For a COO of a private bank, the reporting challenge is rarely framed as a technology problem. It surfaces as something else: relationship managers who are not as prepared as they should be, client meetings that drift toward operational updates rather than strategic conversation, and a creeping sense that the bank's reporting capability is not keeping pace with what clients have come to expect from their most important financial relationships.
The root cause is almost always the same. The bank's data is fragmented across booking centres, internal systems, and asset classes. The analytics layer sitting on top of that data was either built in-house at a point when the requirements were simpler, or assembled from tools that were never designed to work together coherently. The result is a reporting workflow that is slower, more manual, and less analytically rich than the business needs it to be.
Sesame Data is built to solve that problem directly, without asking the bank to replace its core infrastructure or commit to a multi-year technology transformation programme.
Sesame Data is a modular analytics and reporting platform delivered to private banks through a flexible API integration. It sits alongside the bank's existing systems, connecting to data from across the business, normalising it into a consistent and analytically ready format, and making it available through whichever delivery model fits the bank's architecture and client experience requirements.
The platform operates across three deployment models, each of which can be adopted independently or in combination depending on where the bank's most pressing needs sit.
The Analytics API provides a powerful data and analytics layer that the bank can embed directly into its own internal systems, client portals, and digital experiences. Performance analytics, exposure analysis, allocation breakdowns, and portfolio-level insights are all available on demand through the API, which means the bank can surface the right information at the right moment in the relationship manager's workflow without requiring a separate tool or a manual data pull. The API is designed to integrate cleanly with existing infrastructure, which means the time from integration to live capability is significantly shorter than a build-from-scratch approach.
Templated Reporting at scale addresses the operational cost of producing consistent, high-quality reporting across a large client base. Pre-built, configurable report templates allow the bank to generate scheduled and on-demand reports across the full client portfolio, with outputs that are consolidated across asset classes, brand-aligned, and produced without manual intervention. For a COO managing the economics of the reporting function, the reduction in operational overhead is direct and measurable.
The Premium Analytics and Reporting Experience goes further, providing relationship managers and clients with direct access to interactive analytics through a secure, bank-branded portal. Rather than receiving a static PDF, clients can explore their portfolio dynamically, and relationship managers can walk through performance and exposure analysis in real time during a meeting rather than presenting a document prepared days in advance. The portal is fully white-labelled, which means the client experience reflects the bank's brand throughout.
The quality of any analytics and reporting capability depends entirely on the quality of the data underpinning it. Sesame Data connects to data from across the bank's booking centres and internal systems, normalising it into a consistent format before any analytics or reporting is produced. The normalisation layer handles the differences in data conventions, formats, and schedules across sources automatically, which means the analytics output reflects a coherent and reconciled picture of the client's portfolio rather than an aggregation of inconsistencies.
The operational consequence of Sesame Data's analytics layer is a relationship manager who is demonstrably better equipped for every client interaction. Performance data is available on demand rather than on a reporting cycle. Exposure and allocation analytics can be pulled up in a meeting rather than requested from an operations team and followed up afterwards. The preparation time for a client review drops from hours to minutes.
The strategic consequence is a shift in the character of client conversations. A relationship manager who can answer questions immediately, present a clear view of how the portfolio has performed against the client's objectives, and explore allocation and exposure analysis interactively is a relationship manager having a different kind of conversation from one who is presenting a static document. That difference is visible to the client, and it is the difference between an advisor and a reporter.
For a COO evaluating the investment, the commercial case for Sesame Data rests on three things.
The first is the cost of the alternative. A bank that is maintaining in-house reporting infrastructure is allocating engineering and data science resource to a problem that is not a source of competitive advantage. That resource has an opportunity cost measured in the capabilities that are not being built elsewhere in the business. Sesame Data transfers the maintenance burden to a team whose entire focus is keeping the platform at the market standard, freeing the bank's technology capacity for higher-value priorities.
The second is client retention. The banks losing UHNW relationships are rarely losing them on investment performance. They are losing them on experience, on responsiveness, and on the sense that the primary banking relationship is not delivering the quality of insight the client can find elsewhere. A reporting capability that meets the standard those clients now expect is not a discretionary investment. It is a retention mechanism.
The third is speed to capability. A modular integration with Sesame Data delivers a materially improved reporting experience in a timeframe that a build-from-scratch programme cannot match. For a COO under pressure to demonstrate progress on the client experience agenda, the difference between a twelve-week integration and a two-year build programme is not a detail. It is the decision.
Sesame Data is already deployed across private banks, family offices, and institutional clients managing complex, multi-asset portfolios. The platform's architecture is designed for enterprise-grade deployment, with the security, scalability, and integration flexibility that a private bank's technology environment requires.
If the gap between your current reporting capability and what your clients now expect is a conversation you are having internally, it is worth having it with us. Book a demo to see how Sesame Data works in practice and what a deployment would look like for your institution.