The Imperative For Operations Transformation In Financial Services

It is clear that a new “modern operations leader” is beginning to emerge

Across financial services, the need to manage operational complexity at scale creates ongoing discussion on how to transform operating models so as to gain greater efficiency and flexibility.  In the late 1990s and into the early 2000s, operations functions went through a paradigm shift. Concepts of centralization, offshoring, standardization, consolidation, process re-engineering and outsourcing abounded. This shift created large operations centers housing tens of thousands of employees across the globe, all performing interconnected tasks that together completed a transaction. The focus was on employee productivity, labor arbitrage, and managing down error rates.  Fast forward to today, and operations has changed once again. An emphasis on large labor forces conducting manual tasks has been superseded by the need to reduce headcount and provide value-additive services to customers. Automating key parts of the value chain – especially repetitive tasks – has become a focus, and technology has been critical in enabling this shift. Operations has become “smarter.  ”Despite significant advances, many promising technologies – such as artificial intelligence, machine learning and robotics – have only been sporadically adopted. Operations remains an area where there is tremendous opportunity to drive efficiency, reduce costs, and, at the same time, enhance customer experience. The technology exists to make that happen. The “missing link” is a modern operations leader: an executive who understands both the core business and the technologies that can drive transformation and who has the change management capabilities to implement these technologies as solutions.  Through interviews with operations leaders involved in large-scale transformation and extensive research on the market and its key executives, this paper explores the drivers behind this, and the implications for financial services firms.

There is a clear impetus for change

Operations transformation has never been more important than now, and there are several critical drivers that underpin this – lower revenue growth, shifting customer expectations, greater regulatory pressures and increased scrutiny, and economic uncertainty – particularly in the COVID-19 environment.

Leaders highlight how these drivers affect the entire financial services ecosystem, demand urgent attention, and provide clear impetus for change in the way that financial services organizations operate.

• Stagnating revenue growth

• New customer expectations

• Regulatory pressures and scrutiny

• Economic uncertainty (including from COVID-19)

The resulting transformation can have three critical implications for business: 

In each of these three key areas – reducing headcount, improving customer experience, and increasing profitability – technology has a fundamental role to play.

The exact technologies deployed vary – including applications as diverse as AI, microservice architecture, API, bigdata, cloud, and blockchain – but all can be used to achieve these outcomes, alone or in combination.

There are a plethora of examples, from across banking and financial services, where organizations have started to improve in these areas by leveraging these tools – and many more – across different parts of the operational value chain.

01. Reducing headcount

Elimination of manual processes, reducing excessive spend on low-value tasks that will free up employees for value-additive tasks

02. Improving customer experience

Providing services more effectively, more conveniently, faster and at lower cost

03. Increasing profitability

Taking better decisions, that reduce losses and get higher share of wallet from customers

Reducing headcount through technology

Many financial services organizations have historically relied on large human workforces to manually complete the processes that underpin their business – often adding no real value to the end customer.

20% of FS roles could be automated in the next five years

Source: KPMG/Harvey Nash, 2019

Even within customer-facing parts of organizations, time is spent on answering basic queries (such as a customer’s current balance) that could be answered with an automated process, a chatbot, or a sophisticated IVR.

Technology exists to reduce inefficiencies and allow smaller human workforces to add much more value, reducing one of the major cost bases of every business.

Case Studies

Fidelity has deployed AI/ML to make its customer service workforce more efficient and less human-intensive, by providing agents with answers to the enquiry the customer is most likely to make.

A number of global insurers have applied RPA to reduce significantly the time taken in, for example, the administration of claims processes: Zurich announced in 2017 that robotics had already saved 40,000 work-hours.

JPMorgan uses NLP to extract the most important clauses from its internal legal documentation – reducing the manual burden of document review by hundreds of thousands of hours per year.

Chatbots, such as Bank of America’s Erica – now used by over 10 million customers – use RPA to allow customers to access service provision without routing through a human agent.

Citigroup and Goldman Sachs conducted the world’s first equity swap built on blockchain, using a platform which automatically updated and verified variables including end-of-day prices, dividends, stock splits, and variable interest rates.

Many banks now routinely deploy RPA in branch, in the form of “banker tablets,” which use automated processes to call up the most relevant information about a given customer, allowing fewer human branch employees to add more value.

Improving customer experience through technology

Technology can drastically improve customer-facing operations across financial services – whether through adding value in new ways, simplifying processes involved in making applications or claims, allowing existing customer support networks to provide faster, better advice.

16 points average NPS lead of technology firms over banks in the UK

Source: Marketing Week/ MaritzCX research, 2019

These can be achieved in a wide variety of ways – but all contribute to enhanced customer loyalty and build brands, enabling organizations to better compete with high-touch digital products.

Case Studies

Technology-powered InsurTech startups, such as By Miles and Cuvva, have built “pay-as-you-go” insurance solutions allowing customers to access products in a much more flexible way.

Allstate uses an NLP-enabled database to provide its sales executives with better access to product data, letting them give customers better guidance in the process of quoting and issuing commercial lines products.

Several banks, such as BBVA, Capital One, and ING, have launched apps – o­en including RPA-powered chatbots and limited AI/ML – to provide high-touch, experience-enhancing services, including money management advice / spending tracking.

Ageas uses an AI/ML powered claim assessment product for its automotive insurance offering, allowing customers to use photographs of damage as part of the claims process.

Nationwide Mutual Insurance has developed APIs that allow pension management apps to communicate with the Nationwide database – providing customers with fast, easy access to their pension data.

