Finance News

Cash Management – Changes, Challenges and Opportunities

Cash and Liquidity Management have been around since the beginning of trade and business, making sure that cash is optimally utilized and is at the right place at the right time. Over time, ways to optimize receipts and working capital have evolved so that businesses enjoy maximum float while simultaneously maximizing returns. It is integral for a banking business, for corporates, and an important line of business for banks in the corporate banking space.

Cash Management is especially critical for organizations operating across multiple geographies or multiple lines of business. What’s more, a corporate or SME business typically has multiple banking relationships, with close to 100 or more accounts across those relationships. With one physical bank account for all the payments and collections, tracking and reconciliation of payments, collections, account receivables and account payables becomes a mounting challenge. According to a 2017 CGI Transaction Banking survey, about 21% businesses globally bank with more than 20 banks on an average, while more than 30% have at least 2 to 5 banking relationships.

It is critical for corporates to ensure that the accounts are funded optimally, overdraft positions are covered, interest is optimized at all times, and ensure that they have a holistic view of their liquidity positions across banking relationships. Businesses need to manage the “Cash in the business” at the “Balance Point” or at least within the “Optimal Zone” as required.

Many corporates and SMEs look to their banks for efficient cash and liquidity management. Banks need to keep abreast of the developments in the space and the demands of new-age corporate and SME businesses to provide innovative digital solutions. In the next few paragraphs we look at some of the key factors impacting cash management, and how digital technologies can help transform the space:

Payment innovations: Several countries have adopted faster means of payments and this is changing the way the world functions. Cross-border payments too can’t lag behind for long and it is this realization that has led to multiple changes in this space. Banks are working to leverage new innovations like SWIFT gpi which, with its end to end tracking, faster settlements, and stop and recall service is bringing in a long awaited and slightly delayed revolution in the cross-border payments space. With payment schemes like SCTInst in Europe, real-time payment schemes are on the rise and businesses demand a 24/7 processing and visibility.

RTP in the US is intrinsically designed to cater to corporate payments with options for messages like Request for Information on top of normal pacs.008 or such payment messages. SWIFT gpi is playing a significant role in fostering faster, near real-time credits, creating enhanced propositions for banks as well as their business customers with global operations. Corporates and banks need to be equipped to handle such changes as the turnaround-time between an invoice generated and payment made/received will reduce significantly with these advances.

Open Banking/APIs: From an era of proprietary apps, private APIs and close networks, banking is now becoming increasingly open with developments like open API, Fintech collaborations, cross-industry partnerships, regulatory changes like PSD2 etc. These developments impact all areas of banking, and corporate banking too needs to be digitally-enabled and API ready. Multi-bank cash management, which today takes hours or sometimes days to process, is set for a massive transformation with APIs and will transform the way cash management works today.

Changing corporate expectations: Corporate banking has lagged behind retail banking in the adoption of latest technology and user experience. Corporate banking users are exposed to convenient banking on mobile and other channels as retail banking customers in their personal life, and expect similar experiences from their corporate banks. They also want retail-like real-time payments and faster payment systems. Another area where corporates have invested heavily is reconciliation. Adoption of solutions like virtual accounts can help corporates digitize and manage cash management more efficiently.

Regulatory changes: Regulatory changes like the upcoming Basel III norms, norms related to BEPS, and thin capitalization rules in various jurisdictions have now made some of the traditional products like Notional Pooling and Domestic/Cross border sweeping less appealing and very complex as well as costly to maintain. The implications of certain norms like IFRS IAS 32, presentation norms on offsetting and cash pooling are impacting the traditional liquidity management products like Notional Pooling. Wolfsberg guidelines, and the exhaustive AML/KYC norms make it a cumbersome process to have multiple accounts or entities defined. It is against this backdrop that banks as well as corporates are looking to rationalize their accounts and operational costs. This is where solutions like Virtual Accounts and on-behalf of payments/collections are gathering momentum.

