Pricing Optimization Unsecured Lending

Jane Zhong

Customer Knowledge & Insights

Scotiabank

Toronto Data Mining Forum

May 15, 2013

Page 2

Agenda

Who we are

What is pricing optimization

Project Initiative

Stakeholders

Analytical Solution

Pricing Solution

Lessons Learned

Questions

Page 3

Who We Are

Customer Knowledge & Insights

Enterprise

Data

Warehouse

Decision

Support &

Management

Market

Research

Predictive

Analytics

Customer

Analytics

Customer

Interaction

Management

Predictive Modeling:

Business/Sales Growth

Asset/Liability Management

Optimization:

Marketing Optimization

Pricing Optimization

Responsibility

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What is Pricing Optimization?

Upon product application, specific customer attributes are potentially used to determine a customer’s optimal price based on business objectives.

o Different pricing strategies could exist depending on the business

objectives. o Optimizing the trade-off between volume and profit within a set of

business constraints.

o Re-optimizing the pricing whenever necessary to maximize net revenue and manage the sales conversion.

A strategy of customizing pricing for each customer based on an understanding of its sensitivity to pricing.

This means…

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How Can Pricing Optimization Help?

Pricing optimization is

enabling bank executives to use pricing as a strategic weapon to meet their corporate objectives and to become more customer-centric in their decision making.

Dr. Robert L. Phillis

Founder &

Chair Science Officer

Nomis Solutions

Page 6

Project Initiative

Background

Unsecured lending is a key component of the retail bank.

Our existing approach relied on broad risk-based pricing and discretion.

However, this approach had resulted in fewer sales and lower profit

Business Case

Similar to the best practices in the industry, apply dynamic pricing optimization technique for pricing decision.

Leverage our internal expertise to build a pricing optimization framework in house.

Build a process that regularly monitors segment level sales to re-optimize our pricing and maximize the overall product profit.

With a modest investment in IT, complex pricing optimization techniques can be simplified for practical deployment within our sales channels.

Until we incorporate customer relationship fully within the pricing model, pricing discretion capabilities will remain an option.

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How will it Happen?

Enterprise Data Warehouse

Builder of data mart to store

pricing solutions and interactions

for monitoring, reporting and

further enhancements

Information Technology Solutions

Builder of the “generic” pricing engine and

system enhancements that will provide individual

customer pricing decision

Branches

Decision Support & Management

Provider of pricing solutions through

predictive analysis & optimization to

determine the factors & parameters which

will drive the pricing decision

Call Center

Online

Page 8

Stakeholders

Project Sponsor: Unsecured Lending

Solution Provider: Decision Support & Management

Data Provider: Enterprise Data Warehouse Business Requirement: Integrated Business Solution

System Development: IT&S

Price Execution: Channels

Customer Experience

Risk Management

Audit

Compliance

Page 9

Scenario

Creation

Scenario/Pricing

Signoff

Price

Publishing

Price

Execution

Performance

Monitoring

Pricing

Strategy

Analyze planned

vs. actual results,

update models and

reports to for better

performance

Performance

Monitoring

?

ANALYTICS

Simulate, optimize,

and collaborate to

develop pricing

scenarios for

evaluation

Scenario

Creation

?

Business objective

Strategic Focus

Market Change

Competitors

Pricing

Strategy

?

Data driven

proposals to adjust

pricing for changes

in the market,

and/or our

business goals

Scenario and

Pricing

Signoff

?

Automate the

publishing of prices

and store an

auditable record of

pricing decisions

Price

Publishing

?

Optimize

negotiation ranges,

and offers and

tracking and

incorporating

pricing discretion

Price

Execution

?

Pricing Process

Page 10

Analytical Framework

Booking Models

Attrition Models

Utilization Models

Loss Models

Customer data

Account data

Pricing

Optimization

Platform

Reporting

Monitor/Track

App Data

Risk Data

Pricing Solution

Business Line Signoff

Price Engine

Page 11

Analytical Methodology

To identify major pricing factors by building different customer behavior models

Booking Sensitivity Model

Account Attrition Model

Limit Utilization Model

Loss Model

To build sensible pricing segments on business objective

Combine business sense and scientific study

Customer homogeneity

To deliver better pricing solution by using optimization

Maximize life-time product profit and satisfy certain constraints:

Improve booking ratio

Maintain loss ratio

Improve booking mix of profitable customers

Improve profit from certain customer segments

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Pricing Solution

Price

H H M M L L H H M M L L H H M M L L H H M M L L H H M M L L Y N Y N Y N Y N Y N Y N Y N Y N Y N Y N Y N Y N Y N Y N Y N 5 5 5 5 5 5 4 4 4 4 4 4 3 3 3 3 3 3 2 2 2 2 2 2 1 1 1 1 1 1

New Price for A Old Price for A New Profit for B Old Profit for B New Price for C Old Price for C

New Price vs Old Price

Profitability orientation not volume orientation

Multiple pricing factors vs. sole pricing factor

Stay competitive within the unsecured lending market

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Lessons Learned

Pricing evolution as opposed to revolution – make small steps

Time to market is a key

Phased approach provides immediate benefit while gaining executive supports

Need more experts with end-to-end knowledge

Build robust methodology and flexible infrastructure

Work around limitations and control the controllables

Data doesn’t lie and let the number talk first

Identify data gap and collect more relevant data

Need sufficient price driven behavior data to quantify price elasticity

Marry business sense and scientific study for customer segments

Models will need periodically calibration for market volatility

Re-define pricing strategy to align with business objectives and market

Pricing is a key strategic weapon and should continue to be invested

Page 14

Thank You !