By Sarath Madakayil, Head of Presales APAC, SmartStream
At the SmartStream Forum in Singapore, a wide spectrum of discussions revolved around post-trade technology and operations, and the criticality of a robust liquidity management framework. The event also explored the latest trends and technology applicable to the capital markets industry. A highlight of the forum was the keynote address delivered by Irene Liu, Managing Director of Digital Finance, Regulatory, and Compliance at Accenture. Her presentation titled ‘Navigating Digital Disruption: Exploring Fintech and RegTech in the Financial Services Landscape’ shed light on the significant disruptions that have swept through the financial industry in recent years, owing to remarkable fintech advancements. The introduction of new regulations has also amplified the need for comprehensive data and ad hoc analysis to effectively address a wide array of crises. This increasing pressure has imposed significant challenges on both financial institutions and regulatory experts. Irene emphasised the crucial importance of regtech, powered by extensive transactional data, advanced analytics, and AI (including the rising impact of GenAI). This regtech-driven approach facilitates a shift from passive to proactive compliance, introducing enhanced transparency, agility, and consistency in operations.
Next, our very own Rohith Rajamony, Senior Business Solutions Consultant APAC, shared a great talk around the application of advanced technology and how it enhances efficiency within the back office. Back office functions are the operational backbone of any organisation. They navigate intricate organisational dynamics and undertakes a multitude of tasks, with data processing and reporting standing at their core. For the back office to operate efficiently, it demands a steady stream of accurate, consistent, and pertinent data. This entails a need for cost-effective solutions, self-service capabilities, analytics, scalability, and above all, ease of use and productivity gains. Such enhancements ultimately allow organisations to reduce their reliance on IT resources and respond more swiftly to market demands.
While doing this, it is essential to uphold robust governance and control mechanisms, fostering a secure environment for both the business and its customers. Common challenges within the realm of back office operations generally fall into three categories:
- People-related challenges: These include issues related to training, skills gaps, and employees turnover. When an employee departs, their organisational knowledge departs with them, necessitating the training of new hires. Human fallibility can lead to errors.
- Technology-related challenges: Legacy systems that are inflexible and resistant to change often lead to technological challenges. Integration difficulties between systems, as well as cybersecurity concerns, especially for outdated systems, pose additional problems.
- Environmental/systemic challenges: Increasing volumes of data, growing complexities, and internal processes struggling to keep pace with these changes form the core of systemic issues. Regulatory demands for accurate data add to these challenges.
Dealing with these challenges requires a holistic strategy. This encompasses comprehensive training, adopting automation and AI technology, and implementing robust data governance and cybersecurity practices.
Rohith explained the three key areas where advanced technology can help and simplify these back office challenges:
- Modern architecture: Adopting a multi-tenanted cloud approach creates a hub-and-spoke model where a single software instance caters to multiple customers or tenants. This approach is particularly relevant when different departments and functions interact with shared data and processes. Modern architecture also involves a micro-services approach, breaking down back office functions into manageable modules that can be developed, deployed, scaled, and updated independently. Lastly, APIs facilitate communication between micro-services and other systems, promoting reusability.
- Cloud technology: Cloud environments enable rapid deployment of new tools, scalability, remote work capabilities, and a safe space for innovation. Cloud technology’s disaster recovery features provide data availability and business continuity even during unexpected disruptions.
- Artificial Intelligence (AI): Real-world AI applications can significantly aid in data management, particularly data reconciliation for quality assurance. An ideal AI solution accepts varied data formats, manually or automatically uploaded, while adhering to responsible AI practices. It automatically maps data from different sources, generates rules, learns from user actions, reconciles data, identifies anomalies, and assigns them for human investigation and resolution. This AI-driven process enhances efficiency and accuracy, transforming a task that could take months into a matter of minutes.
