Capabilities > Business Intelligence > Financial Analytics

Customer Success Story

Financial services company repositions its sales strategy to target profits instead of revenues

Situation: Corporate margins eroding while company is going through revenue growth

Approach: Identify source of margin erosion using fact- based,analytical rigor

Solution: Developed analytic application to help company salespersons make real-time pricing decisions improving profitability

Financial Analytics

 

High performing organizations need a complete understanding of which parts of their business are adding and which parts are subtracting from their overall profitability. Using Confida's Financial Analytics and our product, the Performance Management Portal (PMP), organizations can in real-time identify best and worst performing segments/assets of their business.

Confida's financial analytics process is based on an activity-based revenue and costing model.

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Company-specific financial data is combined with a financial and an activity model in order to create a profit-and-loss profile for every key business activity. Often, instead of calculating profitability profiles for key activities, we determine profitability for the lowest common denominator in the business. For example, in leasing, the lowest common denominator might be a loan, in health insurance, it might be a claim, in other cases, it might be a contract. These profitability profiles form the foundation of a flexible profitability model that can be used to assess profitability for key business dimensions (e.g. salesperson, industry).

Profitability profiles are cash flow driven. Thus, a cash flow structure is built for the aforementioned lowest common denominator for the business - for example, a loan or a claim. This cash flow structure includes revenues and associated costs in acquiring and servicing the revenues over time. The diagram below represents what the cash flow for a loan might look like

 

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The cash flow structure is then used to formulate aggregate economics for any grouping within the business. One can think of these groupings as portfolios. A portfolio can be the entire company, one salesperson, one customer or a user-defined combination of various parameters (e.g., all the salespeople who have been with the company less than 2 years). Whatever the chosen portfolio, the aggregate economics can be displayed using a standard diagram. The diagram below is an example of the aggregate economics for a leasing company - the single point represents the portfolio and the "target curve" represents a predetermined profitability target. The diagram thus displays a performance profile for a particular segment of the business - to the left of the curve is an underperforming portfolio and to the right of the curve is overperforming portfolio.

 

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The underlying methodology behind Confida's financial analytics is a robust activity-based costing engine used to assign both fixed and variable costs to the correct consumers of those resources. The cost allocation strategy is usually detailed, but can be represented in a simplified format; the "purpose & nature" matrix depicted in the diagram below is used to determine the cost allocation strategy for a given general ledger account. Each account is analyzed separately to determine its cost profile.

 

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Then, both acquisition and service cost allocations are directed through various cost centers to the lowest common denominator (see diagram below). Thus, each penny of expenditure is fully accounted for - whether the expenses are incurred at the office of the president or at a local branch, they are fully apportioned and allocated to the lowest denominator. The methodology is a closed-loop system in that adding all the lowest denominators together will yield the cost structure for the entire company. A similar approach is followed to arrive at the revenue and profitability figures.

 

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The ensuing model provides for a powerful set of financial analytics. Once the model is built, the business can be sliced and diced in an infinite number of ways to find profitability profiles for various parts of the organization.

For example, in many organizations, it is difficult and undesirable to micro-manage piece-parts of the business - it more practical to provide strategic and financial targets and have the business segments self-manage within these parameters. Using the described financial analytics, an organization could provide necessary information, for example, for salespersons or branches to self-manage. A dynamic tool like PMP, built on these financial analytics, allows constant evaluation of each sales territory and creates a reasonable and disciplined environment to effectively manage the portfolio both up and down the management chain.