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Decision
system construction, validation and regulatory review. |
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To contact us: |
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Management Consulting Services |
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Mortgage Decision Technologies, Inc. |
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MDT Consulting: |
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When loans are rank
ordered from highest to lowest risk
by score, a table similar to the one above results. This
enables lenders to balance the profit available from incremental
production against incremental loan losses in a quantative fashion. Prime Models are embedded in
GSE and MI company automated underwriting
systems. Lender specific proprietary credit models make
sense from a strategic standpoint. Simultaneous pricing of mortgage credit and
prepayment risk is a “mission critical” capability. Lenders using their own data and personnel
exercise some control over their destiny.
They come to “own” the technology and it becomes a part of their
franchise value. It represents a barrier
to entry in the mortgage lending |
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business.
Those who rely on “me too” pricing without the ability to judge profitability at the loan level will generate
submarket returns. They forfeit the skill set necessary to
evaluate risk and will be burdened by higher regulatory capital requirements. Models can increase loan
production volume, increase the weighted average coupon on loans produced,
decrease cost per funded loan, and decrease “Prime” loan losses
simultaneously! Models provide
empirical support for why high risk applicants need higher pricing in order
to provide acceptable return to the
investor. Adherence to a Prime /
Subprime cutoff score assures that
applicants who have had credit problems but have modified their behavior
actually upgrade to Prime pricing at the first opportunity. Models are constructed without use of age,
race, national origin, gender, or other prohibited factors. They produce denial rates by protected
group that are far better than judgmental underwriting. |
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% of Loans |
% of losses |
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1 |
10% |
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2 |
19% |
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3 |
25% |
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4 |
30% |
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5 |
35% |
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10 |
50% |
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15 |
62% |
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20 |
70% |