FUSION LENDERCOMM
Company : Finastra
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Target Industry : Financial Institutions(Agent Bank & Lender Bank)​
BNY Mellon, HSBC, BNP Paribas, Natixis, Société Générale
A blockchain-based platform that enables agent banks and lenders to securely exchange syndicated-loan data in real time.
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Fusion LenderComm is a digital platform developed by Finastra, in collaboration with R3 and leading global banks, to transform the syndicated lending process — a traditionally manual, opaque, and fragmented workflow between agent banks and lenders.
By leveraging distributed ledger technology (DLT) on R3’s Corda and deep integration with Finastra’s Fusion Loan IQ, the platform delivers real-time transparency, efficiency, and trust across all participants.
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As a UX designer, the goal was to simplify the complexity of syndicated loan management — reducing administrative effort, eliminating reconciliation errors, and building a self-service experience lenders could trust.
Initial Problem Statement
The traditional syndicated loan market is a critical part of global finance, but its underlying processes have long been characterized by inefficiency, fragmentation, and a lack of transparency.
Before the introduction of platforms like LenderComm, agent banks and participating lenders relied on a highly manual, paper-based, and fragmented communication infrastructure. The syndicated loan market, worth trillions globally, relies heavily on manual processes, email communications, and fragmented systems for deal servicing and position reporting.
The Challenge
The design needed to:
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Support secure, role-based access to deal data.
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Create a self-service experience for lenders to view their positions, accruals, and transactions.
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Integrate seamlessly with existing back-office systems (Loan IQ) without forcing workflow disruption.
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Reflect the trustworthiness of blockchain technology through clear visual and interaction design.
How might we digitize the syndicated loan information exchange between agents and lenders, while ensuring data integrity, transparency, and user trust across a multi-party ecosystem?
Discovery
Opportunity
There was a major opportunity to redefine syndicated lending by bringing modern digital UX to a process that hadn’t evolved in decades.
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The platform could:
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Reduce operational costs and manual effort.
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Increase transparency and speed of information flow.
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Enhance data quality and compliance through immutable records.
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Strengthen Finastra’s leadership as an innovator in corporate banking technology.
For UX, this meant the chance to humanize complex financial data and make distributed-ledger technology tangible and trustworthy for traditional banking users.
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The goal was to reimagine how information flows between all parties — without disrupting existing systems of record.
User Interviews
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5 Agent Bank Operations Managers
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8 Lender Relationship Managers
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3 Loan Administrators
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2 IT System Integrators
Insights
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Lenders needed instant access to deal-level data without relying on agent emails.
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Trust and accuracy mattered more than visual flair — “I need to be sure this is the official figure.”
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Agents wanted automation for data publication and clear control over what’s shared with whom.
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Most users came from legacy UIs; too much novelty would reduce adoption.
Pain Points
Key user pain points identified through industry research included:
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Manual and Error-Prone Processes: The exchange of sensitive loan information, data updates, and administrative details often involved time-consuming methods like faxes, emails, and phone calls. This manual intervention increased the risk of human error, miscommunication, and operational risk across all parties.
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Data Latency and Lack of Transparency: Lenders often had to wait for agents to provide updates, leading to a significant delay in accessing accurate, real-time information about their specific deal positions. This lack of immediate transparency made it difficult for lenders to optimize their portfolios or make timely, informed financial decisions.
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Inefficient Reconciliation: Both agent banks and lenders spent considerable time and resources on reconciling data due to the fragmented nature of information sources. This duplication of effort was costly and slowed down the overall loan lifecycle.
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High Operational Costs and Burden: The cumbersome administration involved in agent-to-lender communication created a significant cost and resource burden for financial institutions, reducing operational efficiency and profitability.
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Limited Scalability and Integration Challenges: Existing systems were often rigid, making it difficult for banks to adapt to new market demands, scale their operations, or seamlessly integrate with modern, innovative technologies
User Persona
Agent Bank Operations Manager
Name : Sarah Mitchell
Organization: Global Investment Bank Agent
Experience: 12+ years in loan servicing and agency operations
Location: London, UK
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Background
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Sarah oversees a team that manages syndicated loan portfolios worth billions.
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Her team’s responsibility is to ensure that loan data, interest calculations, and payment instructions are accurate and shared with hundreds of lenders across different time zones.
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She works heavily in Finastra Loan IQ, relying on spreadsheets, emails, and manual data reconciliation to communicate with lenders.
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Mistakes or delays can lead to financial discrepancies and reputational damage.
