1. Develop Usage Forecasts: Any business case begins with a forecast of projected usage. Forecasting is more of an art than a science, but your forecasts should consider these four factors as a starting point:

• Computer usage among your target market. This is not the same as computer ownership. Ownership is a leading indicator, but many users will be able to use online banking (OLB) from work or other locales.
• Online connectivity among your target market. In the future, with Net TVs and e-mail telephones, users will be able to access OLB services without using a computer. This will be a significant number in the later years of a five-year planning horizon.
• General pricing philosophy. Are you planning to offer OLB services:

• free?
• below-market prices?
• at the going market rate?
• at premium prices?

• Competitive pressure. Even if you are planning to offer OLB as a premium-priced break-even service to retain customers, your competitors may have a different idea.

Depending on the sophistication of your business case, you may need to subdivide your forecast into three categories:

• existing (bank) households using OLB
• new households that came to the bank to use OLB
• households retained because of OLB

2. Estimate Financial Information Fee Income: Everyone’s first question is, “What can we charge?” The short answer, “it depends.” It depends on your strategy, your customers, and what value-added services you provide.

We are absolutely convinced that basic online account access will evolve as a free service just like call centers today. But unlike telephone banking, OLB has many other ways to become a significant profit center. Though you may never charge for simple account access, you will likely charge fees for ancillary and premium services. You should try to account for that inevitability in your business case.

3. Estimate the Value of New Customers: New customers attracted to your bank by the lure of online banking are an important source of revenue. Banks have reported 20-40% of online banking customers are new to the bank. But many of those new households would have become bank customers even without online banking.

So, determining the value of new households is a two-step process. First, estimate the percentage of new households that are incremental due to the online offering. Ideally, a survey of new households would be used to develop this estimate. If that’s not feasible, take an informal survey of new account reps to support your estimate.

Next, determine the average profitability of new households over time. Then multiply this value times the number of new households to determine the total value of online banking for generating new households. In our example, we assumed a three-year ramp-up to maximum HH profitability of $200/year

For more precise measures in the future, flag new online banking households in your CIF and track their total profitability over time.

4. Estimate the Value of Retained Customers: Even more important for most banks, is the number of households “saved” or retained due to online banking. But this number is even more difficult to measure (really impossible), so an educated guess must suffice. To support your estimate, you could ask OLB households if they would move accounts if you didn’t offer the services. (Note: We don’t take a lot of stock in telephone survey responses to hypothetical scenarios, but by comparing answers to other possibilities, e.g., “would you move accounts to save $3/mo,” you can get a sense of the relative value of OLB compared to other price/performance attributes.)

Multiply the number of saved households times average OLB household profitability to determine their value.

Another way to handle the estimates in steps three and four is to lump the two together and estimate what percent of your OLB base is incremental to your bank because of OLB. The number would be a combination of new and/or saved households. In our example, we have assumed that 15% of the OLB base is incremental.

5. Forecast Cross-Sales of Other Bank Products: Online account access will drive users to your Web. Since they must identify themselves to retrieve account data, you will have an ideal opportunity to pitch appropriate products in an extremely cost-effective way. For example, instead of sending preapproved direct mail costing $0.50 to $1 per piece, deliver the same offer to customers when they log onto your Web to check on their accounts. This could be accomplished for just pennies per customer. Further reducing costs, your customer will do their own account set-up data entry.

Again, you need a line item(s) in your business case to credit the “online channel” with its value as a generator of incremental sales to OLB households. We chose to estimate the value of cross-sales as a dollar contribution. Alternatively, you could show incremental deposits and assets as they grow with your OLB base.

6. Estimate Cost Savings: Just as ATMs promised an era of reduced bank costs that was largely unrealized, Internet banking suffers some of the same early problems. For every one customer who answers their own simple question on your Web site (eg., “What are the hours of the main branch?”), ten others e-mail with bizarre (for a bank) questions like, “In my AOL browser I can’t read the mortgage rates in the third column. What should I do?”

But there is a big difference between ATMs and Internet banking. ATMs are expensive, high-maintenance mechanical devices prone to breakdown, vandalism, crime, and often (but not always) require a dedicated telecom line to handle a few hundred transactions per day (at most), and armored car delivery of consumables (cash).

On the other hand, Internet banking uses highly efficient equipment whose only consumable (electrons) is available at practically no cost. Once users, and banks, move down the learning curve, the cost savings of self-service information retrieval will be significant. The high-tech companies that were first to service corporate clients on the Web (Sun, Cisco, Federal Express) are already experiencing multimillion dollar savings through Web-based customer service and order entry. Banks and other retailers will get to the same point in a year or two.

7. Deal with Bill Payment: Bill payment probably deserves special treatment in your business case. For one, it’s a customer service black hole, frustrating both user and service rep as the bank (either on its own or through its service provider) takes on a new role as go-between among the user and merchant.

Right now the economics of bill payment are disastrous. For every check turned into an electronic item, saving you maybe a dime, you incur customer service costs of $0.10 to $0.50 per item and vendor processing costs of $0.30 to $0.50 per item. No matter what you charge users, you’re probably operating with a negative contribution (variable costs are greater than variable revenues), so the more volume you project the more you lose.

But the economics of digital bill payment will be reversed within the next few years as electronic bill presentment schemes take hold (see Microsoft/First Data announcement p. 24-25). Not only will the cost of end-to-end electronic payments become less than the cost of paper items, the customer service costs will pretty much disappear, and if the Microsoft/First Data business model holds, the vendor processing costs may disappear as well. In fact, bill presentment could end up being a profit center if it follows the precedent of credit/debit cards with interchange flowing from the acquirer of transactions (Microsoft/First Data) to the bank servicing the end-user’s transaction account.

All this makes bill payment difficult to cost out in a five-year business plan. Our recommendation: zero out bill payment beginning in year 2000. In other words, assume the cost to provide bill payment is exactly equal to what you can charge for it. Whether this falls to zero or not doesn’t matter. The important thing is it doesn’t drag down your business case as subscriber volumes ramp up 2-3 years from now.

8. Estimate the Value of Other Intangible Benefits: The final area of revenue forecasting is a catch-all for estimating the value of the less-quantifiable benefits of online banking. Even if your bank steers clear of “warm and fuzzy” or “soft dollar” benefits in its financial analyses, you should at least summarize them in a chart, or better, quantify them and include as a footnote to the financial analysis. In our example, we show intangibles “below the line” and they are not included in the net present value (NPV) calculation. Below are some of the major intangibles to consider:

• implicit fee income (the ability to charge higher fees
  on other products due to the value of online access)
• the value of being perceived as an innovator
• ancillary revenues such as commissions, referral fees, sales of aggregated user preference data, etc.
• the value of Web as communications vehicle to community, investors, press, etc