“We’ll call 2015 the year of the pancake” was how Mike Mayo (analyst at CLSA) described a year that saw the six biggest banks in the US produce revenues that did not rise from their 2014 levels. Banks have operated within a difficult environment since the financial crisis, which has seen revenues hampered and escalating regulatory costs. These challenges look set to continue for the near term future at least and continue to impact the ability to increase returns on investment.
The mood in many quarters seems to be to keep running on the treadmill, and eventually the historical issues will disappear. However, we believe that the most successful banks will be the ones that leverage two of their key assets – data and people.
The environment that banks find themselves in is certainly not one to envy. Since the financial crisis, banks have struggled to generate revenues through net interest margins (the difference between the interest banks charges on loans and the interest it pays for deposits) because base rates have remained at near record low levels. In addition, recent slow growth in China and the slump in the oil price have negatively affected investor confidence, resulting in reduced bank trading and investment revenue.
On the other side of the equation, the industry continues to grapple with the continued wave of regulations that are costing billions to implement which shows no sign of slowing down. With these challenges negatively impacting revenue and costs, investment banks achieved a return on equity of 7% in 2015, well below the mid-teens that their investors look for.
The response so far
Banks have responded to these challenges by looking for opportunities to diversify and grow. For instance Goldman Sachs, who predominantly serve institutional clients, has ventured into personal banking for retail clients with GS Bank. However, diversification opportunities are limited and require movement away from core capabilities and hence are inherently risky and expensive.
Another response has been to bolster revenues through increased fees and charges. Banks such as Wells Fargo have sought to increase service charges on customer accounts including ATM fees, overdraft fees, maintenance charges. However, this is ultimately a tactical solution rather than a sustainable long-term answer. It would be very hard to put your fees up every year and retain your customers.
With revenues ‘flat as a pancake’ and forecast to stay that way, costs rising due to the increasing burden of regulation and avenues for growth and cost-cutting nearly exhausted, how are banks to retain their competitiveness?
We believe the answer lies in extracting more value from the two resources readily available to any investment bank – their people and their data.
Not so long ago, data analysis was a one-off exercise, often outsourced, to shape the one, three or five year plan. Under this model, strategic decision-making stayed in the hands of a few and was based on data that is often past its sell-by-date by the time a decision was made. Today, technological advances have improved the usability and sophistication of data analytics tools. Analytical tools now make it easy for all levels of management to structure and analyse real-time data in order to make well-informed decisions. Advances are not confined to just analysis. Data visualisation applications have revolutionised the way we can view and digest data. This is a powerful step change, insightful and visually compelling real-time analytics can be at the hands of every middle-manager.
Innovative banks are now investing in data science, long since practised by tech firms such as Google to automate decision-making. Predictive analytics may sound like the stuff of sci-fi novels but it is happening now and those late to the game may suffer.
This is not about the robots taking over
Sophisticated tools will not be enough to tip the scales. We believe the organisations that will gain the greatest competitive advantage will be those with an operating model where people and data act as a complementary force.
Data-driven decision-making helps people make more informed decisions, and faster. Automated decision-making does not replace human intervention. It removes low-value processing activity to allow people to focus their efforts on developing and acting on the strategic insights hidden in their data. It is the difference between an army of people completing UAT testing and an army of people working out how they are going to fix the bugs in the system to deliver optimal performance.
This may appear deceptively easy. Firstly, data analytics needs to be embedded as core capability within any management role. This will require a well-considered approach to training. However, the bigger challenge may in fact be cultural. It is not only that people may not know how to manipulate and present data to drive decision-making. It can be that they refute the idea that they need to. Addressing this mind-set will require a cultural shift.
Addressing the cultural shift
We believe that change management is key in approaching the cultural shift that needs to occur and that the key lies in selling the benefits of the new data-driven approach. The simple automation of previously time-consuming data reporting or the automation of low-value, tedious activities should be a powerful sell in many organisations.
Additionally, real-time decision-making often leads to rapid changes in direction to respond to the latest information. This, at first, does not make people’s lives easier. Suddenly strategic direction has a 24 hour lifespan. That is very unsettling for people who are used to strategy having a shelf life of one year at the very least. This requires robust change management skills to encourage global teams to operate in regular bursts in direction. It requires the flexibility and agility to change course regularly. People’s roles and responsibilities become fluid. This requires trust and a totally new way of working. The team has to engage with the numbers, believe that the analysis is robust and the direction it provides stands up to challenge. It requires a change in recognition and reward and that the star performers do not excel alone, but flex workload globally to maintain the optimal performance that the analysis tells us is possible.
Does it really work?
At Moorhouse we believe that change management and data analytics work hand-in-hand to accelerate performance and our experience backs up our belief. With our help our clients have doubled output, saving over 800 hours of manual effort. They have performed complex analysis themselves, with key insights being made available to the experts. Through a focus on change management we have helped our clients embed agile ways of working that make rapid changes of direction possible.
Banks still face a challenging road ahead. However, if people are empowered to make better and faster decisions through the use of data, we believe they’ll be better equipped to face the challenges ahead.
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