RESIDUAL RISK ANALYSIS SYSTEM, METHOD AND COMPUTER PROGRAM PRODUCT THEREFOR
Systems, methods and products for determining residual values of asset portfolios are disclosed. In one embodiment, a system includes a server computer coupled to a network and to a data storage device. The server generates residual value curves for each of a set of item types and stores them. The server computer also receives and/or maintains information defining a set of items in a portfolio. When an assessment of the portfolio is initiated, the server determines a residual value for each item in the portfolio by identifying a corresponding one of the item types, retrieving the residual value curve corresponding to the identified item type, and determining a future value of the item based on the retrieved residual value curve for the corresponding item type. The server then aggregates the individual residual values into a residual value for the portfolio and enables access to this value.
1 . A system for forecasting a future value of a portfolio of items, the system comprising:
a server computer coupled to a network; and
a data storage device coupled to the server computer;
wherein for each of a plurality of item types in a set of item types, the server computer is configured to generate a residual value curve and to store the residual value curve on the data storage device;
wherein for each of a plurality of items in a set of items, the server computer is configured to:
identify a corresponding one of the item types;
retrieve the residual value curve corresponding to the identified item type; and
determine a future value of the item based on the retrieved residual value curve for the corresponding item type;
wherein the server computer is configured to aggregate the future values of the items in the set of items and to store the aggregated future values in the data storage device; and
wherein the server computer is configured to enable a client device to access the aggregated future values.
2 . The system of claim 1 , wherein the server computer is configured to modify the residual value curve for at least one of the item types based on input received from a client device and to determine the future values of ones of the items associated with the modified residual value curves.
3 . The system of claim 1 , wherein for each item in the set of items, the server computer is configured to identify the corresponding item type by identifying a type number associated with the item, and identifying one of the item types that is associated with the type number.
4 . The system of claim 1 , wherein for each item in the set of items, the server computer is configured to identify the corresponding item type by identifying a first type number associated with the item, and identifying one of the item types that is associated with a second type number that is a partial, non-identical match of the first type number.
5 . The system of claim 1 , wherein the items comprise vehicles, wherein for each vehicle in the set of vehicles, the server computer is configured to identify a vehicle identification number (VIN) associated with the vehicle, and identify one of the item types that is associated with the VIN.
6 . The system of claim 1 , wherein the server computer is configured to generate residual value curves for a common set of item types, and wherein the server computer is further configured to determine future values of items contained in multiple, distinct sets of items based on the residual value curves of the common set of item types.
7 . The system of claim 1 , wherein the server computer is configured to determine, for one or more of the items, corresponding future values that are based at least in part on item-specific information that is associated with corresponding ones of the items in addition to the residual value curves for the item types associated with the items.
8 . A method for forecasting future values of an item, the method comprising:
for each of a plurality of item types in a set of item types, a server computer generating a residual value curve and storing the residual value curve on a data storage device;
for each of a plurality of items in a set of items, the server computer performing:
identifying a corresponding one of the item types;
retrieving the residual value curve corresponding to the identified item type;
determining a future value of the item based on the retrieved residual value curve for the corresponding item type;
aggregating the future values of the items in the set of items;
storing the aggregated future values in the data storage device; and
enabling a client device communicatively connected to the server computer to access the aggregated future values.
9 . The method of claim 8 , further comprising performing, by the server computer:
receiving input from a client device;
modifying the residual value curve for at least one of the item types based on the input received from the client device; and
determining the future values of ones of the items associated with the modified residual value curves.
10 . The method of claim 8 , wherein for each item in the set of items, identifying the corresponding item type comprises identifying a type number associated with the item, and identifying one of the item types that is associated with the type number.
11 . The method of claim 8 , wherein for each item in the set of items, identifying the corresponding item type comprises identifying a first type number associated with the item, and identifying one of the item types that is associated with a second type number that is a partial, non-identical match of the first type number.
12 . The method of claim 8 , wherein for each item in the set of items, identifying the corresponding item type comprises identifying a vehicle identification number (VIN) associated with the vehicle, and identifying one of the item types that is associated with the VIN.
13 . The method of claim 8 , further comprising performing, by the server computer:
generating residual value curves for a common set of item types; and
determining future values of items contained in multiple, distinct sets of items based on the residual value curves of the common set of item types.
14 . The method of claim 8 , further comprising performing, by the server computer for one or more of the items:
determining corresponding future values based at least in part on item-specific information that is associated with corresponding ones of the items in addition to the residual value curves for the item types associated with the items.
15 . A computer program product comprising at least one non-transitory computer-readable storage medium storing computer instructions that are translatable by a server computer to perform:
for each of a plurality of item types in a set of item types, generating a residual value curve and storing the residual value curve on a data storage device;
for each of a plurality of items in a set of items:
identifying a corresponding one of the item types;
retrieving the residual value curve corresponding to the identified item type;
determining a future value of the item based on the retrieved residual value curve for the corresponding item type;
aggregating the future values of the items in the set of items;
storing the aggregated future values in the data storage device; and
enabling a client device communicatively connected to the server computer to access the aggregated future values.
16 . The computer program product of claim 15 , wherein the computer instructions are further translatable by the server computer to perform:
receiving input from a client device;
modifying the residual value curve for at least one of the item types based on the input received from the client device; and
determining the future values of ones of the items associated with the modified residual value curves.
17 . The computer program product of claim 15 , wherein for each item in the set of items, identifying the corresponding item type comprises:
identifying a type number associated with the item; and
identifying one of the item types that is associated with the type number.
18 . The computer program product of claim 15 , wherein for each item in the set of items, identifying the corresponding item type comprises:
identifying a first type number associated with the item; and
identifying one of the item types that is associated with a second type number that is a partial, non-identical match of the first type number.
19 . The computer program product of claim 15 , wherein for each item in the set of items, identifying the corresponding item type comprises:
identifying a vehicle identification number (VIN) associated with the vehicle; and
identifying one of the item types that is associated with the VIN.
20 . The computer program product of claim 15 , wherein the computer instructions are further translatable by the server computer to perform:
generating residual value curves for a common set of item types; and
determining future values of items contained in multiple, distinct sets of items based on the residual value curves of the common set of item types.
21 . The computer program product of claim 15 , wherein the computer instructions are further translatable by the server computer to perform:
for one or more of the items, determining corresponding future values based at least in part on item-specific information that is associated with corresponding ones of the items in addition to the residual value curves for the item types associated with the items.