In an era where the eyes of the world’s regulators are focused more than ever on the banking industry, the opportunities to make a quick buck are getting fewer and further between. The sort of exotic money machine products that were so prevalent in the years up to 2008 are now out of the question for most banks.

Financial institutions are looking to achieve pre-recession strength, without incurring the same risks that got them there in the first place. All are also keen to do so without the equally damaging reputational risks posed by questionable practices treated as cash cows in the early 00s.

There are few financial institutions in the world that do not have work to do in terms of rebuilding reputation of the industry – but the bottom line is well, exactly that – the bottom line. The task at hand is to return the big banks of the world to their former glory, without revisiting some of the darkest days of the industry. The fat margins enjoyed in the past cannot be regained by the same means, so significant innovation is required. However with research showing the combined gains of preventing revenue leakage can be up to ten percent in the case of investment banking, and 4 percent in retail.

While revenue leakage is not a particularly glamourous topic, it affects every stage of the customer lifecycle – prospecting, on-boarding, transaction processing, billing and recovery, monitoring and service termination – and is often grossly underestimated in initial business cases for revenue management and business assurance transformation projects.

The solutions put in place are manual, which drive operational costs and regulatory risks, negating many of the initial advantages of such a scheme. An automated real-time monitoring solution, which can identify small sources of revenue leakage, can go a long way to identifying faults as soon as they appear.However, monitoring is not enough. A great deal of revenue is lost each year because core banking and billing systems are simply not flexible enough to account for different customer requirements. This is not simply a question of customer satisfaction, but a matter of potential revenues which cannot be booked.


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A customer may ask for a service that the bank simply cannot provide, or the customer may use a service, and the bank actually lacks the ability to charge them.  For example, many applications lack the ability to calculate fees on daily basis – this means every customer joining in the middle of the month cannot be charged until the beginning of the next month. The alternative is to charge the full fee for the partial month, not something customers are often too happy about.

What the industry needs is better management of financial, staff and customer data, and the ability to cross reference them at will and without restriction. This requires software layers capable of communicating with core systems, staff-facing interfaces, and customer-facing applications. New technology makes this possible, and the ability to do so offers a cost-effective opportunity to implement consistent tender offer margin controls, revenue audits and pricing review automation.

Fundamental business assurance of this type doesn’t only address revenue leakage, but can also directly enhance business management analytics thus providing critical capabilities needed to rapidly address and resolve low performing regions and products. A centralized pricing and billing platform with its function separate from, and sitting on top of, the core banking infrastructure, can do a lot to provide the flexibility that is needed to tackle the sources of revenue leakage.

Revenue leakage that merits a great deal more attention than it receives. While each individual source of revenue leakage may on its own represent a relatively insignificant loss, when aggregated together, the total can provide a very significant gain in actual revenues.

In the past, it would have been uneconomical to pursue each source of revenue leakage, but advances in software have changed this and it’s a gain worth pursuing for a bank of any size.