The bots are coming: Intelligent automation and the modern corporate treasury department

Transcription

1 The bots are coming: Intelligent and the modern corporate treasury department KPMG s Corporate Treasury Management Practice kpmg.com $

2 A barrage of terms Robotic Process Automation Bots Artificial intelligence Machine learning Natural language processing

3 These terms and many others are becoming part of the daily vernacular of futurists and trend predictors, often with the implication that these technologies may eventually replace some aspects of the current human workforce. We prefer the view that, rather than signaling the rise of a digital workforce, these terms represent a cross-section of the many innovative applications available under the broad umbrella of intelligent (IA). These rapidly expanding technologies both complement and augment human skills and boast the power to exponentially increase the speed, scale, quality, precision, and operational efficiency at which enterprises operate. Modern manufacturing facilities commonly employ legions of robots to incorporate subassemblies into final, fully functioning products, but these noncognitive machines still require humans to provide monitoring, oversight and quality control. Clearly, the introduction and expansion of technologies has had an impact on manufacturing organizations. What about businesses with less tangible products and services such as finance and treasury organizations? The intermediate effects on these enterprises are less clear. This whitepaper explores this evolving dynamic. In it we provide a brief overview of the current intelligent landscape, supported by observations and examples that illustrate how these emerging technologies can enhance your current and future treasury operating model. These rapidly expanding technologies both complement and augment human skills and boast the power to exponentially increase the speed, scale, quality, precision, and operational efficiency at which enterprises operate. Intelligent generally falls into three high-level categories: Basic Process Automation (RPA) Entry-level processes that are repetitive, rule-based and transactional in nature (e.g., bank reconciliations) Enhanced Automation Interpretation of unstructured data supporting selflearning and limited decision making through natural language processing (e.g., cash and cash flow forecasting) Cognitive Automation Self-learning and Adaptive technologies that are taught, rather than programmed, and designed to identify trends and make humanlike decisions within wide parameters (e.g., cash positioning and investments) IA and corporate treasury management 1

4 ACT like a human RULES LEARN REASON Basic process Macro-based applets Screen-level and OCR data collection Workflow Process mapping Self-executing Enhanced Built-in knowledge repository Learning capabilities Ability to work with unstructured data Pattern recognition Reading source data manuals Natural language processing Cognitive Artificial intelligence Natural language recognition and processing Self-learning (sometimes selfoptimizing) Processing of super data sets Predictive analytics/ hypothesis generation Evidence-based learning THINK like a human The spectrum of technologies range from basic to intelligent The development and implementation of these methods of within the treasury environment are currently works in progress. Through KPMG s ongoing discussions and engagements with global treasury organizations, we ve identified a mix of internally created applications and third-party programs currently in development. Examples include automated daily cash posting, bank reconciliation, intercompany netting and purchase orders (three-way matching). 2 IA and corporate treasury management

5 Practical applications/limits Despite their relatively wide usage across financial services, bots certainly do not render human oversight and intervention unnecessary. Program trading, common on all major stock exchanges, is a good digital example. These quantitative bots are primarily designed to ensure that all trades clear while employing curbs that provide oversight to minimize market disruptions. While bots process buy and sell orders continuously, they still rely on human intervention to establish trading limits and write or modify algorithms as market conditions change. Without human oversight, the risk of loss would be magnified in a downward-trending market cycle because the automated program would continue to repeat the process based upon stale data. Given the importance of cash and the ever-prevalent risk of cash-related fraud, employing intelligent to manage cash-related transactions, such as positioning, transfers and investments, will continue to require enhanced human oversight. Treasurers must strike a balance between utilizing these rapidly developing, but still imperfect, technologies and the development and implementation of enhanced internal controls. Treasurer s challenges This environment poses significant challenges for corporate treasurers. The mandate is typically a combination of reducing operating costs, improving process and increasing efficiencies all while navigating corporate strategy and accounting, tax and regulatory changes. As an integral partner in a company s financial chain, treasury must also maintain adequate liquidity, minimize risk and support operational growth. Like the earlier manufacturing example, treasury controls and executes a series of subprocesses not all of which can be fully automated. In other instances, tools can only be partially deployed. In these scenarios treasurers must identify the most efficient combination of basic and more advanced options to reduce errors, improve compliance and enable faster decision making. Following are two examples in which KPMG supported the introduction of digital. EXAMPLE 1: Cash management and investments Forecasting a company s shortterm liquidity needs is a critical treasury function, but it is often a manual process with varying degrees of accuracy. More and more, leading organizations are using basic RPA and cognitive solutions to achieve more precise and timely forecasts. Basic Process Automation bots are employed to extract data from the Treasury Management System and/or Enterprise Resource Planning systems into predefined templates. This automated process significantly enhances the historically manual nature of forecast creation and verification, as well as variance analysis. One client, a global autoparts supplier, implemented these processes and improved its short-term liquidity forecast accuracy to 97-percent. In this case, the digital application extracted monthly up to 3.6 million records from underlying source systems (i.e., accounts payable, accounts receivable, payroll and the intercompany netting center). Going a step further, the company incorporated a Cognitive Automation option that enabled the bot to forecast customer payment patterns based on previous trends. These solutions facilitated efficiencies that enabled some staff to transition from clerical to more value-added analytical tasks, while reducing external interest expense through the redeployment of cash balances. IA and corporate treasury management 3

