Implementation of data analytics can’t wait – banks must improve sales and trading productivity today
The drive for more productivity amongst FICC-trading financial services institutions has never been greater than in today’s challenging market conditions.
By Matthew Hodgson, CEO of Mosaic Smart Data
It’s little secret that FICC businesses in many banks are struggling to achieve profitability and ROC, while dealing with increased regulatory burdens, cost pressures and the impact of COVID-19.
Against this backdrop, banks must do everything in their reach to improve performance and get the most out of their sales and trading teams – and a recent survey shows they are indeed stepping up their game in this regard.
The survey, conducted by PwC, found that an overwhelming number of financial institutions recognize that they must accelerate productivity efforts if they are to create sustainable business models. 72% stated they were planning to implement specific productivity measures, compared to 53% in 2018.
But what tools do banks have at their disposal to achieve this goal? Data, analytics and AI have become the number one driver of gaining a competitive advantage through increased productivity across industries. Investment banking is no exception.
The range of innovative digital technologies available to boost the productivity of human bank employees has exploded in recent years and, according to PwC’s survey results, the industry is capitalising with almost 80% of institutions using these tools for this purpose.
Of these institutions, 54% are using AI, 40% deep learning and 37% robotic process automation – and 90% of these businesses have seen an improvement in productivity as a direct result.
With statistics as clear cut as these, the benefits of tools that turn big data into smart data come into sharp focus: a stronger understanding of trends, market activity and client needs, to name just a few.
It’s clear that implementation of these technologies can’t wait – banks must act today if they are to unlock new opportunities and improve the productivity of their client relationships. But how can they leverage their unique position as the custodian of information and knowledge and deploy these technologies to maximum effect?
Information is king
Data-driven banking is no longer the future or a ‘nice to have’ – it’s the present and it’s critical. Sales and trading teams are now required to be able to understand and mine vast quantities of internal and external data, giving them a comprehensive overview of their clients’ trading activity, enabling them to make informed decisions and appropriate recommendations.
It is a simple fact but worth re-stating that clients value information. Even in flow markets, salespeople that provide insights and advice generate better business from it.
A smart data solution that can deliver the necessary data consistency and granularity for existing information to be analysed in one consolidated platform is clearly a major step forward. However, it also needs to be able to do this in real-time, while simultaneously enriching in-house information by consistently integrating external data sources.
At the most basic level, this can immediately transform the productivity of the existing analysis a bank is able to provide. A common complaint among data scientists is that they spend most of their time in data wrangling rather than actual productive analysis. If all transaction data is now accessible by data scientists and quants in a single consistent format, then this challenge is virtually eliminated.
But the benefits of consistent data apply universally across the business, not just to data scientists and quants. If the solution that transforms the data also includes actionable reporting and rich analytics, then the quality and productivity of analysis throughout the FICC business in general also rises – as should profitability.
A smart data solution that makes available a large repository of clean consistent transaction data represents a major opportunity for artificial – as well as human – intelligence. Data scientists and quants will also be able to work far more effectively in developing AI and machine learning (ML) tools if they are no longer hamstrung by deficient data sources.
While in many instances AI and ML have been seriously over-hyped, in the case of an investment bank the immediate opportunities for productivity gains are genuine. One example is the extension from humans to machines of the fine tuning of client relationships mentioned earlier. Other business sectors – for example online retail – have long been doing this by mining and analysing client transaction and interaction data and then using AI/ML to drive more customized and personalized service and hence productivity and profitability. This is equally applicable to a FICC trading business.
Cultural stasis: the gorilla in the room
In the current market environment, many banks’ FICC businesses need significant re-engineering to retain a competitive edge. The traditional sales function at investment banks is simply no longer fit for purpose, but cultural stasis is the gorilla in the room when it comes to improving productivity.
Data is clearly at the centre of the re-engineering required by banks, but analytics must be championed from the top if an institution is going to truly evolve. This often requires a total cultural overhaul for a bank.
The good news is that the bulk of the information needed for this transformation is already within the enterprise, so major and costly data acquisition is not needed. However, leaders must not be stubborn in the face of change and focus on establishing a culture of analytics – which means hiring the right people and deploying the right technology.
Looking further ahead, making the right changes today can deliver significant long-term returns. Smart data and smart analytics can certainly be used to achieve a profitable improvement to productivity in the immediate term, but equally importantly they can also serve to future-proof the business.
The same PwC survey mentioned earlier also found that financial institutions are spending, on average, a staggering 14% of annual operating costs on change management functions in order to drive greater productivity gains.
Responding to future change more effectively is one of the core benefits of gaining control over data and utilising it to its full potential. Those firms who make optimal use of smart data and analytics today will also be able to anticipate and prepare for change far more efficiently and profitably in the future. Herein lies the key to real, quantifiable productivity gains.
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