By utilising all the three pillars – Modern Architecture, Cloud and AI, we created a solution in SmartStream Air that can handle any volume of data, efficiently. SmartStream Air scales up or down seamlessly based on the data volumes, saving costs, passing that savings to our customers. AI reduces manual operations which are risky, resulting in huge productivity gains for the back office. In the cloud, we ensure information security by adopting best practices across the industry, and by certifying ourselves with external agencies – like SOC, ISO27001 or PCI-DSS. Thus, we enable better data management, there by a more efficient back office. SmartStream Air also won the Red Dot design award for best design in a finance application. This award is one of the largest independent design competition awards in the world.
During the latter part of the forum, another topic that garnered attention was ‘Cash and Liquidity Management 2.0 and what it takes to build a resilient future’ presented by Peter Dehaan, who serves as the Global Head of Cash and Liquidity. His talk encompassed several aspects, including:
- Reflecting on the past
- Evaluating the potential spread of the US Banking crisis
- Identifying challenges faced by treasuries and their significance
- Examining the role of digital technology
The envisioned resilient future entails several crucial elements:
- AI and machine learning integration: ‘TLM Cash and Liquidity’ offers predictions for liquidity, scenario analysis through AI and machine learning, which contribute significantly to financial institutions’ treasury departments. These tools empower banks to potentially reduce liquidity buffers by analysing unstructured data and improving settlement predictions, thereby curbing costs.
- Real-time data: The cornerstone of resilience in the banking system is real-time cash and liquidity management. Accurate insights into cash and liquidity positions enable banks to identify and mitigate potential risks effectively and make informed decisions.
- Maintaining system integrity: Ensuring the integrity of the financial system is paramount, encompassing areas such as preventing money laundering, sanctions violations, and fraud.
Peter’s poll question aimed to gauge liquidity concerns for the upcoming years. The poll results highlighted various concerns, with operational risk emerging as the primary focal point:
- Operational risk – 50%
- Data transparency – 36%
- Address manual processes – 36%
- Operational resilience – 32%
- Moving to the cloud – 32%
Peter’s presentation also touched on the recent US banking crisis and the looming risk of global contagion. Intraday liquidity has gained unprecedented attention in this context. Addressing challenges faced by treasurers and cash managers, Peter brought forth a multitude of key topics. Some of these, like climate risk, central bank digital currencies, and cryptocurrencies, hold sway over intraday liquidity’s dynamics.
Lastly Peter highlighted the capabilities of ‘TLM Cash and Liquidity Management,’ a solution that fosters confidence, compliance, and control over short-term liquidity through automated real-time visibility and management.
The event concluded with Vaibhav Kumar, Senior Consultant APAC, shedding insight on the automation of fees and expenses as a strategy to reduce costs and enhance profitability. Among expenditures in the financial industry, transaction fees, particularly BC&E expenses, represent a considerable share. When examining diverse transaction fees, it’s worth highlighting that BC&E charges encompass the most substantial proportion. To be precise, BC&E fees rank as the second-largest category of non-compensatory expenditure within a bank. It’s reasonable to think that banks typically spend more than $1 Bn annually on BC&E fees! For Tier 1 banks, this amount can exceed $1 Bn almost every year. Meanwhile, Tier 2 and Tier 3 banks can spend anywhere from $100 to $400 Mn annually.
To maintain client profitability, banks need to be innovative in finding ways to optimise spending, reduce costs, improve transparency and operational efficiency. This is precisely where technology comes into play. The underlying systems must be highly scalable and flexible to manage substantial expenditure volumes spanning diverse asset classes and fee classifications. The goal is to understand transactional costs, increase operational efficiencies, automate accounting controls, and develop spend analytics to drive data driven decisions.
Advanced technology and in depth industry knowledge are pivotal for efficiently managing these expenses. SmartStream’s ‘TLM Fees and Expense Management’ solution addresses these challenges by ensuring accurate expense substantiation and proper allocation. The solution enables financial institutions to enhance transparency, allocate expenses effectively, and measure client profitability, ultimately driving informed decision-making.
