What is data mining solution?

Data mining is a technique to excavate knowledge and rule effective to business with statistical analysis.
Our consultant with abundant experience on analysis work analyzes enormous data inside office & in the market to support your business promotion in visualizing and indexing necessary information for decision making.

Characteristics

・Practical analysis based upon abundant experience on analysis work and business knowledge .
・Analysis to comply with clients’ requirement with a variety of tool(SAS, SPSS, R, Python, etc.,.) and
method(deep leaning, logistic recursion, tree analysis,etc.,.).
・Total support from data extraction ~ analysis till establishing solution.

Targeting Clients

Credit Risk Management

Client needs prediction of probability of borrower’s default and its uncollectability as well as efficiency of receivable collection with priority ranking.

Marketing

Sales promotion of financial instruments as loan & investment trusts according to purchasing pattern.
Recommendation for customers’ preferred merchandise based upon access log on web site.
Client needs prediction of & countermeasure against defectors in current customers as cancellation. etc.

Revenue Management

Evaluation of housing loan asset.
Revenue prediction for new product in using simulation based upon volume of potential customers and merchandise condition.
Client necessary to maximize revenue (revenue management;RM) for hotel and golf links based upon played days/time zone/climate.

Our Solutions

Data Mining for Credit Risk Management

For loan risk management, totally supporting to from listing up current tasks, credit risk model establishment,monitoring till tuning .

Data Mining on Marketing

Totally supporting to data mining analysis for realizing esfficinet marketing such as effective campaigning.

Data Mining on Revenue Management

Supporting to grasping revenue risk and establishing revenue maximizing policy .

Consulting Done

Initial Credit Control Model of Housing Loan

Case 1: Major Banks, Local Banks, Trust Banks.

overview
・Established housing loan credit risk model to realize quantification of the credit risk.
・Established examination rule for minor customer segment to which is hard to get their financial picture
in the credit risk model.
・Established revenue model to simulate profitability after housing loan effected.

Establishing Marketing Strategy Model

Case 2: A Local Bank

Defining growth pattern of customers in retail banking (increase /develop of account corresponding to life stages) by means of data mining for segmentation of customers as revenue resource of bank. Clarification by customers segment-wise of necessary policy to lead to revenue increase with the analysis upon data mining.。

Recent Contributions/Seminar Lecturers

12 Feb.2009
•Problem of Use of Scoring Model for Examination of Personal Loan
•New Fiance Magazine, Feb. Issue , Regional Finance Study Institute.

Utilization Method of Selection Rule of Targeted Merchandise as a Business
Opportunity based upon Topics Information.

Apr.2009
•Characteristic & Problems of Scoring Examination ~ Domain of Examination of Housing Loan
Finance Compliance Magazine, Apr. Issue, Bank Training Company.
•Establishing Verification Method and Management System of Revenue on Housing Loan
Finance Compliance Magazine, Sept. Issue, Bank Training Company

Jun.2009
•Cyber Brain Monthly, Jun. Issue, Analysis Pointsof Customers with Access Information to Web
Monthly Magazine, Finance Business Promotion Department, NTT Data

Seminar Lecturers

Recent Trend of Housing Loan Promotion by Regional Finance Institutions
Brainy Works Seminar
Risk Control Method of Retail Loan
Brainy Works Seminar
Precaution on Utilization of Scoring Model
Financial System Study Institute(Kinzai) Seminar
Upgrading Policy of Revenue Management of Bank Housing Loan
FIT2009SAP Company’s Seminar
Regional Finance Institute’s Current Problems for Use of Information & Direction for its Solving with BI
Finance System Study Institute(Kinzai) Seminar