CIAL 360 – Transforming Credit & Risk Decisions

Year
2019 – 2020
Role
Lead Product Designer
Key Contributions
Research, UX/UI, Prototyping, User Testing, Stakeholder Collaboration

Overview

CIAL360 Credit is a SaaS platform designed to digitise and simplify credit risk management by centralising data, automating workflows, and enabling finance teams to make data-driven decisions. Leveraging access to one of the world’s largest commercial databases, CIAL360 helps users gather, analyse, and compare business information to improve decision accuracy and profitability.

Challenge

Designing a Seamless Credit Risk Platform: A key design challenge was creating a user-centred interface that could replace traditional, time-consuming workflows with a digital, centralised solution. The platform needed to support a clear flow — from searching companies in a vast database to analysing data and making credit decisions. Ensuring accessibility across various roles, designing flexible features for different user permissions, and balancing usability with robust functionality were central to the design process.

How the Design Sprint Shaped the Search → Analyse → Decide Workflow

I began with a design sprint to establish foundational goals and challenges with key stakeholders, including finance managers, credit analysts, and report-generating staff. This collaborative session was crucial in setting a high-level vision and defining core workflows for the platform: company search, data analysis, and decision-making. Together, we mapped out essential user flows and envisioned the platform's role in replacing manual processes with an intuitive, centralised solution.By the end of the sprint, I developed a prototype reflecting the initial design strategy. Early user feedback from this prototype offered critical insights, setting a strong foundation for further refinement.

Research and Discovery

Following the sprint, I conducted in-depth research to validate assumptions and uncover deeper insights into user needs. Through interviews with clients and internal reporting staff, I learned that users struggled with analysing business reports individually, without tools to aggregate or compare data. This process not only added time but also led to inconsistencies in decision-making. My research confirmed the need for features like centralised data tables, comprehensive filtering options, and consistent evaluations to streamline credit assessment.This discovery phase provided invaluable context for refining the prototype, allowing me to prioritise solutions that addressed both user frustrations and business goals.

Personas

Based on research, I identified three primary personas, each with distinct permissions and responsibilities:

Chris, the Credit Analyst

Frustrations: Manual data analysis is time-consuming and inconsistent, lacks streamlined comparison tools.

Primary Goals: Access customisable views for focused evaluation, conduct efficient and reliable assessments.

Morgan, the Finance Manager

Frustrations: Needs faster access to high-level summaries, clear evaluation status, and decision-making tools.

Primary Goals: Quickly interpret data summaries, ensure accuracy in recommendations, and maintain efficiency.

Taylor, the Executive

Frustrations: Needs straightforward, high-level insights without sifting through details.

Primary Goals: Access a comprehensive top-level dashboard, track key metrics efficiently, and support strategic planning.

Solution

My solution design prioritised ease of use, role-based accessibility, and a structured flow of search → analyze → decide. Key features included:

1. Company Search

CIAL360 allows users to quickly search over 587 million companies in the CIAL Dun & Bradstreet database using multiple search criteria, providing an expansive yet streamlined way to access relevant business information for credit evaluations.

2. Centralized Data Collection and Evaluation Views

To improve data accessibility and streamline analysis, I designed centralised data collection with two primary views: a table view for granular report comparisons and a dashboard view for an overview of critical portfolio metrics. This setup allowed users to easily filter, sort, and analyse data from various business reports in one location, significantly reducing the time and effort needed for comprehensive evaluations.

3. Decision-Making with Role-Based Permissions

Role-based permissions ensured each user could only access information relevant to their position, supporting a collaborative yet secure credit evaluation process. By enabling customised access levels, finance teams could work more effectively, share insights, and make informed credit decisions efficiently.

Testing and Iteration

After the initial prototype, I led user testing sessions with a select group of early clients who previously used manual credit risk processes. Feedback from these clients informed critical improvements:

  • Enhanced data filtering options for faster access to specific information
  • Improved visibility of real-time workflow updates to support transparent collaboration
  • Role-specific navigation adjustments to streamline user experience based on distinct permissions and tasks

Results and Impact

The final product design for CIAL360 Credit successfully transitioned finance teams from manual, fragmented workflows to an efficient, digital platform. By centralizing data and automating key processes, the platform reduced the time spent on credit evaluations and allowed finance teams to make faster, more accurate decisions. CIAL360 enhanced collaboration across teams, ensured data consistency, and provided accessible, user-centered interfaces that finance professionals of all levels could navigate easily.

Conclusion

Through user-centred research, strategic prototyping, and continuous design iteration, I developed CIAL360 Credit as a comprehensive tool that modernises credit risk management for finance teams. The platform’s UX design prioritises intuitive navigation, role-based accessibility, and efficient workflows, enabling finance teams to make smarter, data-driven credit decisions.

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