Inverse Matrix Credit Sales Model by Yakub Khan

VALUE AT RISK MODEL VS GOODS AT RISK / STOCK AT RISK MODEL

      As we know there is a model related to risk i.e. VaR, (Value at risk). This model play’s very vital role in RISK. There are confidence levels to define that the losses will not exceed to this limit and the profits can be reached to this extent at this confidence levels.

    At the same time, there is a big use of this model for the Retail Industries, Manufacturing Industries. This model can be used as “Good’s at risk model” or “Stock’s at risk model”.

       In the given graph X- axis shows the confidence level’s and the data points in blue color defined the stocks/Goods from the lowest value to the highest value which are not able to sold in the market. i.e. lying at the sales point or the ware house.

        At Y- axis i.e. in green region defines the value of Stocks/Goods from the least to the highest ranged product’s, which are able to sold in the market at sales point.

        Under this model it shows that the stock’s lying at warehouse / sales point not able to deliver the results under which how much losses were incurred or can be incurred. i.e. decision has to be sell out at the most discount rate or take necessary actions to get rid of the stock lying under the belt.

Advantage of Model: 

      At the same time, model showing the products of highest value which are able to sold in the market, can give good results by increasing the production of such products in the market.

     Decrease the stock’s that are risk and increase the production which are good in sales (Highest Values to the Lowest Value)

CREDIT SALES MATRIX MODEL

     This is a strategic credit sales model in order to decrease the unsold stocks inversely related to the introduction of credit worthiness matrix model, Customers matrix, Customers allocation matrix & Products matrix.

      There are 3 stages of creation of matrix to allocate the customers based upon their purchasing power that includes those products for which they will be eligible to avail the credit facility for those products, and those products are inverse with in the product matrix, which is related to the value of products.

      Customer ID allocation matrix = Based upon the purchasing power already done by the customer i.e eligible to the defined products between the ranges.

1. Matrix loaded to the customer based allocation that links to the eligible products.
2. Products matrix that holds the products based upon the categories, valuations, etc.

    Once the above categories goes into the inverse matrix model the following results shows the products and its eligible customers to avail the credit facilities, to fix the credit facilities there will be another matrix model that shows the limitations on credit to avail from those products and vice versa.

1. X represents the customers
2. Values in “k” represent the purchasing power / purchasing credit limit (Customer / Allotted ID)
3. X0 (A0, B0, C0, as so on) represents the allocation of products / values to those matrix customers.
4. List of products are matrix under the big allocation of products / categories as shows in red box.

       It’s a flow of inverse matrix that allocates and gives us different shapes, different ideas for different customers, models. This is more useful for any firm to create a credit worthiness model in order to increase the sale for unsold stocks.

     Credit facility can be allocated based upon the existing purchasing capacity of the customer in order to increase the sales. This is still need to be reviewed and create another model in order to link the credit limits.