The ability of CFOs to leverage digital and intelligent technologies to position their finance function as the catalyst to drive data-driven insights and identify strategic opportunities, will determine the future of their organisations.
Shift to building smarter bots
The first wave of a financial digital core was led by the adoption of Robotic Process Automation (RPA). The RPA ability to automate repetitive rules-based processes, to open email attachments, complete e-forms, and initiate workflows, record, re-key data, make calculations, generate reports and work around the clock was revolutionary. The benefits of automation are obvious in cost reduction, lower error rates, improved service, turnaround time reduction and increased scalability of operations, with improved controls and compliance.
However, RPA has its limitations. Bots are able to follow logical rules-based processes – but unable to see patterns, understand the logic behind the data or extract meaning from images, text or speech.
Since late 2019, organisations have been seeking to scale these solutions by integrating intelligent and cognitive AI capabilities such as speech recognition, natural language processing (NLP) and machine learning (ML) to automate perceptual- and judgement-based tasks and predictions that were once reserved for humans.
This has shifted the paradigm, extending automation to a whole new potential. Organisations are now able to become more efficient and agile as they transform into fully dynamic digital businesses.
Benefits of intelligent cognitive automation
Machine learning, autonomics, machine vision, NLP and deep learning offer the ability to extract meaning from images, text or speech, detect patterns and anomalies, predictions analysis, recommendations and decisions.
A modernised financial digital core driven by RPA and intelligent cognitive capabilities has the ability to eliminate closed tasks and provide real-time analytics to support business objectives. Leading organisations are leveraging the digital core to reimagine financial processes, enhance strategic business partnership through real-time analytics to rapidly respond to business changes and M&A activities.
A recent Deloitte survey found executives of organisations currently scaling intelligent automation have already achieved an average 27 per cent reduction in costs, as compared to the expected 22 per cent, from their implementations to date.
Digital finance controllership
In digital finance controllership, a specialised combination of accounting knowledge and flexible in-memory financial applications is being used to modernise business data and logic.
Finance controllers can now transform business and finance processes, achieving higher efficiency, speed and accuracy, including by automating predictions and decisions on the basis of structured and unstructured inputs.
By combining internal financial information and operational data with external information to make sense of an increasingly complex world, financial controllers are able to generate new insights and identify hidden patterns.
Many ERP systems are faced with the challenge of automating the full end-to-end Close, Consolidate and Report process but often do not fully support the linkages within the business. This can lead to a fragmented, manual and inefficient close, as well as to inefficiencies throughout the accounting period.
In contrast, integrated systems promote a clean transactional data flow from source directly to financial systems (sub-ledgers and general ledgers), reducing the number of transaction-level variances that require manual reconciliation.
The previously fragmented and manual financial close management is being replaced with a hub-and-spoke model where applications can now work in synchronization within a single data source.
RPA software helps to pull, aggregates fragmented financial data, while the processing of the data are under the direction of more advanced intelligent and cognitive technologies. When the AI algorithm has completed processing its functions on the raw data, RPA then pushes the final output answers to the target systems.
How to start?
Embracing intelligent cognitive technology requires strategic transformational change and design thinking, but can play a key role in ensuring long-term implementation success.
As financial controllerships embark on their modernisation journey it is critical to establish a clear, long-term vision and road map that has buy-in and input from key stakeholders across the risk and finance organisations. There is a need to examine the opportunities of AI to address today’s business challenges, prioritise the opportunities, articulate how the intelligent cognitive automation will add value to the business, and align the next steps.
In summary, financial controllers have the opportunity to harness sophisticated intelligent cognitive technologies, analytical tools, and methods. The importance lies in the ability to identify quick-wins and decisions to address key pain points such as manual journal entries, data aggregation processes, manual reconciliation processes, and product control and reporting preparation processes.
This targeted automation of manual processes will help to enhance overall data quality, reduce costs, increase processing speeds, and better manage the risk of reporting errors in the near term, providing a quick turnaround in ROI. This, in turn, will pave the way to longer-term investments and strategy to incorporate more sophisticated intelligent cognitive capabilities such as machine learning, predictive analytics and AI to achieve a true transformation in digital finance controllership.
Montri Khongkruephan is a partner, and Joeyvoen Teo a senior manager, of audit & assurance at Deloitte Thailand.
Published : January 28, 2021
By : Montri Khongkruephan, Joeyvoen Teo Special to The Nation