Virtual Solutions: Virtual Account Management has been around for some time, but their usage was either restricted to reference-based reconciliations or in case of bigger companies, for use cases like in-house banking. Now driven by the challenges and opportunities in modern corporate banking combined with regulatory changes, “Virtual Ledgers” are making their way into the corporate banking space. Corporate treasures focus on factors like efficiency, fund optimization, cost reduction, and STP operations. Rationalization of banking relationships is a key area of focus for businesses and virtual account management solutions allow corporates to do this effectively. With virtual accounts and on-behalf-of operations, the benefits are manifold – reduction in cost, risk and administration, easier liquidity management etc. Moreover, onboarding/opening of virtual accounts is much simpler compared to opening new accounts which comes with its set of KYC processes et. al.

DLT/Blockchain: The uptake of DLT in banking is increasing and many banks have already conducted POCs for cross border payments, trade finance etc. In fact, some of them are already production-ready. Cash Management too is poised to benefit from DLT, and DLT applications along with other payment initiatives can lead to more secure and significantly faster settlements.  

Artificial Intelligence and Advanced analytics: Getting the required amount of information is key to good decision making. Use of AI and advanced analytics in cash management is on the rise as it can ensure availability of data and knowledge throughout the business to make better liquidity decisions. Predictive and prescriptive analytics can help corporates mine the mammoth amounts of data they have to further improve their business output and financial performance. Predictive analytics techniques like statistical analysis, rich data modelling, real-time processing and scoring can be used to detect trends related to forecasting. Scenario modelling using techniques like prescriptive analytics can help corporates analyze different courses of action, rank them and pursue the most suitable one. Some of the key questions which can be addressed with the help of analytics include:

  • Adequate limits/balance and liquidity flows available or not
  • Are there heavy outflows to be expected and grouping/time of such debits – Do the debits occur early in the day, while credits arrive later?
  • How to efficiently use the liquidity in the system by orchestrating payment and receivable thereby minimizing the overdrafts required
  • How much of the funds are tied up due to time-consuming cross-border payments?
  • How accurately can we predict the intraday liquidity forecasts and how to improve them?

Using solutions like virtual account can further help improve analytics as there is more information and data available in real-time with straight-through reconciliation, virtual account level statements etc.

RPA, OCR and Machine Learning: Robotic Process automation combined with machine learning techniques can completely change the way corporates operate today. There are a lot of activities like remittance advice generation and payment advice application which currently take place in a manual + system mode. These kinds of activities are prime candidates for applying machine learning practices to help streamline the whole process. A fully integrated system effectively using OCR based tools can help in various activities like A/R, A/P and reconciliation.

NLP/ Chatbot: Voice is the new touch. Adoption of Siri or Alexa the world over points towards the increasingly digital ways banking services will soon be consumed. Machine Learning-based Natural Language Processing tools can also be used to offer real-time, chat-bot-based assistance to corporates. This is especially essential as most of the activities in the near future will be carried out either on wearables or mobile phones or tablets and most of the commands will be voice-based. Robo advisory can also help banks act as an advisor and not just a service provider.

Internet of Things: Apart from the most obvious use case of tracking goods in transit to streamline cash management and trade services, there are several other innovative use cases for IoT in banking. One of the most vital capabilities of IoT is the real-time data feed and communication which when combined with virtual accounts and blockchain technology has resulted in potentially disruptive benefits. Banks are toying with the concept of machine identity through blockchain which enables assigning virtual accounts to machines to process transactions at a machine level.

Neural network and self-learning algorithms: Today, any corporate with inflexible and stringent payment terms can find themselves in difficult situations. It is very critical for suppliers to ensure effective utilization of their cash. Neural network-based systems can help identify and inform corporates about the cost of delay, where and how to pay etc. and provide actionable insights. The amount of data available coupled with the capabilities of AI to evaluate them can help corporates with a clear picture on aspects like:

  • whether credit should be given to a supplier
  • what are the chances of the credit turning bad
  • who all are likely to make early, timely or late payments

For example, it may help corporates identify and offer early special terms to actors in a business’s supply chain. This way, organizations can manage their own cash position effectively and also support their best partners, who may be given more leeway on payment terms. These algorithms can also help identify potentially fraudulent activity and assist proactive action automatically.

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