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​Goals
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Ensure data accuracy and compliance across all syndicated deals.
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Reduce manual reporting cycles and lender follow-up queries.
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Maintain transparency with participating lenders without losing control of sensitive data.
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Provide her management team with clear audit and performance visibility.
Pain Points
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Too many repetitive data-publishing tasks — each lender requires a different report.
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Time lost responding to simple lender queries (“What’s my current balance?”).
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Difficulty verifying who has the latest data version.
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No visual trail or audit history to validate information changes.
Needs & Expectations
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A secure, automated way to publish loan information to multiple lenders.
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A dashboard view showing all deals and data publication status.
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Role-based permissions to control who sees what.
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Audit trail visibility to support compliance and reduce disputes.
Design Implications
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Prioritize clarity and control in the interface.
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Use clear system feedback and timestamped updates to signal data reliability.
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Provide batch publication and monitoring capabilities.
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Keep visual design enterprise-neutral — efficiency over aesthetics.
Lender Relationship Manager
Name: Rajesh Nair
Organization: International Commercial Bank (Lender)
Experience: 9 years managing syndicated lending portfolios
Location: Singapore
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Background
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Rajesh manages multiple syndicated loan participations for his bank’s corporate clients.
He relies on the agent bank for timely data on interest payments, outstanding balances, and repayment schedules. -
Currently, Rajesh and his team depend on periodic spreadsheets and email attachments — making it difficult to track real-time positions or reconcile internal records.
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Pain Points
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Access accurate loan data on demand, without depending on agent reports.
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Quickly verify accruals and upcoming payment dates.
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Export consistent data to his internal risk and accounting systems.
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Reduce reconciliation effort and avoid errors in reporting.
Pain Points
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Long delays waiting for agent banks to respond to data queries.
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No visibility into updates or changes until official reports arrive.
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Difficult to track who made what update and when.
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Manual data entry across multiple deals and currencies.
Needs & Expectations
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A self-service dashboard showing live syndicated loan positions.
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The ability to filter, export, and reconcile loan data quickly.
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Transparency and timestamping for all updates.
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Assurance that data comes from an official, trusted source.
Design Implications
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Present complex data in simple, scannable tables and summaries.
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Show “last updated” and data-source information prominently.
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Support efficient workflows — export, filter, and search functions first.
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Reinforce trust through consistent data presentation and error-free interactions.
Design Strategy
Information Hierarchy for Clarity
Data Transparency as a Design Element
Role-Based Interaction
Integration with
Loan IQ
Streamlined complex datasets (positions, accruals, balances) into an intuitive drill-down structure — portfolio → deal → cashflow → transaction.
Used visual cues (timestamps, last-updated labels, source markers) to reassure users that data was live, validated, and traceable.
Designed modular dashboards that adapted to user roles — agents saw publishing and audit tools, while lenders saw consolidated portfolios.
Ensured the UX seamlessly reflected back-office data, bridging the gap between legacy and new systems.
Competition
The 3 biggest banks in the world, announced they were partnering to solve the same problem.
This only further proved our solution was one that was needed.
Our senior product manager, decided to pivot and leverage the fact that the overwhelming majority of people in the syndicated loan market used Finastra’s other product Loan IQ. So, the idea of a Loan IQ module was born.
Outcome
The communication between lenders and agents was streamlined. And allowed lenders to view and process over 30 types of transactions, automated deal mapping and transaction processing and integrated with Loan IQ.
Real-Time Data Visualization: Replaced static reports with dynamic tables and interactive dashboards.
Audit Trail Transparency: Each data update was trackable, creating a visible chain of trust.
Self-Service Access: Lenders could view, filter, and export loan data without manual agent intervention.
Consistent Financial Language: Used domain-specific terminology and formatting to reduce learning friction.
KEY OBSERVATION FROM USER TESTING
Connecting Disparate
Systems
I had a creative strategy to automatically map deal data based on key data and weighing those factors for recommendations.
The issue was that the lender’s serving system might not have all the data or match what we have. I kept thinking of how the user needed to do extra work to map deal data between the 2 systems.
I brought up my concern in a meeting and showed the idea of auto-mapping in a mockup. After a few collaborative meetings with the business analysts, some key pieces of data were pinpointed that would be similar. For the North American markets, there were 2 key data points to help identification. With that I advocated for the giving weighted values for these data points for recommendation ranking, and if they all matched, then Fusion LenderComm would automatically map them.
Insights
Terminology varies between countries and businesses, so it was important to use system agnostic terms.