In the rapidly evolving landscape of financial operations, Artificial Intelligence (AI) stands out as a transformative force, offering substantial opportunities for enhancing business value. This shift towards AI adoption is not merely about technological advancements but rather about leveraging these tools to achieve tangible benefits and drive strategic outcomes.
Financial institutions have long sought to automate processes and reduce manual intervention. AI presents a significant opportunity to streamline operations, minimize errors, and enhance efficiency across various functions such as trade reconciliation, regulatory compliance, and exception handling. By automating routine tasks and leveraging predictive analytics, firms can optimize resource allocation and focus on value-added activities, ultimately driving down operational costs and improving overall productivity.
One of the key advantages of AI lies in its ability to analyze vast amounts of data and extract meaningful insights in real-time. By harnessing AI-driven analytics, you can gain deeper visibility into your operations, identify patterns, and anticipate future trends. This enables informed decision-making, allowing firms to proactively address risks, capitalize on opportunities, and stay ahead of the competition.
In this blog we are going to take a closer look at some of the initiatives SimCorp is working on in relation to artificial intelligence in the operations space (aka IBOR, Back Office and Settlement), but also what other initiatives they are working on to improve its solutions.
Artificial Intelligence – Practical Application
It seems that every company around the world is exploring the benefits of Artificial Intelligence (AI) and how to apply it. SimCorp is no different. While AI has become a buzzword, particularly with the emergence of technologies like ChatGPT, the emphasis here is on predictive AI rather than generative AI.
Here are some examples of improvements SimCorp is currently working on.
In operations there has always been a desire to automate as much as possible, whether through enhancing Straight Through Processing (STP) rates or employing rule-based automation to handle common exceptions. In addition, there exists a lot of data. This combination makes it ideal to apply AI as a complementary layer on top of this framework, addressing issues beyond the scope of automated trade flows or rule-based logic. It serves as a solution for challenges that traditionally only a human could solve for. With advanced statistical modeling integrated into solutions, exceptions can be further automated by learning from user resolutions and applying that knowledge to the remaining dataset.
Typically, in reconciliation workflows, efforts are made to automate matching and data processing as much as possible. However, this often results in a list of breaks that may include legitimate discrepancies or errors requiring manual intervention for resolution. This scenario presents a prime opportunity for the application of AI. While the data logically aligns, human intervention is necessary to ensure accurate matching. By leveraging observational AI, the model can be trained using manually matched data, which can then be applied to reconcile future unmatched data. Moving forward, the system can automatically suggest matches based on the user's past interactions, enhancing efficiency and accuracy in reconciliation processes.
A common concern raised about AI revolves around its opacity, often referred to as a "black box." Essential for user adoption is the ability to illustrate why a match is proposed, showcasing the linkage between attributes in a given record and what percentage of certainty that is. This transparency is paramount in fostering confidence in the system's recommendations, even more so than the model itself, as it ensures users can fully understand and trust the system's output.
Another application of AI is in regulatory reporting, where the system can predict whether a specific attribute in a transaction report has been reported correctly compared to what is typically reported for the respective types of assets. This is particularly valuable for attributes not covered by standard validation rules, making them difficult for clients to detect. By providing this capability, clients gain additional assurance that their regulatory reporting is accurate. This is a space SimCorp is exploring with their clients, offering them insights that can help avoid fines or issues arising from updates in standard validation rules.
Strategic Goals – Other Enhancements
With a stated goal of reducing total cost of ownership for their clients, SimCorp’s strategic development goals aim to address these. In this section we take a closer look at what some of these are.
The first is enhancing workflow automation, specifically targeting the workflow that enables clients to manage and automate their exception processes, distinct from STP automation. For instance, consider a scenario where a client repeatedly encounters issues with a counterparty providing incorrect settlement dates for fixed income instruments every Friday. This continual challenge prompts repeated resolution efforts with the same counterparty. However, by implementing automated workflow solutions, clients can leverage decision-making logic such as "if this, then that" to autonomously handle these exception processes. Consequently, they gain the ability to easily control, amend, and update these rules as they see fit.
