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By Mike Wallberg | 15 September 2016

If you listen closely to the lyrics to the classic children’s song, “There’s a hole in the bucket,” you’d realize they could have been written by Joseph Heller. Famed for penning Catch-22, Heller saw the futility and irony that surrounds so much of us in our day-to-day. In the song, poor Henry and Liza struggle to mend the infamous bucket because the water they need to sharpen the axe, to cut the straw, to plug the hole… keeps leaking out.

Running a cash management business is not dissimilar as revenue leakage, or the failure to collect all potential revenues due, can become chronic if not addressed systematically. No sooner do you plug some hole – rectify a series of contracts that aren’t being billed properly – than you realize the discount you offered a giant corporate customer is unprofitable because it’s not meeting a specified condition, e.g., a minimum-deposit threshold it accepted, that you have no way to track.

In a treatise on rapid digitization in banking, McKinsey writes about leakage in the context of what they call dual manual and digital “ecosystems” that don’t communicate. “This leads to leakages on the ground,” the authors write. “Financial companies therefore need to ensure that the physical and digital worlds merge seamlessly and that there are no break points.”

To illustrate, they point to the experience of an anonymized “large universal bank” that – even after undergoing a significant digitization program – only reaches true automation for 35 percent of what they estimate are 600 individual processes. Manual practices persist.

 

Figure 1: While banks have made significant strides in transforming their operating models, significant opportunity remains in automation.

revenue_leakage_calculator_01 (2)

Source: McKinsey.

 

Measuring the leakage

Zafin recently undertook some research that revealed the most insidious characteristic of those pesky bucket holes: banks don’t often realize how numerous or big they actually are.

We took a snapshot of the sources and scale of revenue leakage at a handful of banks. While the data-set is admittedly nascent, the findings were surprising, both for their scale and consistency. Focusing in on two central sources of leakage – processing issues and errors, and poor price governance – the work sought to quantify the “average” leakage experience across this group.

The data. The constituents were four large banks with assets ranging from $100 billion to over $1 trillion, located in North America, Europe and the Middle East. To this group, we added input from Deloitte’s Revenue Leakage Advisory, which works with Tier 1 banks globally, helping them quantify these exact metrics.

The data points for which we developed percent leakage ranges were:

  • Processing issues and errors due to manual processes
  • Processing issues and errors due to existing automated processes
  • Poor price governance with large clients
  • Poor price governance with everyone else

 

We then built a calculator incorporating these ranges capable of evaluating real-life cash management revenue opportunities. The calculator accounts for the size of a bank’s cash management business, the degree to which it relies on manual processes, and its exposure to large clients within its global transaction banking portfolio.

The results. For the most common scenarios, the calculator yields an approximate leakage range of three to 12 percent of existing revenues. In other words, a $1 billion cash management business with an experience in line with these averages could be leaking anywhere from $30 to $120 million every year.

How can this be?

 

What causes leakage?

Processing issues and errors can encompass everything from physical payments handling, approvals via email and deal committees, incorrect straight-through-processing set-ups, to Excel-based management of pricing offers, paper-based onboarding, billing changes made manually and more. A failure in any one of these, perpetuated annually across a bank’s client base, can quickly become very expensive.

We’ve written extensively about price governance in past editions of the Relationship Banker (here, here, and here). The main culprits in a cash management setting include untracked conditional offers, unenforced price contracts, loosely controlled exception pricing (fees and waivers), long lead times to effect price changes, and ineffective suitability filters.

In talks with both the contributors to the research and bankers with whom we’ve discussed the findings, these themes emerge again and again and again. It doesn’t seem to matter if it’s a very large multi-national or a small community bank: the ability to effectively track condition fulfillment and “turn off” promotional pricing when appropriate evades most banks. So unwarranted, discounted pricing persists perniciously throughout the banking system, nibbling little holes in the buckets CIOs and business heads work tirelessly to fill.

 

Figure 2: The many potential sources of revenue leakage.  

revenue_leakage_calculator_02

Source: Zafin.

 

Large investments of both time and money in executing simple price changes is another major source of leakage, with many banks citing six to nine-month ordeals costing millions every year.

 

How can banks plug the leakage holes?

At the heart of these problems – both processing and governance – is insufficient control. Control over the data that banks are generating, collecting and processing and control over how offers are conceived, approved, extended, tracked, and reviewed. And the cost of the leakage is visible (IT hours spent patching stop-gap solutions), invisible (foregone revenues from price increases and enforcement of existing contracts), and what I’ll call “potential” (the inability to communicate and apply pricing correctly introducing the notable and increasing liability risk of regulatory fines).

We discuss this month what a gold-standard cash management solution looks like in our feature article, Four arrows for your quiver: Building a successful cash management business. With specific regard to the two leakage drivers isolated by the model: a centralized data warehouse for product and pricing can go a long way to solving these problems.

By connecting multiple, siloed pricing and billing systems through a central clearing house, banks can configure, bundle, and implement relevant products for specific segments and then create, simulate and manage standard pricing, exception pricing and regular pricing reviews for both fee- and rate-based products.

Importantly, by establishing a central point of truth for each element of each client contract, banks can track their fulfillment of conditions (or lack thereof) and then automatically adjust pricing, billing, statements, and the general ledger. So that a big client that never delivered those balances can pay full freight until it shows you the money, and your relationship manager can be aware of it without being burdened with tracking and enforcing it.

There may be a machine-gun’s spray of holes in your bank’s bucket, draining it year after year. But you can make your bucket bullet-proof. You just have to know where to look.

 

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