The highlights of the OFS Retail Performance Analytics (OFS RPA) Application are as follows:
1. What-if Analysis: Predictive Modeling through Time Series Forecasting
§ What-if analysis reports use the reporting line forecast values that are generated using the Arima Algorithm in the Oracle R code seeded with the application and Segment Average method.
§ Oracle R has a base package called stats which provides the function called arima(). This function enables the usage of the ARIMA technique for time series forecasting.
§ This report enables the user to account for the change in profitability owing to any probable changes in the projected components of profitability. The probable change can be defined by the user and is termed as Variation.
§ The effect of variations on profitability can be analyzed at differing levels of granularity like enterprise, LOB, Product, Customer, and Account. This selection is enabled to the user through dashboard prompt selections.
§ The projected data of income statement is available at an account level. Aggregations are done based on the desired level of granularity. The projections are created based on historical data of the account.
§ The variations once applied on the income statement can be reapplied by either of the following two methods:
— Basic: The variations that are applied get simply aggregated with the modified values of components to show the resulting net income. The basic version supports variations to be applied to multiple parameters at the same time.
— Advanced: The variations that are applied also affect the other components it is correlated to and the modified values of all such parameters get aggregated to show the resulting net income. In the Advanced version, variation can be applied to only a single component at a time.
2. Segmentation
§ Segmentation is the procedure of grouping a set of customers based on similar features. These customers grouped are known to have similar behavior and hence, the future behavior of accounts within a Segment can be predicted to follow the similar behavioral patterns as observed for other accounts. Thus, by predicting the behavior of an account, it can be segmented with a set of similar accounts and its future projections can be created. These future projections provide the value of net income that can be expected from an account or customer.
§ Segmentation is done based on a certain set of dimensions wherein accounts which exhibit a particular combination of dimension members are grouped. Based on the characteristic around which segmentation is to be created, the dimensions used for segmentation can vary.
§ The segmentation models within Cutomer Insight (CI) are also used to provide an output to the OFS Price Creation and Discovery Application (OFS PCD).
3. Reports generation through Essbase cubes
Reports of the OFS IPA Application can be configured to work on a Relational database or Essbase cubes. The Source of data for the reports is determined by the priority set for each Logical Table Source (LTS) in OBIEE RPD. Multi-dimensional databases store aggregated data for better performance and provide mechanisms for performing non-additive rollup within a hierarchy and defining complex derived measures using cross-dimensional operations.
4. Service Calls to OFS RPA
Customer insight web service is designed to get consumed by other applications to get the profitability details. This web service will work at customer level and account level.
5. Customer Central: 360-degree customer view
This is a Sun-burst wheel that displays the circular graphical representation divided into several sectors, such as Turnover, Customer Since, Total Assets Balance, Total Liability Balance, Number of Assets Product, Number of Liability Product, Number of Products Held (currently), Number of Products Held (Since the inception of a customer), Debit Turnover, Credit Turnover, Mitigant Value, Total Spent, Net Income, and so on, of the selected customer.
Each Sector represents the following values:
§ Customer Value: This represents the dimensional value of customers across the scale.
§ Segment Average: This represents the average value of the dimension of the segment that the customer belongs to.
§ Enterprise Average: This represents customers from all the segments considered to compute the average value of dimension or measure.
6. Life Time Value
Based on the profitability of the accounts, the future behavior of accounts is predicted, and this predicted value is used to compute Customer Life-Time Value (CLTV). The CLTV can be analyzed for different periods of projections and accordingly the projected data to be considered for reporting CLTV is selected.
7. Income Statement
Profit & Loss Statement generation by Accounts, Customers, Products, and Line of Businesses.
8. Profitability Calculations
Risk-adjusted Performance Metric Report: This report helps you to determine the ratio of risk-adjusted Net Income against the Economic Capital. This metric is also called Risk-Adjusted Return on Capital (RAROC). It helps in determining the efficiency of Economic Capital corresponding to every customer. This report shows a snapshot of measures against various reporting lines, for example, Total Revenue, Total Expenses, Net Income, Return on Total Asset RAROC, and Return on Equity.
9. Performance Analytics Metrics Computation
Availability of account and customer-based metrics like ROTA, RAROC, Return on Equity (ROE), Total Expenses, Total Income, Net Income, and so on.
10. Profitability Reports
A host of Profitability reports based on Accounts, Customers, Products, LOBs, Relationship Managers, and Geography along with analysis of opportunities handles with detailed activities are available.
OFS IPA offers dashboards to users to organize different kinds of reports by subject area. These reports present:
§ Behavioral and Engagement trends of its target segments: exposures, commitments, line utilization, assets liabilities, deposits, withdrawals, fees, income, recent transactions, and so on.
§ Performance of the business lines and underlying customers.
§ Analyze expenses across customer segments, products, and channels to understand ROI.
§ Product holdings through different line of businesses.
§ The efficiency of the sales force in terms of ongoing customer revenue generation, cross-sell and up-sell, product usage, and pipeline.
§ The efficiency of investments (such as marketing and partner development).
§ Perform Wallet share analysis and Customer Profitability.