuster notes, medical reports, and other documents. Rules integrated with predictive models translate predictions into business decisions.
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.
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.
Management and Validated Compliance Solutions for the Banking Industry (Basel II)
With the New Basel Capital Accord of 2001 (BASEL II) the banking industry is faced with new regulatory challenges, as well as opportunities to fine tune the measurement and management of operational risk.
The three pillars of BASEL II are measurement of minimum capital requirements, supervisory review, and market discipline. To achieve BASEL II compliance requires that financial institutions build a secure and robust data analysis and reporting system that can be validated and controlled (e.g., version control of reports), and provides role-based security (so that only certain individuals can create data queries, report templates, and so on) and audit trails for review by regulatory agencies.
The STATISTICA Enterprise Analytics platform provides the ideal solution that will allow financial institutions to move forward with confidence: The STATISTICA solution for general data analysis, modeling, and reporting is based on proven and mature technologies that are currently deployed in regulated industries worldwide.
Here is what sets the STATISTICA solution apart from other "spot-solutions" or proprietary and expensive data warehouse solutions:
Contact StatSoft for details and a demonstration of this unique analytics platform designed specifically to support mission critical applications in regulated industries.
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'sCluster 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 asmultidimensional 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.