Vision 2014: Regain Confidence With Pricing Optimization

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Regain confidence with pricing optimization

Danna Gurbaxani Experian

Craig Wilson Experian

#vision2014

2 © 2014 Experian Information Solutions, Inc. All rights reserved. Experian Public.

Lending challenges

Evolution of pricing

The basics of pricing optimization

Benefits and Experian’s pricing solutions

Next steps and conclusions

Agenda


Lending challenges


Political and regulatory threats to long-term revenue

Ability to adapt to changing regulation

Pressure on non-interest income

► Card Act regulations impacting non-interest income

Political pressure on usage of financial products

► Public statements challenging financials of credit cards and need for consumer transparency

Lending challenges

Political and regulatory

uncertainty

Growth in a saturated

market Loan performance


Methods to increase approval rates and to sustain growth trends

New pockets of opportunity for growth (near prime segments)

Saturated market

► Maximizing lending opportunities with existing customers

Near prime segments

► New methods to extend potential customer base

Lending challenges


uncertainty




Exceptionally low delinquency rates and bad rates

Responsible growth: Balance of revenue growth and loan performance

Loan performance

► Number of debtors is not increasing

► Loan amounts are increasing

Lending challenges


uncertainty




Implications for pricing

Political and

regulatory

uncertainty

Reduce dependency on non-interest income

Pricing techniques to maximize income potential in constrained regulatory environment

Flexible approach to pricing to accommodate new regulation !

Growth in a

saturated market

Identify higher risk pockets of opportunity but price accordingly

Grow profits through efficient pricing in times of difficult volume growth

!

Loan performance

Responsible growth: Grow volumes without increasing risk exposure

Understand near prime customers and price to off-set increased risk

!

Conclusions

Need for flexible pricing techniques due to uncertain regulatory changes

Need for efficient pricing to drive sustained growth

Need for smart pricing for responsible growth !


Evolution of pricing


Evolution of pricing Increasing analytical sophistication

One price Product-

based pricing

Relationship-

based pricing

Risk-

based pricing

Pricing

optimization

Price structure

One-size-fits-all

price

Product rate

sheet

Differentiation by

product features

Product rate

sheet with

specified

discounts

Computed price

by customer or

risk segment

Optimized price

by customer

Pricing decisions

Competition driven

Price floors by

portfolio risk

Competition driven

Price floors by

product-level risk

Limited

segmentation

Broker/dealer

discounts

Customer status

Product bundling

Risk-adjusted

return hurdles

Customer-level

or segment-

level

Builds on risk-

based pricing

Predictive

analytics

Optimised

customer-level

decisions


Risk-based Pricing

A: Higher prices for higher-risk

customers

Lower prices for lower-risk

customers

Can be integrated with Basel

capital allocation initiatives

Q: Difference between Risk-based Pricing and pricing optimization?

Price variation

– different

prices by risk


Implications for customers and performance

Price and risk Risk performance vs. market pricing

Market price

Risk

Low risk customers are

over-charged: Damages

volumes and relationships

High risk customers are

under-charged or not served:

Unprofitable, subsidized by low

risk customers

Price

Risk

based pricing


Pricing optimization

Price levels –

Right price for

each customer

or segment

A: Strategic use of pricing to

better manage performance

Pricing for performance

(profits, volume)

Pricing for control (regulatory

constraints)

Q: Difference between Risk-based Pricing and pricing optimization?


The basics of pricing

optimization


Optimization to set the right prices In one sentence

Maximize your business goals (such as EVA, risk-adjusted profit, origination volumes)

By determining the best decision for each customer or segment (such as which APR, fees, margin above index)

Based on the forecasts of your underlying data and predictive models (such as RAROC, take-up rate models, loss models)

While satisfying the constraints of your business (such as eligibility, capital availability, channel capacity)

Optimization enables you to:


Demand-side:

Willingness to buy

Price

Vo

lum

e

Supply-side:

Willingness to sell

Price

Pro

fit

Unified view of

pricing

What are the trade-offs

between volume, profit

(and other KPI’s) as

price changes?

Volume

Pro

fit

The fundamental principles of pricing: Understanding supply and demand

How do costs and profitability change

as price changes?

How many customers will we

acquire/retain as price changes?


Demand-side:

Willingness to borrow

Price

Vo

lum

e

Supply-side:

Willingness to lend

Price

Pro

fit

Unified view of

pricing

Volume

Pro

fit

Supply and demand The basics applied to retail lending

What is the expected take-up rate for

each loan/customer as price changes?

What is the risk-adjusted return for

each loan/customer as price changes?

What are the trade-offs

between volume, profit

(and other KPI’s) as

price changes?


