1. A method of facilitating use of targeted indicators, comprising:
determining at least one condition associated with a target business segment;
selecting a series of indicator input items; and
automatically generating a forecast model for the target business segment based on historic information associated with the series of indicator input items and the condition.
2. The method of claim 1, wherein at least one indicator input item include at least one of: (i) economic information, (ii) employment information, (iii) inflation information, (iv) equity information, (v) debt information, (vi) construction information, (vii) backlog information, (viii) new order information, (ix) vacancy information, (x) interest rate information, (xi) money supply information, (xii) payment information, and (xiii) delinquency information.
3. The method of claim 1, wherein said selecting further comprises:
identifying the target business segment;
identifying a series of potential indicator input items; and
evaluating the potential indicator input items.
4. The method of claim 3, wherein said evaluation is associated with at least one of: (i) seasonally adjusted information, (ii) rolling median information, (iii) standardized values, (iv) correlation coefficients, (v) weighted averages, and (vi) graphical analysis.
5. The method of claim 1, wherein the target business segment is associated with at least one of: (i) an industry, (ii) an industry segment, (iii) a market, (iv) a market segment, (v) a customer, and (vi) a group of customers.
6. The method of claim 5, wherein the target business segment is further associated with at least one of: (i) a collateral type, (ii) a geographic location, and (iii) a customer type.
7. The method of claim 5, wherein the target business segment is associated with at least one of: (i) manufacturing, (ii) construction, (iii) retail trade, (iv) services, (v) wholesale trade, (vi) agriculture, (vii) forestry, (viii) fishing, (ix) mining, (x) transportation, (xi) communication, (xii) utility, (xiii) electric, (xiv) gas, (xv) sanitary services, (xvi) finance, (xvii) insurance, (xviii) real estate, and (xix) public administration.
8. The method of claim 1, wherein the condition is associated with at least one of: (i) an economic condition, (ii) a payment information, (iii) a business cycle, and (iv) an industry behavior.
9. The method of claim 1, wherein the condition is associated with a plurality of bins.
10. The method of claim 9, wherein at least one bin is associated with at least one of: (i) an above trend business level, (ii) a trend business level, and (iii) a below trend business level.
11. The method of claim 1, wherein said automatic generation is associated with a linear optimization technique.
12. The method of claim 1, wherein the forecast model is associated with weighing factors applied to each indicator input item.
13. The method of claim 1, wherein the forecast model is associated with at least one of: (i) leading indicator information, (ii) lagging indicator information, and (iii) coincident indicator information.
14. The method of claim 1, further comprising
predicting future conditions based on current indicator input items and the forecast model.
15. The method of claim 14, further comprising:
adjusting a adjusting a score associated with an existing credit account based on said prediction.
16. The method of claim 14, further comprising:
adjusting a potential credit deal based on said prediction.
17. The method of claim 16, wherein said adjusting is associated with at least one of: (i) a loan amount, (ii) a loan spread, (iii) a loan duration, (iv) a loan term, and (v) a lease.
18. The method of claim 14, wherein said predicting is associated with a long term performance forecast in accordance with a time series model.
19. An apparatus, comprising:
a processor; and
a storage device in communication with said processor and storing instructions adapted to be executed by said processor to:
determine at least one condition associated with a target business segment;
select a series of indicator input items; and
automatically generate a forecast model for the target business segment based on historic information associated with the series of indicator input items and the condition.
20. The apparatus of claim 19, wherein said storage device further stores at least one of: (i) a customer database, (ii) an account database, (iii) an indicator input database, (iv) a condition database, (v) a forecast model database, and (vi) a risk information database.
21. The apparatus of claim 19, further comprising:
a communication device coupled to said processor and adapted to communicate with at least one of: (i) a risk manager device, (ii) an underwriter device, (iii) a third party service, (iv) a risk score controller, and (v) a leading indicator system.
22. A medium storing instructions adapted to be executed by a processor to perform a method of facilitating use of targeted indicators, said method comprising:
determining at least one condition associated with a target business segment;
selecting a series of indicator input items; and
automatically generating a forecast model for the target business segment based on historic information associated with the series of indicator input items and the condition.
23. A method of facilitating use of targeted indicators, comprising:
retrieving a forecast model for a target business segment associated with an existing credit account;
determining a series of indicator input values;
predicting a future condition based on the forecast model and the series of indicator input values; and
adjusting a score associated with the credit account based on said prediction.
