The financial services (FS) sector is under more pressure than ever. Juggling the effects of the pandemic, technological disruption and high customer expectations, coupled with maintaining business continuity, has been a difficult balancing act – and yet these factors are critical to FS. Neil Murphy, Global VP at ABBYY, explores how this has led some teams to butt up against the long-held rules and processes of the sector.

In order to see success, banks and FS firms need to take a long, hard look at how their business really works. This means getting visibility into business processes as they actually behave, identifying variances in them, and discovering how they can better meet customer and business needs.

With the world under unprecedented pressure, finding out how best to manage rules and processes can alleviate the strain and set your business on the path to success. Our recent research found that almost half (46%) of banking and FS workers and 30% of insurance staff rigorously follow the rules – giving the industry a good head start in coping with what’s thrown at them.

But is following the rules always the best route? And what happens when employees break the rules?

Rules – there to be followed?

Banking and financial services staff are working harder than ever before to help customers, keep businesses afloat, and also digitally transform. In such a process-driven industry, honing the many rules and processes could be the key to survival in this economy.

Our recent research found that almost half (46%) of banking and FS workers and 30% of insurance staff rigorously follow the rules – giving the industry a good head start in coping with what’s thrown at them.

At this point in time, it’s vital that banks and FS teams check in on their processes often to see where issues lie, which processes are most problematic, and which are ripe for automating. Following the rules is the cornerstone of achieving the potential of digital transformation, according to a McKinsey study which found that half of the value from digital transformation can be realised from as few as 10-20 end-to-end processes.

What tech brings to the table

While digital transformation is nothing new to most banks and financial institutions, now more than ever, they must rely on technology. It will help them conduct better business, comply with regulations, connect with customers, and deal with an ongoing flood of emergency business issues.

Getting your processes in order before automating them is a crucial step to avoiding failure. Yet many banking and FS staff claim that processes are too complex or there are too many to follow.

This is where technology comes in, and encouragingly leaders are open to helping their staff using technologies that can lighten the burden. According to our research, almost all banking and FS bosses think process mining technologies would be helpful to their business (98%), as did 89% of insurance bosses. These technologies can free up time for finance staff, enabling them to work on more pressing business matters that require the human touch.

Bending the rules 

Rigorous rule-keeping is a trait the financial industry needs to uphold, in order to comply with stringent industry regulations. But there is a flipside.

[ymal]

Key to a bank or financial institution’s success, especially in this digital age, is how they adapt and respond to customer needs. This means that even in a process-driven industry like financial services, employees occasionally break the rules. Sometimes, they have good reason: the most common reason to break the rules is to provide good customer service, which is more critical than ever before. Our research found that 62% of insurance bosses have confidence that their employees break rules so they can meet the needs of customers, and 50% of banking and FS bosses agree.

Relationship-building services like customer care, supplier management, or simply supporting colleagues and staff, can go a long way in benefiting a business and boosting morale. Being willing to bend the rules when it’s better for customers illustrates that rather than financial services staff being solely process-driven, they are driven even more by customer satisfaction.

So where do we start?

Unfortunately, customers are used to delays and layers of processes when it comes to banking. But it doesn’t have to be that way. To better serve customers, while also ensuring staff aren’t straying too far from the rulebook, the FS industry needs to be able to identify the bottlenecks and blind spots in every engagement. They also need the ability to analyse and discover processes using all the data they have.

Process intelligence technologies offer a deep understanding and real-time monitoring of processes. It helps you drill down into the details, explain why processes don’t work and how to fix them, and provides the tools to solve problems a business didn’t even know existed.

Say a customer loses their debit card. They shouldn’t need to go through the time-consuming process of calling various support teams, keying in endless numbers, and being put on hold, only for their account to be frozen as a precaution. By having every process mapped out and every piece of data available on an analytics dashboard, staff are given the knowledge of where customer service bottlenecks lie and why delays happen, so they can resolve issues much more quickly and securely.

Process intelligence technologies offer a deep understanding and real-time monitoring of processes.

But it’s not only useful for directly customer-facing interactions. Take anti-money laundering and anti-fraud compliance efforts. At a time when fraud is more prevalent than ever, nailing the processes that catch odd customer behaviour patterns in your data, and being able to action them automatically, means customers’ accounts are safer and more secure, even with less staff in the office and more fraudsters in the system.

Looking ahead 

A clear understanding of your business’ processes will identify inefficiencies that may be impacting the customer experience – that you would never have known about otherwise. Empowering your staff with the tools to analyse less-structured processes, identify opportunities for improvement, and increase both the speed and accuracy of executing said processes, will reap many rewards.

Not only will it ensure businesses are getting the most out of their huge investment in digital transformation – it will also ensure customers are getting the best possible service. Right now, there’s nothing more vital than that.

