System and Method of Demand Modeling for Financial Service Products
A computer system is provided which models financial products such as demand deposits and time deposits. The computer system collects transactional data related to a plurality of financial products. The demand model includes an acquisition model, average balance model, and time demand renewable model for predicting customer responses to changes in interest rate based on the transactional data. The demand model evaluates consumer response through account opening, balance variations, and time deposit renewals. The demand model can also predict effects of cannibalization, seasonality, promotions, and time-dependent demand on the financial products. The cannibalization model estimates model parameters by demand group level, categorical level, and multicurrency level. The interest rate is optimized for each of the financial products by utilizing one or more of the acquisition, average balance, time demand renewable, cannibalization, seasonality, promotional, and time-dependent models. The optimized interest rate is exported to a financial institution.
1 . A computer-implemented method of modeling a financial product, comprising:
collecting transactional data related to a plurality of financial products;
providing a demand model to predict customer responses to changes in interest rate, the demand model including
(a) an acquisition model for quantifying relationships between the financial products and interest rates and predicting volume for the financial products based on the transactional data,
(b) an average balance model for quantifying relationships between temporal average balances of the financial products and interest rates based on the transactional data, and
(c) a time demand renewable model for quantifying relationships between probability of renewals and interest rates for the financial products based on the transactional data;
optimizing interest rates for the financial products utilizing the demand model; and
exporting the optimized interest rates to a financial institution.
2 . The computer-implemented method of claim 1 , further including modeling cannibalization between the financial products based on the transactional data.
3 . The computer-implemented method of claim 1 , wherein modeling cannibalization includes estimating model parameters by demand group level, categorical level, and multicurrency level.
4 . The computer-implemented method of claim 1 , further including modeling seasonality on the financial products based on the transactional data.
5 . The computer-implemented method of claim 1 , further including modeling promotions and time-dependent demand on the financial products based on the transactional data.
6 . The computer-implemented method of claim 1 , wherein the financial products include demand deposits and time deposits.
7 . The computer-implemented method of claim 1 , wherein the demand model evaluates consumer response through account opening, balance variations, and time deposit renewals.
8 . A computer-implemented method of modeling a financial product, comprising:
collecting transactional data related to a plurality of financial products;
providing a demand model including an acquisition model, average balance model, and time demand renewable model for predicting customer responses to changes in a financial product attribute based on the transactional data;
optimizing the attribute for the financial products by utilizing one or more of the acquisition model, average balance model, and time demand renewable model; and
exporting the optimized attribute to a financial institution.
9 . The computer-implemented method of claim 8 , further including modeling cannibalization between the financial products based on the transactional data.
10 . The computer-implemented method of claim 9 , wherein modeling cannibalization includes estimating model parameters by demand group level, categorical level, and multicurrency level.
11 . The computer-implemented method of claim 8 , further including modeling seasonality on the financial products based on the transactional data.
12 . The computer-implemented method of claim 8 , further including modeling promotions and time-dependent demand on the financial products based on the transactional data.
13 . The computer-implemented method of claim 8 , wherein the financial product attribute is interest rate.
14 . A computer program product usable with a programmable computer processor having a computer readable program code embodied therein, comprising:
computer readable program code which collects transactional data related to a plurality of financial products;
computer readable program code which provides a demand model including an acquisition model, average balance model, and time demand renewable model for predicting customer responses to changes in a financial product attribute based on the transactional data;
computer readable program code which optimizes the attribute for the financial products by utilizing one or more of the acquisition model, average balance model, and time demand renewable model; and
computer readable program code which exports the optimized attribute to a financial institution.
15 . The computer program product of claim 14 , further including computer readable program code which models cannibalization between the financial products based on the transactional data.
16 . The computer program product of claim 15 , wherein modeling cannibalization includes estimating model parameters by demand group level, categorical level, and multicurrency level.
17 . The computer program product of claim 14 , further including computer readable program code which models seasonality on the financial products based on the transactional data.
18 . The computer program product of claim 14 , further including computer readable program code which models promotions and time-dependent demand on the financial products based on the transactional data.
19 . The computer program product of claim 14 , wherein the financial product attribute is interest rate.
20 . A computer system for modeling a financial product, comprising:
means for collecting transactional data related to a plurality of financial products;
means for providing a demand model including an acquisition model, average balance model, and time demand renewable model for predicting customer responses to changes in a financial product attribute based on the transactional data;
means for optimizing the attribute for the financial products by utilizing one or more of the acquisition model, average balance model, and time demand renewable model; and
means for exporting the optimized attribute to a financial institution.
21 . The computer system of claim 20 , further including means for modeling cannibalization between the financial products based on the transactional data.
22 . The computer system of claim 21 , wherein modeling cannibalization includes estimating model parameters by demand group level, categorical level, and multicurrency level.
23 . The computer system of claim 20 , further including means for modeling seasonality on the financial products based on the transactional data.
24 . The computer system of claim 20 , further including means for modeling promotions and time-dependent demand on the financial products based on the transactional data.
25 . The computer system of claim 20 , wherein the financial product attribute is interest rate.