In case you haven’t come across the term before, “operational efficiency” is exactly what it sounds like - optimising processes within the operation of a business in order to gain the greatest result for the smallest input of expense and effort. Depending on the business, that could take the form of decreasing the time to market, increasing volume or increasing revenue. There is a major distinction between operational efficiency and other measures commonly taken to streamline a business. For example, it is not the same as cost-cutting. Indeed, you might actually find costs increasing in order to obtain optimum returns.
In the case of financial services, the pursuit of operational efficiency has taken on a degree of urgency, to some extent because of uncertainty in the global economy. Forrester VP and Research Director Analyst Benjamin Ensor included some expectation of a push towards greater operational efficiency among financial services in his predictions for 2019, citing the need to reduce costs while still effectively serving customers. Given an increased reliance on digital banking and eCommerce, especially in response to self-isolation measures enacted to combat COVID-19, the need for increased speed and reduced cost in operations is only going to increase in 2020.
Fortunately, there is fintech. As customer expectations of what can be achieved online increase (particularly in the wake of COVID-19), technology is the one element of the business trinity - consisting of people, processes and technology - that can improve the efficiency of the other two, speeding up processes and reducing the reliance of person-to-person interactions.
Outsourcing data entry
One of the bigger hindrances to operational efficiency in financial services is the need for data to be captured and inputted. Due to the complexity of that data, this has historically resulted in the need for large in-branch staffing and call centres. However, each individual staff member can only handle one customer at a time and, depending on the issue or transaction dispute being processed, it could take as little as a few minutes or as long as a number of hours to handle a single customer. Given the notoriously long queues at branches and even on phone lines for call centres, it’s evident that this is not the optimum approach.
The solution is perhaps a little counterintuitive, but is surprisingly effective - outsource the data entry to the customer. A customer that wants to handle their banking online will generally want to stick with an online approach throughout their interaction. If you stick the need to go into a branch or phone a customer service helpline in the process, it mostly just serves to annoy them. They will be far less annoyed punching numbers into your system and it also removes the risk of human error since the onus is on the customer to get their input right. A technological solution will achieve the same result as the human interaction would have done, but quicker and cheaper.
Naturally, this won’t work for absolutely every customer interaction. There will inevitably be those who prefer talking through the problem with a person, don’t want to enter all the data themselves or who have circumstances that don’t fit into models you can plan and prepare for. However, the overwhelming majority of customers will be able to deal with their issues online, freeing staff and resources from low-impact, low-value minutiae so that they can handle higher priority activities. As a bonus, the information gathered from customer interactions can be compiled and analysed to provide useful insights into their needs and behaviour - assuming that the data is not too sensitive and private, of course. Those insights can then be used to further refine the processes and further improve operational efficiency.
Get your head in the cloud
The rapid development and improvement in cloud computing has opened a lot of doors for financial services, even if costs, security concerns and regulations have occasionally prevented companies from walking through them. However, the trend towards adopting cloud storage and processes will inevitably remove many of those obstacles.
Particularly applicable to financial services is the concept of having a single store of sensitive customer data and essential systems, rather than having duplicates of both in every branch. Put simply, the fewer copies there are, the fewer potential security vulnerabilities and points of failure there are. Additionally, running specialised processing tasks like high performance risk calculations or even defining the automation of process through cloud containers can make the necessary tools more widely available. That will reduce the time it takes to get results and will generally remove the need for repeated ad hoc requests to IT departments for those tools, all of which contributes to getting results to customers quicker.
As security measures surrounding cloud systems become more sophisticated and effective and as those systems are further developed to meet company and customer needs, it is highly likely that regulations will also adapt. Companies that invest in fintech early will therefore be in a better position to exploit the easing of regulations more rapidly, giving them a significant edge over their competitors.
Data makes the difference
One of the security concerns raised by increasing automation in financial services is the fact that a computer cannot spot a fraudulent transaction. Or can they? Yes, a human operator would maybe think it a bit odd if a customer in Thailand suddenly requests a new credit card be posted to the Philippines or something equally out of character, but when they are dealing with hundreds of customers per week and have targets to hit, the risk of them accepting some weak excuse given by a fraudster may perhaps be raised. They won’t know each of their customers personally - it is simply impossible for the human brain to maintain that number of personal relationships - so they won’t know if this behaviour is out of character or entirely understandable.
By contrast, a well-programmed algorithm with plenty of data to work from has no such human limitation. It can draw from experience in the form of behaviour patterns individual customers and even customer profiles have exhibited in the past and can instantaneously flag suspicious behaviour, blocking potentially fraudulent actions until they can be verified, perhaps by human staff or perhaps even with another automated process like two-factor authentication.
In order to increase operational efficiency, more of this data must be gathered, ideally with minimal disruption to customers and processes. Exactly what form this takes depends on the business and the process - there is no one-size-fits-all answer. It could be gathered in real time or intermittently, using statistical models or specialised AIs or any of dozens of other approaches. All that matters is that data is gathered and processed. Without it, operational efficiency will be stunted.
Any business that handles money in large quantities must inevitably accept a certain amount of risk, managing it as well as possible to minimise potential losses. In the world of financial services, perhaps more than any other, the goalposts are rapidly moving and changing, meaning that new risk assessments need to be made regularly and rapidly. Unsurprisingly, a technological solution will have a huge impact in minimising costs, improving operational efficiency.
Take the example of capital markets: market conditions are constantly changing, yet regulatory requirements limit the speed at which a company can react. Risk calculations that require huge amounts of data take time to conclude and the results may be completely defunct by the time they are available.
Some firms have already started using predictive algorithms and AIs to gain an edge. Bridgewater Associates is perhaps the most famous example, replacing their hedge fund managers with carefully crafted computer programsto obtain the optimum results. Not only can such AIs study vast quantities of data from multiple sources in seconds, but the solutions they come up with are clinically dispassionate, devoid of human emotion and instinct. While they cannot remove risk entirely because financial markets are still able to throw up the occasional curveball, they have consistently achieved reliable results.
Respect the trinity
As stated earlier, there are three elements to the business trinity. While technology is certainly the one in which financial services have the greatest growth opportunities, people and processes should not be overlooked. Instead, a balanced approach will be more likely to achieve the desired operational efficiency.
Involving staff in the changes that directly impact them creates a sense of ownership in the initiatives being enacted, making people feel that their capabilities are being enhanced by technological innovation, rather than replaced. Personnel should also be a factor to consider when implementing new technology. How can it improve staff efficiency and productivity? Is the technology going to improve their workflow or just create more distractions that slow them down? What training and supervision will be required to make sure new technology is used effectively?
Processes, too, must be considered. Some business lines may need to be adapted in order to cut out wasted time and effort while others may need to be dropped entirely if they no longer serve the overall goal.
It’s important to note that improving an organisations operational efficiency is a process that must be approached with considerable care and thought. Throwing money at fintech firms and hoping for the best will inevitably result in efficiency dropping, not improving. Leaders should designate a task group or committee of senior staff to discuss the challenges they face and solutions that could help. There are also external resources they can use - examples they can follow from other organisations. Above all, the results aimed for an achieved must serve the strategic goal. Otherwise, the efficiency gained is really not operational.
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