FinTechAutomationRobotic process automation in finance

Robotic process automation in finance

Robotic process automation (RPA) is attracting widespread attention in the business world, evoking both excitement and apprehension. This article examines the development of RPA and the many areas in which it is now being applied.

Robotic process automation (RPA) has in practice been a feature of treasury and finance system solutions for some time. RPA allows users to configure software, or a “robot”, to automate transaction management, data manipulation, or communications with multiple systems. It is ideal for relieving employees of manual tasks involving high volumes, and in highly transactional processes which occur particularly in areas of finance such as the order-to-cash (O2C) or purchase-to-pay (P2P) cycles, or in record-to-report (R2R) activities. Many companies worldwide have benefited from automated processes thanks to robotic software; it just hasn’t been called RPA until recently.

RPA today

So, how has RPA become such a popular term today – and does it still mean the same as the automation advances of past years?

Today’s focus on RPA can be explained by the fact that it has now entered the consciousness of the broad population of companies, process owners and finance organisations. Its characteristics – and its significant inbuilt benefits and risks – are now discussed and analysed in the general business domain, not just in the specialist IT community. Changing realities demand new approaches as digital transformation enters all areas of life and business, with ever-greater mobility, big data, cloud applications, hyper connectivity and much more.

Customer behaviour changes as a consequence and consumers expect faster processes every day; which has a lasting effect on businesses worldwide. The increasing interest in RPA also has much to do with timing. ‘Business intelligence’ (BI), for example, was a hyped term 20 years ago, but it is only today that the technology is able to analyse big data in such a way that BI can truly fulfill its promises – namely to deliver deep insights into business processes and to generate comprehensive key figures and benchmarks for optimising operations.

In the past, RPA has become an increasingly hot topic amongst corporates, consultants, industry analysts and solution vendors. This change is illustrated in the breadth of recently published RPA material from diverse sources. They include Deloitte’s report ‘The robots are coming’; KPMG’s ‘Robotic Revolution – separating hype from reality’, taken from the 2015 Global Sourcing Advisory Pulse Survey, Shantanu Ghosh’s recent piece for; Erik Brynjolfsson & Andrew McAfee’s 2014 book ‘The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies’; and Gartner’s May 2015 study on working with smart machines. This shift has also become evident in the upsurge of Google searches for RPA, which has seen an exponential rise over the past year.

RPA is much more than a hyped technological buzzword; it is now an essential feature of the treasury and finance technology landscape.

As presently realised in today’s financial applications, RPA provides powerful end-to-end solutions for a range of business issues, which are generically characterised by repetitive, rules-based processes, operating on medium- to high volumes of data. RPA eliminates or minimises the need for human intervention in what are generally routine mechanical workflows; often requiring 24x7x365 operations. Manual and error-prone processes are reduced to a minimum with RPA.

RPA, however, has evolved from such basic process automation and is maturing to enhanced and even cognitive automation. It is thus impacting and changing the behaviour of today’s process owners and decision makers. Accordingly, it is making new competitive demands on software solution providers, designers, managers, sales teams and implementers.

RPA catalyses constant change through the new requirements and opportunities becoming available via digitalisation, new technologies and the need for the intelligent and efficient management of financial data and processes. Emerging technology now enables machine learning and artificial intelligence (AI) in RPA, which can bring a range of benefits to corporate finance operations, treasuries, in-house banks (IHBs) and shared service centres (SSCs). These include improved throughput, control, transparency and accuracy, and these gains are available at low cost due to RPA’s intrinsic efficiency.

Human errors are minimised, or even eliminated and the finance team can be re-deployed to higher value activities and more rewarding duties, such as focusing on exception handling. RPA can therefore substantially reduce operational risk, and additionally cut down the chances of financial losses being incurred; for example through missing payment release deadlines, late financial closing, or acting on incorrect or incomplete information.

The competitive impact of RPA

For businesses to stay successful and maintain their edge over competitors, they need to be versatile and early adopters of new technology. It is vital that companies keep up and even drive continuous technological change for them to succeed.

