Home Finance Operational Efficiency – New Ways to Solve an Old Problem

Operational Efficiency – New Ways to Solve an Old Problem

by internationalbanker

By Fiona McNeill, Financial Services Product Marketing Manager, Red Hat 

The term “operational efficiency” is not new, and in fact, applies to many industries because it works toward a common goal: to optimize operations so they provide greater returns – whether they be faster time to market, greater volume and/or increased revenue – relative to inputs. While it may seem counterintuitive, it can be more operationally efficient to increase costs, as long as returns outweigh the investment. 

In financial services in particular, there has been a renewed sense of urgency to focus on operational efficiency, which may be attributed, at least in part, to global economic uncertainty. In fact, Forrester VP and Research Director Analyst Benjamin Ensor predicts that (Predictions 2019: Financial Services Firms Shift Their Focus To Operational Efficiency, Forrester blog post, November 2018) “.. firms will shift their focus to reducing the cost to serve customers through greater operational efficiency.” 

With digitally savvy customers, heritage bank servicing models can be painfully visible. Even for digital banking newcomers, expectations have been set by the ecommerce channels they already use. The digital storefront to connect to bank services isn’t enough. Customer journeys traverse beyond the interactive interfaces to transact – which is requiring banks to reassess branch-defined processes, removing requirements that no longer apply to digital-first customer journeys. And while technology is only one of the three elements of the business trinity – of people, process, and technology – both organizational culture and business processes can be aided with modern technology adoption. Read on to learn more. 

Shift power to the customer

Automation requires digital data be captured before it can be processed, without manual intervention. However, there are some banking practices, like settling transaction disputes, where specific information is needed to identify what the issue is and how it impacts the customer. But rather than call center or branch staff spending time recording the issue, digital customers can stay in their preferred channel – entering the information themselves, and with the side-benefit of reducing transcription errors. 

By shifting the entry to the customer, resolutions can be concluded without any staff involvement. Will this work for all disputes, claims, requests, or inquiries? Likely not. But will it work to reduce many activities that staff do today, freeing them to pursue higher value activity? Likely yes. Inquiries that fall within such prescribed online interactions can be automated using decision rules. For those that don’t, additional triage can be applied to automatically process the inquiry given the required data is already in electronic format, easing issue analysis burdens, and even determining the most economical and appropriate process to resolve the inquiry. 

The ability to collect information at scale from digital interactions to power insights requires decision rules that are fully integrated with process automation technology, so that any algorithm, along with any data (like customer segment), can be defined in any combination – simplifying servicing actions across the widest range of use cases. 

Adopt mutable compute

Pools of resources like processing power, storage, and applications are available on-demand across a network when they live in a cloud. When such resources are made available in containers, it is easier to control and manage when and to whom they are made available. This means that security vulnerabilities and points of failure can more easily be controlled, which can be key to having highly available mission critical systems, like payments.  Cloud containers for specialized processing tasks, like high performance risk calculations, or Graphics Processing Units (GPUs) for large scale machine learning tasks, and even the tools for defining automation of processes themselves, can be made available on-demand. Such self-service portals help accelerate time to results, often eliminating the need for ad hoc requests to IT for specialized hardware and providing faster response times for customers.       

With restrictions on compute lifted, instantaneous speeds can become a reality, like with real-time payments or any other type of live data operational process. By running two systems in parallel (i.e. blue/green deployments), financial services firms can add new features to live systems – assessing adoption and adjusting as needed, ultimately achieving the nimbleness and innovation speeds previously available to only tech companies. Given regulatory changes will continue, new advancements in computing power will happen, and cloud providers will fall in favor, firms that look to open cloud container platforms will be better able to quickly adapt to whatever change will come next.   

Streamline with embedded insight

Whether real-time or intermittent, traditional statistical models or specialized AI methods – or anything in between – including insight creation as part of processing rather than an adjunct exercise creates new data to make more informed decisions. This is particularly advantageous when business processes are automated – with different decision rules defined to take specific actions based on calculated probabilities.     

Algorithms require data, and with operational activities, like requests to replace credit cards, for example, firms need to consider new and updated data to understand the current customer profile and the potential of the request being fraudulent. Being able to verify digital customers and changes made to their accounts requires full traceability of decisions – not only for audit purposes, but ultimately for retaining customer trust. As such, the algorithms used, decision rules applied, and automated processing done is best developed in fully traceable, open systems. Moreover, organizations that base embedded insight calculations on a standardized open platform not only have the necessary visibility to all aspects of automated actions, but also benefit from portable code (and the data that goes along with it), that can be reused in different business servicing systems. 

The revival of back office operations to drive net new returns is achieved not by one of these activities – but by all of them, done in conjunction with one another. Modernizing technology adoption for bank operations can help financial services organizations meet expectations of digital customers and generate greater returns from higher throughput, less downtime and in most instances, reduced costs. The type of standardization that an enterprise open platform provides, permits best of breed tools, compute power, and methods while lifting burdens from staff – giving them transferable skills to continue to bring new efficiencies to other parts of the organization.


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