24. A method of facilitating use of targeted indicators, comprising:
retrieving a forecast model for a target business segment associated with a potential credit deal;
determining a series of indicator input values;
predicting a future condition based on the forecast model and the series of indicator input values; and
adjusting the potential credit deal based on said prediction.
25. The method of claim 24, wherein said adjusting is associated with at least one of: (i) a loan amount, (ii) a loan spread, (iii) a loan duration, (iv) a loan term, and (v) a lease.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A method for processing instructions represented by opcodes in an execution unit having multiple pipelines, the method comprising:
receiving data by the execution unit with respect to an instruction including complex opcode data;
queuing the instruction for pipeline processing within the execution unit based on complex opcode data wherein a single instruction from several sources is used throughout execution unit; and
executing the instruction at least a first time to get an address value and at least a second time to get a result of an operation represented by the instruction.
2. The method of claim 1 where the supported set of instructions includes a standardized set of x86 instructions and wherein receiving data by the execution unit includes receiving opcode data.
3. The method of claim 1, wherein the execution unit is configured with an opcode queue and each queue position supports a plurality of sources with a destination corresponding to information passed from decode with each opcode.
4. The method of claim 3, wherein each queue position is generic with respect to loadstore support for an address generation pipeline and simple opcode support for arithmetic logic pipeline, and is configured with a source and destination designation for the queue position.
5. The method of claim 1, wherein for processing complex opcodes, a complex opcode is split into a loadstore instructions component and a simple opcode component and creating an internal source and destination between the two components.
6. The method of claim 5, wherein an internal destination designation is provided to the simple opcode component by the execution unit which is used as an internal source for the complex opcode.
7. The method of claim 5, wherein an internal destination designation is provided for the result of processing the simple opcode component, wherein the internal destination designation is used as an internal source for the loadstore component.
8. The method of claim 4, wherein an instruction represented by complex opcodes is associated with any of the sources available for the queue position.
9. The method of claim 1, further comprising executing the instruction at least a plurality of times to pick a queue position holding a complex opcode, once for each part of the complex opcode operation.
10. An integrated circuit (IC) comprising:
an execution unit having multiple pipelines, each pipeline configured to process instructions represented by opcodes;
the execution unit configured to receive data with respect to an instruction, the received data including complex opcode data;
the execution unit including a mapper configured to queue the instruction for pipeline processing within the execution unit based on complex opcode data wherein a single instruction from several sources is used throughout execution unit;
wherein the execution unit is configured to execute the instruction at least a first time to get an address value and at least a second time to get a result of an operation represented by the instruction.
11. The integrated circuit of claim 10, wherein the supported set of instructions includes a standardized set of x86 instructions and wherein receiving data by the execution unit includes receiving opcode data.
12. The integrated circuit of claim 10, wherein the execution unit is configured with an opcode queue and each queue position supports a plurality sources along with a destination corresponding to information passed from decode with each opcode.
13. The integrated circuit of claim 12, wherein each queue position is generic with respect to loadstore support for an address generation pipeline and simple opcode support for arithmetic logic pipeline and is configured with a source and destination designation for the queue position.
14. The integrated circuit of claim 10, wherein for processing complex opcodes, a complex opcode is split into a loadstore instructions component and a simple opcode component and creating an internal source and destination between the two components.
15. The integrated circuit of claim 14, wherein an internal destination designation is provided to the simple opcode component by the execution unit, which is used as an internal source for the complex opcode.
16. The integrated circuit of claim 14, wherein an internal destination designation is provided for the result of processing the simple opcode component, wherein the internal destination designation is used as an internal source for the loadstore component.
17. The integrated circuit of claim 13, wherein an instruction represented by complex opcodes is associated with any of the sources available for the queue position.
18. The integrated circuit of claim 10, wherein the execution unit is further configured to execute the instruction a plurality of times to pick a queue position holding a complex opcode, once for each part of the complex opcode operation.
19. A computer-readable storage medium storing a set of instructions for execution by one or more processors to facilitate a design or manufacture of an integrated circuit (IC), the IC comprising:
an execution unit having multiple pipelines, each pipeline configured to execute supported instructions that are identified by complex opcodes, wherein the execution unit is configured to execute an instruction at least a first time to get an address value and at least a second time to get a result of an operation.
20. The computer-readable storage medium of claim 19, wherein the instructions are hardware description language (HDL) instructions used for the manufacture of a device.