Maintaining constant awareness of the potential value of change is essential. An organisation which isn’t seeking sustained improvements to its products and services, its business processes and its technical infrastructure will find itself outmaneuvered by nimbler, more alert competitors. This approach is by no means new; it was first articulated by management science pioneer Peter Drucker in the 1940s and retains its validity today. Corporate history is littered with the remains of organisations and groupings which did not adapt and embrace the correct set of innovations, approaches and technologies. Examples of industries to have recently become casualties include traditional travel agencies, photographical imaging companies, retail trade and airlines.

RPA is presently challenging corporations’ approaches to process management. Those which understand and embrace the opportunities now available are better positioned to thrive through the resultant efficiency gains. These range through increased cost efficiency, better central overview, more reliable data, increased visibility and higher revenue.

RPA enables corporations to focus on their core business, and to perform with highly competitive agility and efficiency. Innovation will be hindered if it is supported by inflexible, obsolescent technology and process management; constructive RPA is based on standardised and harmonised processes, taking decisions based on accurate and up-to-date information management and on increasing levels of machine-based intelligence. RPA is now an essential business tool, and its beneficial impact is seen in its growing involvement in driving process improvements in diverse areas such as IT, human resources (HR), management reporting – and finance.

RPA in finance applications

As RPA matures, its effects on efficiency, agility and optimised outcomes are found in a broadening range of financial business processes.

RPA in the cash application: Today’s best performing corporate cash application and receivables management tools are highly automated, as they assemble, validate and organise the complex data management tasks required to measure and mobilise a corporation’s global or regional cash resources most effectively. The component processes include:

  • Daily and intra-day bank balance and transaction statement retrieval, often involving multiple banking communications and messaging technologies.
  • Transforming the statements into the current cash position through reconciliation and optimised exception handling.

Treasuries and finance operations supported by RPA solutions are best placed to make accurate decisions, optimising liquidity and interest management performance. The automation of the mechanical, rules-based processes which comprise much of cash management is a classic example of a value-adding use of RPA.

RPA support for financial closings: Cyclical closings have historically required labour intensive operations, typically involving exacting deadlines to generate a full set of accounting results which can be confidently submitted to finance management. RPA solutions facilitate quicker, more dependable monthly, quarterly and annual closings; effectively manipulating the high volumes of data required for each process.

RPA for management reporting: This is another cyclical task demanding speed and precision. This makes it a most suitable subject for an RPA solution, which will reduce the related efforts and costs.  RPA reporting solutions can assemble, analyse and organise the vast amounts of data that are often involved, and work around the clock (without problems or incremental costs) to produce the required levels of quality and timeliness.

RPA for accounts payable processing: Invoice management, reporting capabilities, reconciliation activities and the more complex process of managing the payment of invoices in the most optimised way are just a few of the areas in accounts payable (AP) processing that lend themselves to RPA.

An important strategic priority in global finance

World class corporates have embraced RPA, accepting that this technology is now central to the consistent achievement of competitive results, yielding the required high levels of financial business processes efficiency, transparency and control. This is reflected in the frequent appearance of the topic on the agendas of leading professional conferences, for example for SSCs.

RPA’s core function is to minimise or eliminate unproductive human interventions, by operating a robust, rapid and secure end-to-end workflow; ensuring that high levels of quality and control are consistently, measurably and objectively achieved. It is increasingly difficult – and will soon become practically impossible – to achieve performance standards which are at a minimum acceptable to customers, shareholders, regulators and senior management without the support of RPA.

RPA takes advantage of the high performance communications and computational facilities and coordinates multiple tools to interconnect, retrieve, analyse and report processes and data. These are features of recently unimaginable degrees of power and flexibility. They amplify the professional risks to corporates of falling significantly behind their industry peer group – and also the truly exciting obverse, the new opportunities for achieving excellence in efficiency, agility and quantifiable quality.

Evolving from basic robotic automation, RPA today increasingly stands for the next evolutionary phase: enhanced robotic automation, which is capable of automating more complex processes than before, and also to integrate unstructured information. This is paving the way for ultimately achieving cognitive automation through self-learning and AI.

The contemporary digital revolution has increased the stakes – and consequently the rewards – that are now available.  Today, it is feasible to apply automated intelligence to all kinds of financial data, providing a basis for superior financial decision taking and best practice process management.

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