Creating a balanced and even workflow will optimise productivity for robots – in the same way as it will for human workers.

Surely robots don’t get tired, can work 24/7, are fully skilled at what they are programmed to do, and don’t have any pesky motivational issues – so their productivity must always be consistently high? Absolutely not. This is according to Neil Bentley, Non-Executive Director & Co-Founder of ActiveOps, a leading provider of digital operations management solutions.

To believe this would be to forget everything we have learned about Lean Workflow and the way production systems work. For a processor (robot or human) productivity is best measured as a ratio of output:input. How much work did we get out for the amount of time we put in? For this to make sense we generally convert time into “capacity to do work” based on some idea of how much work could be done in a given time.

So, if Person A completes 75 tasks in a day and they had capacity to complete 100 then their productivity was 75%. Similarly, if Robot B completes 500 tasks in a day and had capacity to do 1,000 then their productivity would be 50%.

As we begin to increase our investment in Robotic Process Automation (RPA) and AI: the productivity of this (potentially) cheaper processing resource will matter – if not so much now then certainly when everyone is employing RPA to do similar tasks within the same services.”

But why would Robot B only do 500 tasks? They wouldn’t dawdle because they didn’t like their boss. They wouldn’t spend hours on social media, and they would surely only be allocated tasks that they were 100% capable of processing.

Maybe Robot B could only process 500 tasks because there were only 500 available to be done. Maybe the core system was running incredibly slowly that day, or there was so much network traffic that latency was affecting cycle times. Maybe someone changed a port on a firewall and the robot needed to be reset. Or there were hundreds of exceptions and the robot had to try them multiple times before rejecting them.

It is strange (isn’t it?) that if a person’s productivity is 50% we assume idleness, a propensity to waste time on social media, or a lack of skill but if it is a robot we quickly understand that it is the workflow that is the problem,” he continued.

Data-focused technologies such as Process Forensics and some digital operations management technologies or WFO technologies that seek to improve performance by URL logging or other screen monitoring techniques are totally missing the point: people’s productivity is far more influenced by the flow of work through the system than it is by their willingness to work or their skill level.

Workforce monitoring technologies seek to intimidate people into working harder, but you can’t intimidate people into having more work available to do. Equally, fluctuating demand, bottlenecks in the workflow, variations in work complexity will all drive variations in productivity – as with people, so it is with robots,” he added.

The answer is to introduce digital operations management solutions in the back office that will be the result of a blended human/RPA strategy made up of:

• Some degree of “demand smoothing” – using service level agreements to allow for carrying some work from one period to the next to even out resource requirements

• Some degree of cross-team collaboration – moving work or people between teams to balance demand and capacity.

The plain fact of the matter is that with humans and robotics increasingly working alongside one another in service operations a blended and balanced approach needs to be taken on the issue of productivity.

The Lords Select Committee recently issued a report: “AI in the UK: ready, willing and able?”. It outlines the burgeoning AI industry including the public understanding, engagement and design of AI and how the UK can become best placed to build and develop safe, secure and successful AI businesses.

Louis Halpern, Chairman of Active OMG, the British company behind the natural language conversational self-learning AI, Ami, spoke to Finance Monthly below.

AI will penetrate every sector of the economy and has tremendous potential to improve people's lives. I am pleased the report aims to set out a positive framework for the UK AI industry. However, the proposal is not enough to make the UK a leading destination to build and develop AI businesses. We embrace technology when it is safe, normal, and when it makes our lives better. If AI policy is directed at these elements we have the opportunity to make the UK a world leader.

For us at Active OMG safe means personal privacy. Consumers need to know their data is safe. We have to avoid the AI industry being tainted with Facebook Cambridge Analytica type scandals.

We use personal data so our clients’ customers have a better experience. When we apply the machine learning part of what we do the data is anonymised. We do not know if they are Mr or Mrs Jones, Chen or Blackwell. We are not concerned with the details of individuals. There is complete separation of personal and anonymised data.

Overcoming fear needs education, not reaction to “scandal’. The government should be educating individuals on how their data is going to be used and kept safe by the current legislation. We suggest a government information campaign, like the drink driving or Aids campaigns of the past. By explaining the data issue to people it will proactively help normalise AI.

The report talks about investing in Phd programs and cultivating AI companies directly from academic research. Yes, but we need to start programs in schools now to teach children how to use AI as a tool to thrive in a world where AI is normal. In the Pan Canada AI strategy they argued that AI should be taught alongside degrees, e.g. Sociology with AI. To become a leading AI nation, Britain must adopt a similar stance and ensure AI is intrinsic and everywhere.