Understanding willingness-to-lend Breaking down the problem

Revenue

Interest income

Fees

Other revenues

Adjustments

+

+

+ / -

Cost

Cost of funds

Operating costs

Expected losses

Cost of

economic capital

+

+

+

Economic profit = revenue – cost

Expected losses

Cost of

economic capital

Both are a

function of risk


Decomposing RAROC

Refining the framework Risk-adjusted return on capital

How much profit can

we make (in $ / £ /€)?

How efficiently do we

make the profit relative

to the capital we must

put aside?

Economic

profit

Economic

capital

RAROC

From BII A-IRB

approach or VaR

model

Risk adjusted

return on risk

adjusted

capital

Revenue Costs

=

–


Price-sensitivity at origination (example modelling structure)

Understanding willingness-to-buy Measuring consumers’ price-sensitivity

Acquisition funnel

Market size (macroeconomic conditions and rates)

Market share (headline rates and lending policy)

x

Approval rates (lending criteria)

x

Product selection (x-product rates, macro conditions)

x

Expected

originations =

Take Up (offered rate)

x Greatest driver of

price-sensitivity at

origination


From insights to execution Estimating the impact of pricing decisions

Customer A Customer B Customer C Customer D

For each set of rates,

we can add the model

predictions to estimate

the overall profit,

volumes and other

KPI’s (risk, etc) Total volume

To

tal p

rofit


From insights to execution Estimating the impact of pricing decisions

Customer A Customer B Customer C Customer D

Unified view of

pricing

Evaluating all the

different rate

combinations predicts

the possible outcomes

Total Volume

To

tal P

rofit

Efficient frontier


If the bank has unlimited capital and no operational constraints, then price to maximize expected return for each customer

Reality is more complex with many constraints on pricing and acceptable growth

Pricing theory vs. reality Understanding constraints


Types of constraints

Eligibility

► Who is eligible for the loan?

Capital availability

► How much total capital do I have available?

► How much capital do I have available by product or other grouping?

Competition

► Do I want to keep my prices within a window of competitors’ prices?


Capital

availability


Solution space

Types of constraints

Controlled growth

► Do I want to control the composition of my growth?

► By term, risk, geography or other attributes?

KPI targets

► Do I have multiple goals I need to achieve?

► Market share and profit? Risk and return?


KPI

targets

Capital

availability

Controlled growth


Benefits and

Experian’s pricing

solutions


Implications for pricing

Political and

regulatory

uncertainty

Flexible approach to adapt to changing regulation

Financial benefits to off-set threats to long-term revenue

Increases of 33% in profit, >100% in EVA and RAROC

Growth in a

saturated market

Increase amount booked through higher approval rates and

take-up rates

4% increase in amount booked

Loan performance

Grow responsibly

Increase profits and volumes while controlling for risk

Reductions of 8% - 18% in bad rates

Conclusions

Flexible pricing techniques due to regulatory changes

Efficient pricing to drive sustained growth

Smart pricing to grow volumes without growing risk

Challenges Benefits of pricing optimization


Experian’s modular approach The four building blocks

Technology

Optimization solutions

► Marketswitch® for

individual-level decisions

► Strategy Tree Optimization

for segment/tree-level decisions

Delivered as service or as a

software product

Technology

Consulting

RAROC and profit model

consulting

Industry consulting (e.g.,

regulation trends, risk-based

pricing adoption study)

Optimization consulting

Consulting

Data

Data

Data readiness assessment and

recommendations

Partner with third-party ETL

vendors for data

transformation efforts

Analytics

Analytics

Custom model development

► Take-up models, demand

estimation models,

cannibalization models

► Profit model assumptions

(loss forecasting, etc)


Next steps and

conclusions


Multi-phase approach Perfection is not a pre-requisite to optimization

Phase I:

Proof-of-concept

Benefit

Com

ple

xity Phase II:

Implementation

Phase III:

Increased sophistication

Illustration Only

Limited scope and easy to

implement

First generation models and

data (existing or proxy models)

Develop additional models

Increase scope

Refine operational

processes

Transition to real-time (as

appropriate)

Additional scope, models,

decision points


Conclusions

Pricing at the

root of

challenges

Regulation: Need flexible approach to pricing

Growth opportunities: Identify pockets of opportunity

Loan performance: Responsible growth

Risk-based

Pricing vs.

Pricing

optimization

Risk-based Pricing: Price variation - Differentiated pricing by risk

Price optimization: Price levels – Right price for each customer or segment

Pricing

optimization =

supply and

demand

Supply: Understand your willingness to lend

Demand: Understand your customers’ willingness to borrow

Proven results: 33% profit increase, 18% bad debt reduction,

100%+ EVA and RAROC improvement

Modular

approach

Four components: Data, Analytics, Technology, Consulting

Phased: Perfection is not a prerequisite, start simple with PoC


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