Insights

Within the Capital Markets industry, Intelligent Applications are rapidly evolving from a technology paradigm into a strategic lever for operational efficiency and value creation.

These applications represent the convergence point between traditional functionalities and advanced AI and Machine Learning capabilities, enabling new levels of automation, adaptability, and actionable insights.

This paradigm is built on five key design principles that guide both development and adoption.

Dynamic user experience enables applications to adapt to operational context and user profiles, delivering personalized interfaces and workflows. Embedded intelligence integrates AI directly into business processes, making it a native component of execution, control, and analytics activities. Autonomous orchestration enables end-to-end management of complex processes by combining automation, process mining, and adaptive workflows to reduce manual intervention and improve exception handling capabilities. A modular and reusable architecture, based on composable logic and API-first principles, enables the development of flexible and scalable solutions that can be rapidly integrated into existing ecosystems. Finally, unified and contextual operational data management helps overcome fragmentation and application silos, enabling advanced analytics and AI-driven functionalities.

While these principles define a clear architectural framework, the real challenge today is translating this vision into concrete use cases capable of generating measurable impact across core processes and the overall operating model.

BOSS: The Intelligent Application for Capital Markets Back Office

In this context, the evolution of our BOSS solution represents a key step forward. BOSS has been designed as an intelligent ecosystem supporting the entire front-to-back value chain within Capital Markets. The objective is clear: to bring the principles of Intelligent Applications into securities and derivatives back-office processes, historically characterized by high operational complexity and significant cost pressure.

BOSS will natively integrate AI capabilities — including LLMs, Machine Learning, and Generative AI — into operational workflows, alongside process mining, RPA, and agentic orchestration components. This approach not only automates repetitive tasks but also introduces predictive and advanced decision-support capabilities, particularly in processes such as settlement, reconciliation, and corporate actions management.

At the same time, the adoption of a modular, API-first architecture enables a composable approach in which capabilities can be progressively introduced, reducing time-to-value and simplifying integration with existing application ecosystems.

Reducing Cost to Serve: From Operational Efficiency to Scalability

The primary value driver behind this evolution is the reduction of Cost to Serve across back-office operations. In the sell-side environment, this cost is largely driven by human resources, which typically account for approximately 50–60% of the total.

This is precisely where Intelligent Applications deliver the most significant impact. Intelligent automation and process orchestration enable organizations to structurally reduce operational effort, while simultaneously improving process quality and resilience.

Analyses conducted across the main use cases show that operational effort reductions in the range of 20–30% are achievable, generating substantial economic benefits or, alternatively, enabling business volume growth without proportional increases in headcount.

Importantly, the value extends beyond direct cost savings. The real transformation lies in the ability to industrialize processes, reduce dependency on manual activities, and enable more scalable and data-driven operating models.

From Principles to Use Cases: Where Value Is Generated

The transition toward Intelligent Applications is already materializing through a range of use cases identified within BOSS, targeting the most operationally intensive areas of the back office.

Among the most relevant examples, intelligent automation of trade ingestion and validation significantly reduces manual activities and data-entry errors while improving upstream data quality. Downstream, anomaly detection models proactively identify inconsistencies and abnormal patterns, reducing operational risk and rework.

Another high-value area is settlement fail management, where Machine Learning capabilities enable true “Operations Copilot” functionalities. The application can automatically identify the root cause of issues, recommend corrective actions, and support operators during resolution, significantly reducing handling times.

In the areas of position and collateral management, predictive and optimization models improve both the quality of available information and the ability to support higher-value decisions, such as optimal collateral allocation, with direct impacts on funding costs and balance sheet efficiency.

Finally, the evolution toward operational “control tower” models, enhanced by anomaly detection and intelligent prioritization capabilities, enables proactive end-to-end process management, improving operational resilience and service quality. In this context, the introduction of natural language explanation layers and operational copilots represents a further evolutionary step, making data and insights immediately accessible even to non-specialist users.

The Opportunity

Intelligent Applications now represent a concrete opportunity to rethink the Capital Markets operating model. With BOSS, we are turning this vision into reality by developing targeted use cases that combine technological innovation with tangible business impact.

The journey is already underway: the next step will be scaling these capabilities and supporting our clients in adopting a more efficient, intelligent, and future-ready operating model.

Discover our Capital Markets offering

The transition to T+1 settlement represents one of the most significant changes for European financial markets in recent years. It is not merely about shortening the settlement cycle by one day, but about addressing a transformation that directly impacts processes, systems, and operating models across financial intermediaries.

The regulator’s objective is clear: reduce systemic risk, strengthen market resilience, and increase transparency in settlement flows. However, implementing T+1 in Europe presents structural complexities that distinguish it from other international experiences. The presence of multiple markets, CSDs, and differing operating models requires a high level of coordination across the entire operational chain.

In this context, daily dialogue with banks and service providers highlights how compressed timelines make phases that are often handled on a deferred basis — such as pre-matching, data quality, and exception management — increasingly critical. From TAS’s perspective, as a long-standing technology provider in the capital markets space, T+1 cannot be viewed as a mere compliance obligation, but rather as an evolution of the operating model.

Under T+1, settlement fails can no longer be treated as events to be analyzed retrospectively. They become risks that must be actively managed throughout the trading day, requiring up-to-date information and tighter integration between securities, cash, and reporting systems.

In this scenario, increasing process automation and the evolution toward more “intelligent” applications play a central role. The compression of processing timelines makes management models based on manual intervention or ex-post controls progressively unsustainable. Institutions need systems capable of supporting timely operational decisions, prioritizing exceptions, and continuously monitoring process status.

Ongoing dialogue with the market reveals a recurring theme: adapting individual applications is necessary, but not sufficient. Without an end-to-end process view, there is a risk of informational fragmentation, making operational governance more complex precisely when speed becomes a critical factor.

It is from these considerations that the need emerges to strengthen structured moments of discussion among market participants. This is the objective TAS pursues through its dedicated, periodic User Groups — designed as dialogue forums with directly involved intermediaries to jointly analyze topics that significantly impact technological and market developments.

Within a new Capital Markets User Group, the T+1 topic can be addressed alongside other key transformation drivers — from regulatory reporting developments to digital asset initiatives and the coexistence of DLT-based markets with traditional infrastructures — with the goal of sharing experiences, approaches, and common operational perspectives.

In a landscape that continues to evolve, marked by converging regulatory and technological transformations, dialogue among market participants represents one of the key elements for successfully navigating a transition that, more than ever, requires a shared vision.

Article by Roberto Bruschi, Business Development Manager of TAS.

Original Source: Bancaforte