Tune up your bank’s performance management engine

Improve forecasting, tracking with an optimized EPM system

As banking leaders consider their forecasting and performance management needs for the future, they may wish to reflect on how convenient it was to deposit a check in an ATM — until the ability to deposit via your smartphone from any location came about.

With powerful data-based analytical tools and artificial intelligence capabilities increasingly available to banks, they’re finding that spreadsheet-based tools aren’t meeting their needs anymore. In the banking industry, an effective enterprise performance management (EPM) system can provide budgeting, forecasting and reporting functionality that can make the difference between growth and stagnation.

An optimally functioning EPM system unleashes data from a bank’s systems as well as external sources to provide:

Accurate reporting
Unparalleled visibility into operations
Analysis of trends and opportunities
Ultimately, input that can provide better strategic direction

Banks or credit unions that are operating with spreadsheet processes will see noticeable improvements upon embracing EPM. The powerful EPM tools that once were only affordable for banking giants are now easily within the budgetary reach of much smaller retail banks and credit unions. The affordability has leveled the playing field, allowing all financial institutions to move away from running their businesses via spreadsheets.

“An EPM system will provide benefits such as better collaboration, much tighter security, central reporting with one version of the truth, and faster turnaround times.”

Paul Mack

Grant Thornton Director, Technology Modernization

“Commonly, spreadsheet processes have become too convoluted and frustrating for banking personnel to use,” said Grant Thornton Technology Modernization Director Paul Mack. “The move to an EPM system will provide benefits such as better collaboration, much tighter security, central reporting with one version of the truth, and faster turnaround times.”

Meanwhile, banks that already have an EPM system may find benefits from upgrading. Some banks undergo EPM improvements when they move from on-premise systems to cloud-based solutions, and others may want to upgrade to a tool specifically geared toward their industry, guided by an implementer with the relevant banking knowledge and experience.

Here’s what banks need to do to take full advantage of the benefits an optimized EPM system can bring.

Assess your needs

Banking leaders who are looking to implement an EPM system need to first verify that it will support the key aspects of their budgeting and planning processes. These typically include:

Functionality to support budgeting, forecasting, management reporting, profitability analysis and the calculation of funds transfer pricing (FTP).
Balance sheet-focused planning processes.
Planning that encompasses different rate-related product types — loans, deposits, investments and borrowings.
Projections for rates of the different rate-related products.
Rate-related revenues and expenses, which are derived from the projected average balances and rates.

The focus on the balance sheet, and in particular on average balances, makes the banking industry’s EPM requirements different from those of other industries. While many other industries are looking at balance sheets with ending balances, average balances matter most to banks because they are multiplied against a rate to calculate P&L items.

Meanwhile, interest rate risk presents the biggest challenge to these systems because the models need to account for different interest rate scenarios and how rates will change over time. The models need to be flexible enough to adjust for different rate scenarios.

Banks also need to make sure their EPM systems accurately forecast their expected credit losses across different product lines so they can calculate their reserves in a compliant manner. The expected credit losses will be different based on changes in rate scenarios and other factors as well, and the EPM forecasts need to take this into account.

Retail bank EPM data sourcing needs

Bank EPM systems need data from:

The general ledger
Loan and CD processing systems, describing instrument detail (including rates) and transactions
Treasury systems such as ALM models
Call center/branch transactions
HR systems
Funds transfer pricing (if calculated externally)

All banking EPM systems also need the ability to:

Flexibly integrate information from multiple sources, including financial accounting and non-financial drivers and metrics.
Calculate average balances for all planned balance sheet accounts.
Plan for the different rate-related product types (loans, deposits, investments and borrowings). For example, the system will need the ability to calculate fixed- and variable-rate loans with options for 30/360, actual/360, and actual/365 interest accrual calculations.
Model net interest margin (NIM) for different interest rate scenarios. The system will need to be able to assign products to a rate index (the sum of the rate index plus spread equals the product interest rate). And the system will need to plan interest for existing product balances as well as projected new additions.
Load existing rate-related account portfolio balances and the projected runoff by month.
Plan new rate-related portfolio additions at projected rates.
Calculate FTP using either an instrument-based approach or a pool-based methodology.
Model the profitability of different channels and products across the enterprise. For example, modeling the profitability of each branch is a must.
Enable self-service reporting.

