knowledge discovery

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Knowledge Discovery. In Currency Risk Management. Goal. Increase Profit Reduce Cost of Settlements Increase Customer Satisfaction Reduce Bank Risk Reduce Capital Requirements. Domain. FX Trading System Relational Database 6000 Customers 400,000 FX Transactions Demographic Information - PowerPoint PPT Presentation

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Knowledge DiscoveryIn Currency Risk Management

Goal

• Increase Profit

• Reduce Cost of Settlements

• Increase Customer Satisfaction

• Reduce Bank Risk

• Reduce Capital Requirements

Domain

• FX Trading System Relational Database

– 6000 Customers

– 400,000 FX Transactions

– Demographic Information

– Credit Information

• FX Marketing Desk Customer Info Database

– Marketer

– Relationship Manager

– Pricing Information

Foreign Exchange Primer

• Spots and Forwards

• Swaps

• Window Options and Draw Downs

• Multi-currency Accounts

• Settlements

• Customer Credit

• Bank Risk

Methodology

• Action Rules are discovered to meet our Goals.

For Example:

Geography( Canada ) AND CreditLine( NO -> YES)

=> customerRating( Average -> Good )

• Confidence = 100%

• Support = 52 Customers

Methodology

• Data Extraction– SQL

– Statistical Attributes

• Data Nominalization– SQL

– Range Mapping based on Domain

Knowledge and Visualization

• Data Reduction– SQL

– 6,000 Customers to 2,500

Trad ingS ystem

C ustom er In foS ystem

C onso lida teedD ata

N om ina lizedD ata

Methodology

N om ina lizedD ata

R osetta

S upportingA ssocia tion

R ules

• Rosetta

– Reducts

– Association Rules

– Filtering

Methodology

• Custom Application

– Flexible versus Static Attributes

– Association Rule combination

– Filtering

S upportingA ssocia tion

R ules

S upportingA ction R u les

Action.java

Results

• Spot-rating is Strongly correlated to the decision

Attribute.

– Spot-rating as flexible attribute ( 1058 Action Rules )

– Spot-rating as static attribute ( 99 Action Rules )

• Improving Spot-rating improves Customer-rating

Results

• Some Customers would be more profitable by

doing business with a CRM Interface Partner

– 120 Supporting Customers

– Static• Spot-rating = GOOD

• Swap-volume = NONE

– Flexible• primaryDealsrc( Direct -> (9 other partners)

– Decision• BAD -> AVERAGE

Results

• Some Customers would be more profitable by

recovering settlement cost.

– 118 Supporting Customers

– Static• Spot-rating = GOOD

• Swap-volume = NONE

• Geography = US

• Customer Type = Corporate

– Flexible

• Settlement-volume( Medium -> low or high )

– Decision

• BAD -> AVERAGE

Results

• Marketer EBF Could do Better

– 68 Supporting Customers

– Static• Spot-rating = GOOD

• Swap-volume = NONE

• Geography = US

– Flexible

• marketer( EBF -> {13 other} )

– Decision

• BAD -> AVERAGE

Results

• Marketer BKG Could do Better

– 49 Supporting Customers

– Static• Spot-rating = EXCELLENT

• Swap-volume = NONE

• Geography = US

– Flexible

• marketer( EBF -> {5 other} )

– Decision

• AVERAGE -> GOOD

Next Steps

• More holistic view of Profit & Loss of the

products

• More attributes--less derived attributes

• Filter change to find rules with the most financial

impact support, not number of customers

supporting

• Use methodology for continuous attributes to

yield a more precise actions to take. E.g, increase

spread from 3.2% to 3.4% to increase profitability

by 5%

Questions?Thank You

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