Corporate banking’s biggest challenges in 2021, and how to solve them
In the world of corporate banking, it can be difficult to plot a path that pleases all parties. The challenges from a bank’s perspective can sometimes differ greatly from those facing their clients.
To provide solutions to these challenges, we first need a unified vision as to what they are. NTT DATA’s Global Corporate Banking practice has been engaging in a number of initiatives designed around providing this much needed clarity.
Based on this, we’ve established three key areas on which to focus: cash management, working capital, and trade finance. By identifying the challenges both clients and banks face in these areas, we can then use this information to craft solutions for all involved.
Regarding cash management, banks can often find their internal processes to be very manual, and therefore unnecessarily time-consuming. There is a need for end-to-end digitisation in order to make cash centralisation, reconciliation and fraud detection workflows more efficient. The integration between applications can also be improved, allowing customers to connect real-time services and data as well as optimising customer service offerings.
Payment processes also remain time-consuming, with the involvement of multiple parties in the process leading to increased inefficiency. Banks are increasingly expected to provide their clients with a higher level of security during payment and authorisation processes, on top of adhering to regulatory standards such as ISO 20022.
From a client’s perspective, liquidity access and a limited visibility in real time cash position and cash forecasting remain major challenges. This is in addition to a lack of integration into corporates’ ERPs, which is needed to improve the accuracy of liquidity measures. Another challenge is the decentralisation of cash management solutions, which has the knock-on effect of limiting the global concentration of subsidiary positions.
Disruptive technologies are the key here. By incorporating robotics and machine learning solutions, banks are able to automate previously manual processes in reconciliation, fraud detection and financial crime activities. The automation of fund transferring, via digitization and smart contracts, will help facilitate real-time transactions, and reduce interactions with correspondent banks. Biometrics can also be implemented to help provide greater security in payments for clients, increasing the speed of the lifecycle process.
For clients, transactional data sharing among banks will facilitate client’s cash visibility and cash forecasting activities. Artificial intelligence and machine learning solutions with ERP integrated dashboard solutions can improve cash monitoring and cash forecasting to increase visibility into their cash position. Using API integration platforms can help enhance cash centralisation, whilst a virtual account structure will improve reconciliation to manage the global concentration at a subsidiary level.
Banks need to focus on optimising the efficiency in supply chain finance processes. These include duplication reductions, invoice optimisation approval and discount maximisation. Improving the integration of these processes and reducing interaction between involved parties is a priority, as well as increasing security around the process as a whole.
Manual onboarding processes also remain painfully time-consuming. Banks must reduce the probability of default and improve the analysis of the credit risk in the supply chain finance process.
For clients, there is a need for working capital financing products to improve their working capital ratios, as well as obtaining funding through commercial debt. Additionally, there is an increasing need to leverage banking infrastructure to finance the suppliers by utilising the cash surplus. The visibility of real time supply chain finance lifecycle processes and status remains important, as does the need for improvement in the communication to supply chain finance requirements.
For banks, automating the supply chain finance processes and implementing smart contracts can help reduce manual activities, increase speed, improve invoice processes and provide security whilst reducing the need for interactions with multiple parties. Digitising the onboarding process also goes a long way towards improving efficiency.
Implementing machine learning solutions can help estimate the probability of default and reduce credit risk in supply chain processes. Integrating these processes through APIs will reduce friction in communicating between banks, ERPs and rating agencies.
For clients, it’s all about finding a better way to manage cash and liquidity. This can include the anticipation of invoice collection through the receivables program for cash release purposes and providing liquidity to suppliers in advance through supply chain finance programs, plus negotiating new payment dates with banks.
To optimize the use of cash surplus, the implementation of dynamic discounting services can provide cash in advance to suppliers which leverage the bank’s infrastructure and APIs. Advanced analytics can reduce the likelihood of default and improve supplier analysis, whilst a digital platform solution with multi-geographies capabilities in real time can help visibility and end-to-end tracking of supply chain finance processes.
For improving communication and response time with customers, something as simple as a chatbot is an efficient and cost-effective solution.
The headline challenge for banks regarding trade finance is a lack of communication in documentary trade processes, among both internal and external clients. There are also issues with duplication in documentary trade activities with multiple parties involved in their payment processes.
Efficiency with onboarding processes also remains a problem, given the administrative time in executions, excessive documentation required and lack of solutions to extract data from reports. The documentary trade processes do not provide visibility to clients during the product lifecycle, and inefficiencies in the reconciliation from poor voice matching processes arise due to a lack of information.
The challenge from a client perspective is that there is a lack of real-time visibility through the documentary trade lifecycle process. Interactions with correspondent banks also reduce the efficiency of auditing activities.
Including chatbot solutions, supported by the implementation of artificial intelligence, can help improve communication in documentary trade processes. Blockchain solutions can be leveraged to reduce transaction times and automate end-to-end processes, whilst the implementation of OCR solutions can help optimise the extraction of documents.
The digitalisation of onboarding processes to automate data and document collection will improve the efficiency of onboarding, and the implementation of a digital platform will improve the documentary trade process by guaranteeing a solution with end-to-end connectivity to enhance lifecycle visibility. Artificial intelligence algorithms can also be used to streamline invoice matching processes which will allow self-learning from human decisions and improve customer satisfaction.
For clients, the focus is to implement an end-to-end digitalisation process to provide better visibility and monitoring through the lifecycle process.
As a result of the capacity to generate cash, capital needs from companies, and the obstacles to improve the working capital management, banks are adopting measures to offer solutions to clients to protect their balance sheet and reinforce their risk practices.
Meanwhile, corporate clients are taking steps to increase their liquidity, gain access to finance and reduce the impact of financial risks.
Having identified the challenges both parties face, the aforementioned solutions can help banks and clients clear these hurdles.