After several years of balance sheet shrinkage, banks face a moment of truth. Despite a mass withdrawal from unprofitable or capital-intensive business lines, returns remain stubbornly low. According to Coalition, a financial analytics and consulting firm, the top investment banks achieved a return on equity of just 6.7% last year. Compare that with a cost of capital in double figures and a sense of the problem starts to emerge.
Waiting for these trends to reverse is not an option. As a recent paper by Morgan Stanley and Oliver Wyman predicts: ‘Many banks will fail to meet their cost of capital in the next two years, especially in Europe … Despite removing $4trn to $5trn of balance sheet, a similar amount of risk-weighted assets and $20bn of cost since 2010, there is still too much capacity relative to the forward-looking client revenue opportunity.’ To compound this, regulation is pushing up the costs of capital and collateral.
Against this backdrop, many banks are stuck with back offices built for a pre-crisis world that relied heavily on steady product and revenue growth. Before 2008, the emphasis was on promoting and selling new products. The idea was simple: get the revenues and the ‘factory’ could take care of itself. In today’s world, those factory costs need pruning and the industry needs an operating model in line with the economic reality.
This is spelled out in the Morgan Stanley/Oliver Wyman paper. For all the cost-cutting of recent years, it says, ‘infrastructure costs have stayed resolute … success over the next two to three years will hinge on banks being able to overhaul their infrastructure cost base and respond to new technologies.’ Up to 20% of infrastructure costs, or around $15bn, could be released, it suggests.
At Euroclear, we believe that doing this successfully requires a new approach. Much of the cost cutting to date has had limited impact. Consider offshoring. Savings on labour and premises have often come at the cost of increased complexity. Tasks have been broken up rather than unified. Expertise built up over years has often been lost and turnover within the offshore operation can be high. Direct costs may fall but indirect costs often rise.
Straight-through processing (STP) is often viewed as the panacea – and it can be. Many trading activities have been successfully automated. But there are always breaks to deal with. The more a firm automates and the leaner it gets, the more sensitive it becomes to exceptions. There is a magnification effect when there are too few people on tap to swallow up a problem effortlessly.
The low-hanging fruit has been picked, and much of what is left has so far been difficult to fix. People trumpet STP rates of 97% or 98% but they rarely mention the cost of dealing with the other 2% to 3%. The breaks are often down to data protocols and too expensive to resolve. What’s more, many systems are duplicated and there are vertical silos with major differences between markets, geographies and instruments. And on top of all this, there is a regulatory agenda that takes precedence over rationalisation and re-engineering. MiFID II, Basel III, EMIR, Target2-Securities – the impact is cumulative, the deadlines tight and the required investment deep.
Breaking out of this straitjacket requires fortitude and creativity in equal measure, and taking a new look at solving some of the most persistent problems back offices face.
A systematic approach
In a low-return environment, the pressure on banks to reduce infrastructure costs is intense. In the pre-crisis era, the C-suite focus was on maximising revenue growth, not limiting operations costs. Today, the situation is reversed.
This poses a challenge that many back offices are struggling to deal with in their current setup. There may be legacy systems that are no longer fit for purpose. And there is often pressure to be increasingly integrated across time zones and inevitably the need to comply with multiple regulatory initiatives.
Most banks have made the obvious moves to automate and re-engineer, but are now asking themselves how they can move to the next level. There are no easy answers, but there are four themes worth exploring:
1. Automating areas which can still be automated
2. Improving efficiency around tasks requiring manual intervention
3. Re-eningeering back-office systems
4. Improving the data model under which firms operate
First, there are still business areas and processes that have been left behind in the drive for automation or where there is an absence of structured messaging. Often they involve multiple parties and complex data. Take corporate actions. While some processes cannot be automated today – translating legal documentation into operational data, for example – the strides being made in machine learning suggest more automated solutions to complex tasks will be available down the line. Other areas are easier to tackle, such as claims management, which is still largely conducted through emails, faxes or even letters. Here the data is much less complex and there is a good business case for automating processes as it frees up capital and liquidity by reducing credit exposures and transaction times.
Second, while human intervention is likely to remain a necessity in certain areas, the challenge is to find ways of improving efficiency and productivity within the current imperfect structures. The solution may be as simple as being able to communicate with the right person on the other side of the trade quickly and easily. That is all about cooperation, but it requires more than casual networking. The solution lies in structured collaboration and peer-to-peer communication.
Third, re-engineering continues in every firm and each faces its own unique challenges. A common issue is how to accelerate and de-risk the change process itself. Here, focused, easy-to-implement solutions are preferable. That’s because the lengthy programmes needed to fundamentally change operating platforms are difficult to maintain from both a technical and a governance perspective. Technical because of the sheer complexity of the change required. Governance because the corporate structures of many institutions impede rapid, agile development and roll-out, instead pulling time and resources into managing a vast matrix of stakeholders across business lines, functions and geographies.
Finally, there is the data model under which banks operate. The intermediation role financial services firms provide relies on the efficient management and exchange of data – in distribution, financial modelling, credit assessment or risk management. In the long term, new ways to improve and manage the transfer of data will be key for increasing efficiency, reducing operational costs and improving balance sheet. This is where big data and particularly distributed ledger technology – or Blockchain – offer such promise. A host of initiatives are now underway in this field and could yet prove transformative.
In all these areas, it is not necessary to wait for a big bang solution. There are things banks can and should be doing now, and in some cases the solutions already exist.