6 EXAMPLE 2: Financial risk management As we work with clients to help optimize their workflows, we ve observed that many have difficulties collecting foreign exchange-related cash flow and balance sheet exposure data. Similarly, the need for timely and accurate processing of data limits the ability of many global organizations to reduce FX risk effectively. For example, updates to balance sheet hedge positions generally occur after the accounting period is closed and in some cases several weeks after month-end. This timing can create a mismatch between the exposure and the hedge rate and often results in lower hedge coverage percentages. Treasury organizations that can access timely quality data are generally more efficient in reducing FX risk. Another client, a technology provider, introduced bots to mine data in near-real-time to gather and manage its exposures. The ability of these bots to extract sales data, changes in accounts receivable and accounts payable, and inventory balance data to develop and recommend daily trade plans created a valuable competitive advantage. We work with many organizations that actively manage both balance sheet and cash flow forecasting daily. Access to this refined data enables the company to fully hedge balance sheet exposure in a timely manner and adjust cash flow in response to changes in daily sales reports versus forecasts. In these cases, treasury can improve hedging programs and increase the predictability of its results as the translational and transactional swings are minimized. How KPMG can help deploy robotics in your treasury department As the global capital markets evolve and gain in complexity, our core treasury service offerings continue to expand particularly in the area of digital. A high-level overview of our -related services and the potential benefits appear below: Service Offering Governance Organization Cash management Risk management Analytics Offering Description Review treasury policies, processes and control structures Assess current Treasury operating model roles / responsibilities Target improvements in liquidity and cash flow forecasting Develop hedging strategies that align with company s risk appetite Focus on bank fee rationalization and review of historical models and trends Primary Application* Machine learning Basic process Cognitive Cognitive Enhanced process Potential Benefits Reduced fraud risk Improved cost structure Increased interest income/ reducing interest expense Improved P&L predictability Development of analytical associates * These are likely not the only applications relevant for these service offerings. As Treasury needs evolve, the solutions employed to help automate them are likely to expand and overlap. 4 IA and corporate treasury management

7 In conclusion $ The bots are not coming they re already here. With so much unstructured data out there, businesses can work smarter, rather than harder, by embracing, understanding and implementing intelligent technologies across the enterprise, from front office to back. We believe if we can teach machines to do repetitive, routine tasks that currently tie up and exhaust human workers, there would be more time for them to prioritize issues, address deficiencies, connect with stakeholders, think and innovate things that increase people s satisfaction with their work. At KPMG, we ve made significant investments in intelligent and are experienced leaders using progressive approaches to digitally transform our own organization to lower costs, improve quality, mitigate risks and enable our professionals to deliver higher value to clients and do more rewarding work. We can help your treasury organization expand its role as a creator and protector of shareholder value. IA and corporate treasury management 5

8 Contact us Julie Luecht Principal, Advisory Thomas Schwarb Director, Advisory Kwab Gyasi-Twum Manager, Advisory Liz Holland Manager, Advisory Andrew Hay Director, Advisory KPMG Board Leadership Center Russell Hoffman Director, Advisory Peter Lallos Manager, Advisory Some or all of the services described herein may not be permissible for KPMG audit clients and their affiliates or related entities KPMG LLP, a Delaware limited liability partnership and the U.S. member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative( KPMG International ), a Swiss entity. All rights reserved. Printed in the U.S.A. The KPMG name and logo are registered trademarks or trademarks of KPMG International. The information contained herein is of a general nature and is not intended to address the circumstances of any particular individual or entity. Although we endeavor to provide accurate and timely information, there can be no guarantee that such information is accurate as of the date it is received or that it will continue to be accurate in the future. No one should act upon such information without appropriate professional advice after a thorough examination of the particular situation. kpmg.com/socialmedia