The ultimate goal of this budgeting effort should be real-time planning, enabled by artificial intelligence that synthesizes immense quantities of data to enable better forecasting and quick pivots. In the past, forecasts have been performed almost entirely based on historical data.

“Banks are still working through how to do this with a goal of achieving better capabilities before their competitors,” said Grant Thornton CFO Advisory Managing Director Scott Tripp. “What they’re talking about at this point is having more of a rolling focus on a monthly or potentially a biweekly basis.”

Tracking separate layers

Bank EPM systems should provide the ability to get insights and provide forecasts separately for different branches, products and channels as well as the bank’s overall organic growth and its strategic planning initiatives.

Initiatives should be forecasted and tracked in separate layers or buckets, which are incorporated into the base organic plan to get the total plan.

Key analytics for optimal bank operations

Headcount/FTE
Employee analytics such as branch transaction volumes and staffing by hour
Cross-selling metrics
New loans and deposits by channel
Net interest margin (NIM)
Efficiency ratio (non-interest expense/revenue)
Loans/deposits (total loans over total deposits to measure liquidity)
Return on assets

“The ability to analyze product-type revenue by onboarded channel provides informed decision-making, such as digital banking and branch strategy.”

Scott Tripp

Grant Thornton Managing Director, CFO Advisory

Profitability modeling and tracking will help banking leaders better understand issues that will be undiscoverable in simple spreadsheet allocation processes. Effective EPM modeling will help bank leaders understand:

Which products, channels, services and customers are the most and least profitable — and why.
Volumes and locations of transactions, cannibalization and household relationships.

“Deposits tend to make customer relationships stickier if additional products, such as loans, can be offered along with them,” Tripp said. “The ability to analyze product-type revenue by onboarded channel provides informed decision-making, such as digital banking and branch strategy.”

The benefits of scenario modeling

EPM systems also should provide banks with scenario modeling information that will be useful, including:

M&A modeling. Potential M&A options can be modeled to see what the financial statement of the combined entity would look like. Different scenarios can then be used to model and compare funding options.
Sensitivity analysis. Potential changes in business growth and financing strategies can be tested for the impact they would have on the business. Expected changes in loan/deposit growth, yields/rates, funding strategies, and bank ratios may be modeled.
P&L impacts of key promotions such as sign-up bonuses or highly favorable rate offerings.
Impacts of new branches or channels — or branch consolidation.
Changes in product or service offerings.

“You want to have the ability to create pro forma financial statements of the potential results of different combinations of branch expansions, closures and changes.”

Brian Eccher

Grant Thornton Principal, Business Applications

“You want to have the ability to create pro forma financial statements of the potential results of different combinations of branch expansions, closures and changes — and other initiatives and strategies,” said Grant Thornton Business Applications Principal Brian Eccher. “You can layer in the impact of various different actions into your planning or forecasting.”

An effective EPM system will also be able to measure impacts from different projected interest rate scenarios, or yield curves. Banking asset/liability models (ALM) will measure the spread over time. Incorporating this ALM information into the annual budget enables greater accuracy in rate-related revenue and expense projections. This improved accuracy can also be used to understand variable revenues, such as fees, as well as expenses, such as labor costs.

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Getting started

Advanced forecasting capabilities based on increasingly powerful technologies are driving the potential for banks to make substantial improvements in their achievement of profitable growth.

In this environment, banks that continue to rely on spreadsheets for their forecasting will be at a disadvantage. And banks with EPM systems that aren’t specifically designed for their industry may not be able to measure some of the key metrics that they need to evaluate their progress and potential.

Whether banks incorporate these systems themselves or turn to third parties for assistance, the value of data-based decision-making tends to far outweigh the costs of implementation.