Transcript Title of Presentation

Making The Best Offer
Adem Yilmaz
Chief Risk Officer
Hyundai Capital America
Aleligne Amera
Director, Pre-Sales Consulting
FICO
© 2014 Fair Isaac Corporation. Confidential.
This presentation is provided for the recipient only and cannot be reproduced or shared without Fair Isaac Corporation’s express consent.
The Best Offer – Borrow at 2%, Lend at 6%, at the Beach by 3 pm
If it were only that simple!
As portfolio managers, we are balancing complex and often contradicting goals
Risk
vs.
Reward
Effectiveness
vs.
Efficiency
Customer Satisfaction
vs.
Shareholder Value
Surgical Pricing
vs.
Communication
Competition
Portfolio Yield
vs.
vs.
Survival
Secondary Markets
A business engine that enables us to model our decisions, optimize and refine them is critical for realizing
our strategic objectives
The “Offer” Ecosystem – Full Life Cycle Implications
Downstream implications and the external factors that are driven by the offers we make.
External Factors
• Disruptive Pricing
• Dealer Satisfaction
• Customer Satisfaction
• Brand Image
• Competitive Landscape
• Corporate Rating
• Macro Economic Factors
• Regulatory Factors
Internal Factors
• Risk Appetite
• Balance Profit, Losses & Volume
• Operational Costs
• Underwriting (Rehash)
• Collections
• Operational Risk
•  Rehash =  Inconsistent
Decisioning
• Economic Capital and Reserve
Implications
• Securitization
• Whole Loan Sale
HCA has implemented an optimization framework that gives us agility in pricing while allowing
management to understand the implications. We call it the “Affirmative Offer Optimization Engine”
Affirmative Offer Optimization Engine – The Concept
Decision Modeling
• Evaluates and monitors data that would impact
decisioning
• Builds a graphical model for one or more
decisions
• Establishes mathematical
relationships within key variables
Decision Optimization
• Finds best combination of
decisions based on Decision
Model, Constraints, and Objective
• Uses permutations on key
constraints to evaluate
alternatives
Decision Deployment
Decision Refinement
• Incorporates optimized strategies
into core processing solutions
immediately
• Refines strategies for
interpretability, robustness and
ease of implementation
• Manages and maintains the decisioning
strategies to efficiently respond to market
demands and changes
• Ensures compliance and
palatability
Affirmative Offer Optimization Engine – In Practice
Migrating from a single offer environment to a more educated, negotiable offer requires the ability to
optimize the deal structure – at a deal and a dealer level – enabling the dealer to self rehash
Current Structure
Credit
Analyst
Credit
Capacity
Application
Single
Offer
???
Dealer
Car
FICO 680
Advance 140%
PTI 15%
Term 60
Loan $18,000
APR ?
Offer #1
Declined
Decision
Decision
Engine
Offer #2
Approved
as exception
With an Affirmative Offer Engine
Goal
Market
Capacity
Car
Decision
Decision
Engine
&
Price
Credit
Risk
Optimization
Engine
Credit
Analyst
Offer #1
Advance 140%
PTI 12%
Term 72
APR 8%
Annualized LTL 4.3%
Multiple
Offers
Self
Rehash
Offer #2
Advance 120%
PTI 15%
Term 60
APR 4%
Annualized LTL 2.4%
Dealer
Offer #3
Advance 120%
PTI 10%
Term 60
APR 2%
Annualized Loss 1.1%
In Summary…
To make a best offer –
•
Identify the ultimate goal – be it revenue maximization, market dominance or other and prioritize them
•
Based on the Goal – define the business problem that you wish to optimize
•
Identify the parameters and variables – both upstream and downstream to the decision point
•
Create processes that help transition the scenario engine into the real world (Infrastructure limitations, dealer education,
feedback loop and rapid improvement)
•
Above all – Monitor full lifecycle impact of the optimization engine
FICO Optimization Solution
for Alternative Deal Structure
7
© 2014 Fair Isaac Corporation. Confidential.
Finding the Right Balance Is Hard
► Providing
► Manage
Volume
choices to consumers
trade-off
► Conform
to rules and regulations of
the lender
Profit
Optimized
Deal
Structures
Deale Sat.
© 2014 Fair Isaac Corporation. Confidential.
Loss
FICO Optimization Solution for Alternative Deal Structure
© 2014 Fair Isaac Corporation. Confidential.
Value Proposition: High ROI
Assumptions:
►
►
►
$1B per month booking
200K applications per month
30% auto-approval rate
2%–5% Increase in volume
due to choices
►
1.5% risk adjusted spread
►
3%–5% reduction in
annualized losses due to
optimal restructure
►
► $8–$21
Mid-size lender
►
►
► Expected
Labor cost saving of 3–5
min per manually reviewed
application
© 2014 Fair Isaac Corporation. Confidential.
►
increase in risk adjusted spread:
MM per year
Expected reduction in losses (at 0.65%):
► $5–$9
MM per year
► Expected
► $2–$3
► Total
reduction in FTE:
MM per year
annual benefit:
► $15–$33
MM per year
► Expected
3-year ROI:
►
21:1
Other Tangible and Intangible Benefits of
FICO ADS Solutions
1. Cost savings and loss reduction
2. Increase in volume as a result of improved deal
structure and higher dealer satisfaction
(improved dealer relationship)
3. Minimal IT requirement in changing tiers, LTV, and other policies related to
deal structuring
4. High agility—Speed to respond market conditions is fast
5. Stable margin—ability to counter deteriorating yield with accepted level of risk
6. Intangible benefits:
► Business
consistency in restructuring deals since it is driven by Finance Manager UI
► High dealer and customer satisfaction
© 2014 Fair Isaac Corporation. Confidential.
12
Thank You!
Adem Yilmaz
Chief Risk Officer
Hyundai Capital America
Aleligne Amera
(310) 283-8177
[email protected]
© 2014 Fair Isaac Corporation. Confidential.
This presentation is provided for the recipient only and cannot be reproduced or shared without Fair Isaac Corporation’s express consent.
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© 2014 Fair Isaac Corporation. Confidential.
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Aleligne Amera
[email protected]
© 2014 Fair Isaac Corporation. Confidential.
This presentation is provided for the recipient only and cannot be reproduced or shared without Fair Isaac Corporation’s express consent.