Second, is the implementation of more AI into the solution, namely retention of knowledge that a user has applied to resolve an issue within the system itself. Over the past few years, there has been notable attrition in the operation space, whether due to internal transfers to different teams or simply leaving the company. Therefore, providing a solution that minimizes the impact of such transitions by implementing tools to automate onboarding is invaluable to investment firms.
Third, SimCorp is working on improving the onboarding process for new custodians, taking advantage of readily available tools that can facilitate this process efficiently and effectively. By leveraging such tools, firms can quickly and seamlessly map any new data feeds required by clients or establish connections with new custodians. This capability significantly accelerates the time to market and streamlines the entire onboarding process. Seamless transition from one custodian to another ultimately empowers clients to pursue optimal operational efficiencies.
Lastly, SimCorp is exploring synergies across investment operations products. Having a front-to-back solution means there is a lot of information in the installation. The goal is to ensure a thorough understanding of potential issues and their occurrences across various areas. For instance, if a settlement issue also appears in settlement reconciliation, it's important to provide users with the insight that this issue already has been identified. This helps facilitate coordination between teams and ensures efficient resolution. This provides firms with a comprehensive and cohesive view of their operational landscape.
Introducing Insights
Allowing clients to gain better understanding of their data, SimCorp aim to incorporate analysis and predictability into the processes. This involves introducing analytical capabilities on exceptions and failure rates. Is there a recurring issue that leads to settlement or STP problems? Perhaps a particular custodian is consistently problematic. The objective is to provide firms with these insights to enable informed decision-making, thereby enhancing their operational efficiency.
The proposal includes introducing benchmarking against industry peers. This entails assessing whether your firm is underperforming in comparison to your competitors and if you are exposed to additional risks. Moreover, there's a plan to integrate data analytics services into the investment operation line.
The goal is to provide firms with insights enabling them to predict failures and exceptions. Are there heightened risks of failures during particular periods, such as month-end or post-issuance of an asset class? In other words, empowering firms with the knowledge and foresight to make proactive decisions rather than reactive ones.
SimCorp Onboarding Simplified – Standards
One stated goal from SimCorp is to help ease the burden for their clients to enter new jurisdictions and new asset classes. There already exist tools to support this, but they are working on expanding these while making them more standard, offering turnkey solutions that streamline the onboarding process. This is achievable through the SaaS delivery model and a focus on standardization.
For instance, Simcorp provides standardized offerings for various services, such as regulatory reporting. Firms in Europe are bound by regulations such as MIFID II, SFTR, and EMEA reporting, which are highly standardized. Thus, offering a standardized solution that clients can easily activate or deactivate is of great importance to them. With only a few trade repositories or MIFID II arms needing connection, providing seamless integration to these providers is important for firms. This streamlined process significantly assists clients in staying abreast of new regulations and updates to regulatory requirements.
Similar challenges as in Europe exist in other jurisdictions. SimCorp therefore offers turnkey solutions for global regulatory requirements so firms can effortlessly expand into new jurisdictions.
Operational Excellence
In the realm of financial operations, the integration of Artificial Intelligence (AI) marks a significant shift towards optimizing business value. Beyond mere technological advancements, AI presents a transformative opportunity to drive tangible benefits and strategic outcomes for financial institutions.
By automating processes and leveraging predictive analytics, AI streamlines operations, minimizes errors, and enhances efficiency across various functions. This empowers firms to allocate resources more effectively, driving down operational costs and boosting overall productivity.
Moreover, AI-driven analytics provide deeper insights into operations, enabling informed decision-making and proactive risk management. Financial institutions can anticipate trends, address challenges, and stay ahead of the competition by harnessing the power of AI.
SimCorp, like many industry leaders, recognizes the potential of AI in operations. By prioritizing initiatives such as workflow automation, knowledge retention, and streamlined onboarding processes, SimCorp aims to enhance operational efficiency and support firms in scaling their business operations.
In essence, the convergence of AI, strategic innovations, and client-centric solutions is poised to redefine the landscape of financial operations. By embracing these advancements, financial institutions can unlock new opportunities, navigate challenges, and maximize business value in an ever-evolving market.
If you're interested in learning more or seeking ways to enhance your operations department, we're eager to connect with you. Feel free to reach out to us via email or phone – we look forward to hearing from you!
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