Deutsche Bank has used a combination of tools – including optical character recognition – to extract information from account opening documents, allowing customers to open new accounts in a matter of minutes.

Increasing profitability through technology

Outside of reducing workforce costs and enhancing customer experience, technology operations can dramatically improve the profitability of existing products.

19x faster growth in profitability in the most digitally focused banks compared to the least

This can include using data to improve cross-selling, creating new channels through which products can be provided, and improve largescale processes like claims handling or document storage.

Case Studies

BlackRock has moved its Aladdin service to Microsoft’s Azure cloud, allowing it to better meet client demand for low latency, technology-as-a-service products.

JPMorgan deploys Boost Intercept (a payments system driving STP in transactions) as part of its commercial cards offering, allowing clients to automate previously “un-cardable” employee payments to suppliers without manual inputs.

AXA is deploying AI/ML to analyse transcripts of phone calls in motor claims conversations, and using the resulting data to provide better initial claims estimates.

Wells Fargo has used robo-advisory to reduce its basic management fee to 0.35 percent, compared to over 2 percent for the majority of its human-run wealth management services.

TD Ameritrade has seen significant success with the provision of VEO, which integrates deeply with a variety of third-party applications and gives RIAs a secure way of holistically understanding their clients.

Deutsche Bank uses AI/ML-powered data tools to create cross-selling recommendations around customer accounts generating incremental revenue with minimal human intervention.

HSBC has deployed blockchain to store (formerly paper-based) records of private placements – with a value totaling $10 billion stored in this way. As well as creating cost savings in the long term, the project also streamlines access to this valuable data set.

Obstacles remain to transforming technology 

Operations leaders consistently highlight that technology is not a silver bullet. It will not instantly fix every problem that confronts an organization. What really matters is the way in which it is applied. Making a bad process happen faster will not result in long-term value creation if it doesn’t address the root cause of inefficiencies, even with the best available technology applied to it.

70% of large-scale, complex digital transformation projects fail

Source: McKinsey, 2018

The application of robotic process automation (“RPA”) has been a good example of this. In some cases, robotic processes have replaced manual processes like-for-like – software is used to input data in exactly the same way that a human would. While this has generated incremental improvement, it has often resulted in process breaks – where a single activity passes between two parts of an organization persisting. While individual parts of the process become faster, the root cause of the issue is not addressed.

Modern operations leaders therefore need a much more strategic lens on the function, one which carefully considers where improvements can be effected, and aligns process flows with long term business requirements rather than making piecemeal changes to the way that existing tasks are undertaken.

Operations leaders are battling a legacy concept of what an operations function does

The difficulty that this presents is that the role of the operations leader, as traditionally understood, does not necessarily align with the requirements of a successful technology-driven transformation.

Operations leaders today need a deeper understanding of advanced technology and the talent that they will require, rather than a career managing tens of thousands of customer service and operations agents across outsourcing / offshoring centers. Much more important to a successful transformation is the ability of operations leaders to be the liaison between the needs of the business and the technology function – to understand fully what is technologically possible, and to match that against what is required to effect real, productive change.

Equally, a new degree of change management capability is required. Operations transformation means making serious, large-scale changes to many aspects of the way that a business is run – and operations leaders need to be able to communicate this effectively, ensuring that projects are not waylaid by nervousness or resistance to change in the organization. There is also a fundamental business angle to this – many applications of transformative technology run the risk of cannibalizing internal revenue if applied thoughtlessly, and the operations leader needs sufficient business leadership experience to understand and mitigate this.

A new paradigm for operations leadership

The traditional skill set of the operations leader will not go away. Operations will continue to lead teams at scale and handle budgets that, in many cases, form a significant part of overall cost base. The capabilities that make this possible will be vital to a best-in-class operations leader for the foreseeable future – but these capabilities are now necessary, but not sufficient.

What new skills are required?

In addition to the core skill-set, the pace of change in the application of technology to operations means that the modern operations leader will also be:

• a strategist who can clearly see and shape the organization’s vision on how it intends to differentiate itself in a competitive and ever-changing landscape, and articulate this compellingly to internal and external stakeholders;

• a technologist who understands emerging technology trends and what it means to his business, and who knows the limits of the possible in the context of the organization;

• a product manager who can deploy these technologies by building software and digital products, whether for internal use or customer facing, which are created across the business and meet real needs;

• a change agent who can work collaboratively with business unit leaders, risk and credit heads to ensure that the pace of change does not disrupt core revenue flows or create internal tensions; and

• a business savvy, commercial leader and not just a back-office operator; a leader who comprehensively understands the impact of each decision on the core revenue lines of the business and can take a “big picture” approach to avoid excessive internal cannibalization.

Meeting the talent challenge of the new operations leader 

Given these new requirements, we anticipate that the operations leader will require new skills that span emerging technology, operations, data and change management.

Not only are the requirements themselves broader – often requiring a more diverse background for the operations leader, as opposed to a “pure” operations career – but the skill sets required are in higher demand than ever. Technology, product, and change management talent is always at a significant premium, and this extends beyond financial services and into consumer, digital, and technology. Banks, insurers, and asset managers can anticipate competing directly with scaled technology organizations, including Google, Amazon, and Facebook, for senior operations talent. Equally, strategic and commercial leadership are inherently valuable in any part of a business – deploying this talent in operations will, necessarily, mean not deploying it elsewhere.

In short, there has never been a more difficult time to source truly best-in-class operations leaders – or a time where the potential pay-off from doing so correctly is so high.

Additional Authors

JAKE STRONG is a member of Russell Reynolds Associates’ Financial Services knowledge team. He is based in London.