The ability to customize the scoring engine enables pooling of
relationships and provides flexibility to work with smaller data
sets. Probability of default is calculated using both Basel II and
internal default definitions over a variable sample window.
Change in customer behavior may be captured using a coarse grid
approach, or supplementing the grades with additional indicators,
making the event tracking process as sensitive as required.
Finally the ability to define score ranges for probability of default
calculation allows the user to capture any outliers in the score
distribution, instead of having to group PDs using a generic scale.
 |
A Basel II compliant Obligor Risk Rating (ORR) and Facility
Risk Rating (FRR) engine |
 |
Entity and facility probability of default calculations |
 |
Multifactor scoring engine |
 |
Multiple scoring parameter configurations |
 |
Basel II and internal default event definitions |
 |
Payment behavior tracking and principal/markup overdue analysis |
 |
Out of time and out of sample statistical testing for calibration
and discrimination |
 |
Attribute specific probability of default estimates |
 |
Out of time and out of sample statistical testing for calibration
and discrimination |
 |
Foundation IRB capital charge computation |
 |
Loan pricing module using return on asset (ROA) and risk adjusted
return on capital (RAROC) analytics. |
Alchemy RatingOne - Functionality Table
|
| Obligor |
Facility |
Credit Event |
Probability |
Validity |
Basel II |
Customer Attributes |
Collateral |
Basel II Default |
Entity & Facility |
Out of time |
Foundation IRB Capital Charge |
Financial & Ratios |
|
|
|
|
|
External Rating |
Repayment Behavior |
|
|
Calibration |
Capital Allocation |
|