Economies thrive on entrepreneurship. Entrepreneurs will develop the AI that will change our lives, like the iPhone and the personal computer. These devices cut across every industry and benefit every consumer. Government needs to follow the same model. The report talks about specific Government departments and initiatives; these will stifle, not accelerate. Every Government department needs to set an example by making policy that puts AI at the heart of what they do. No western country has been this brave.

When electricity became available it’s light quickly illuminated everything. To be a world leader, the UK needs to ensure AI’s light shines in every corner.

“In the future, robots will be doing our jobs for us” is one of the most common sentences we hear from futurists, business people and technology leaders. Below Richard Acreman, Partner at WM Reply, discusses the overvalue of automated processes and the future of ‘robots’ on the front lines of business.

There are variations on the theme depending on your perspective, like “robots are stealing our jobs” or, at the other end of the spectrum, “robots will create a revolution in creative freedom.” But while all of these predictions will probably have a strong element of truth to them over the long term, they’re also the source of a dangerous misconception in the here and now: that businesses don’t need to worry so much about talent.

Broadly speaking, the exact opposite is true, but if it’s a misconception you share, you have some prestigious company. A major piece of opinion research recently revealed the difference between the value of human capital vs. physical capital to the economy now and in the future. As part the study, two thirds of CEOs and top leaders at global firms revealed that they believed technology would create greater value for their organisations than their workforces would. Almost half believed that automation, AI and robotics would make their workforce “largely irrelevant” in the near future.

In fact, the economic modelling that accompanied the research showed that human capital would be worth more than twice as much. The key distinction is having the right skills and the right people, who are valuable both in their own right, and as the people who are going to enable the technology to enhance their organisations’ value. That means engaging with, supporting and learning from the best workers to ensure that their knowledge and expertise remains within the business and can continue to unlock the business’s potential as the workplace changes.

A key battleground

Unsurprisingly, the first place that this issue is flaring up is on the front lines of business – among the customer facing or service delivering staff that form the grass roots of most organisations. It’s this audience who are often the most threatened by automation and it’s also this audience who are traditionally most neglected by their companies.

Zagg customers can register online products through ZAGG Register

As the above study shows, it’s all too easy for businesses who have never been particularly strong on engaging their front line workers to take technology as an excuse for inaction or to make the situation even worse, but overestimating the scale of the change or the speed of the transition means that those with this attitude will likely have years to regret their miscalculation before anything close to the future they’d imagined comes to pass.

Why front line workers continue to be so important

Looking at it from both sides helps to clarify how misleading it can be to think that technology is going to make staff less relevant.

If we assume that technologies that are good enough to fully replace staff are here already, or very close, then we might also make the assessment that the best staff will be needed to help inform the processes and approaches of that technology, look after it, and stand in for it when it goes wrong. Not to mention the cases where it doesn’t have the answer, or is dealing with a customer who insists on human interaction.

If we assume that the technology isn’t here yet, but is coming, then this group will remain essential to the work, but exist in a heightened state of anxiety about their future with automation seemingly in hot pursuit of them. They will therefore need not just a decent level of support and attention from the business (as should be standard), but also a certain amount or additional reassurance, the absence of which might well be seen as their death knell.

People and technology in perfect harmony

What then is the short-term answer? And how can companies ensure that they are not only engaging with, but also getting the most out of their front line workers, so that the technology will have to work even harder to offer a quantifiable advantage?

That’s probably something that’s best explained with some specifics. Bea Tartsanyi, enterprise innovation strategist at Sideways 6, talking at a recent event focused around Microsoft’s Yammer, pointed out that the value of grassroots innovation to a business is immense. With the analytics that her team is developing, they’re starting to get a handle on just how important that is. She’s proving that using tools like Yammer to access the knowledge and learnings of those on the front lines – those who ordinarily might not have much of a voice internally – is not only one of the most effective, but also cost efficient ways of driving innovation.

Bea also pointed out that companies are always looking at ways to bring the voice of the customer firmly into the business. To learn from the customer’s needs and to understand the best practice approaches to meeting them. What better way to do that than to directly connect front line workers to the centralised organisation through the engaging, non-hierarchical social tools like Yammer.

It works both ways: Front line workers can easily flag some of the everyday challenges they face for senior managers to tackle, while those at the top can offer up the challenges they face. Whether those challenges come from a loyalty, cost or another perspective entirely, allowing those at the coalface to share their experience of overcoming those challenges on an individual case basis will feed into an organisation-wide benefit.

Ultimately, automation will have an important role to play, but we’re a long way from that role superseding the role of front line workers. Giving those on the ground the tools to excel at their own jobs while also feeding into the wider strategy is an immediate answer to many of the challenges that companies face. Given how much front line workers – properly enabled – can contribute, ignoring the people-based solutions to those challenges in favour of the vague idea that up and coming technologies will fill in the gap is like saying you won’t buy an umbrella because at some point in the future it might not be raining.