— CHUX Long Form Case Study —
I was the lead designer, engaged in all product design tasks from research to design QA after handoff. The MVP released in 2021. 2.0 was a series of projects from 2022-2023. Debt Data was a large-scale feature BondLink's B2G SaaS platform called the Issuer Portal.
Check out the transformation from the MVP to 2.0. Clicking the link above the images below will open a lightbox with the relevant version's mockups. Then read the case studies for MVP and 2.0 by choosing the relevant tab.
How can we save issuer resources by streamlining the industry's standard, yet convoluted, process in debt management?
Cass did an incredible job leading the design... overall, it's really impressive to see a product like this developed by a team that doesn't have years of experience working with debt databases like I do.
“I can’t wait to get my hands on this…it’s the first time I’ve seen our data laid out this way!”
“How can I get access to this? Can I go tell my Issuers to sign up for BondLink today, just for this!”
The municipal bond industry is convoluted, with antiquated processes and methods, resulting in inefficiency worth an estimated ~$3 billion in annual waste. This cost burden falls on the issuers, which in turn falls on the issuers' communities and constituencies via underfunded infrastructure and/or higher taxes for citizens.
An intuitively designed product suite with features and functionality that streamlines the process of important muni bond issuance tasks—such as communication, disclosure, marketing, investor relations, and debt management—and provides standalone value to the primary participants in that process.
Debt Data is a first-of-its-kind tool within BondLink’s Issuer Portal, providing issuers and financial advisors with a consolidated view of historical bond data to streamline debt analysis and support informed decision-making. This innovative product strengthens BondLink’s position as a key data source in the municipal bond market.
The problem is twofold. Firstly, issuers don't really have the opportunity to look at their outstanding debt holistically, but other participants in the market can. It's not an equal distribution of information. Secondly, an enormous pain point is that issuers’ data is everywhere, therefore it's hard to find, hard to rectify discrepancies, and hard to trust.
Empowering issuers with a better understanding of their financial portfolio will drive more effective Investor relations because everything associated with their debt portfolio is accessible in one platform.
The goal of Debt Data is to corral issuers' data on outstanding debt and aggregate it in a central place that is automated, accessible, accurate, and easy to understand.
We will know we are successful when at least 50% of our issuer-customers opt into the feature.
I’m the Assistant Treasurer for the City of Milwaukee.
I’m using BondLink to manage and/or create everything in preparation for my upcoming issuances like roadshows, POS/OS, IR efforts, and compliance. However, I can’t kick off (or even seriously begin considering) this process until my Advisor mocks up a few issuance scenarios using their proprietary debt structuring tools because I don’t have access to the resources, tools, and data needed to plot my outstanding debt. This not only delays my pre-sale process, but it keeps me beholden to my Advisor for simple, ad-hoc planning conversations internally.
I need BondLink to automatically visualize my outstanding debt so that I can do ad-hoc planning and/or pre-planning for potential issuances without needing to involve my Advisor in every conversation.
I am the new Advisor for The Commonwealth of Virginia.
I am helping The Commonwealth plan for an issuance next quarter. I know how much they want to raise but to understand the structure and volume of their debt outstanding, I’m having to search through their CAFRs and past OS’s. This process is extremely time-consuming and prone to human error.
Since The Commonwealth uses BondLink as their One-stop Shop for Munis, I need BondLink to provide a better way for me to interpret, report on, and visualize their outstanding debt data.
We spoke with issuers, financial advisors, and product managers in munis, learning that their debt management methods lacked standardization, relying on a mix of manual and software-based approaches. Typically, issuers contracted with financial advisors who provided them with their debt data.
Manual methods included whiteboards, paper, sticky notes (seriously) and spreadsheet programs like Excel, Sheets, or Access Database. They provided only static snapshots of issuer debt for future planning. Financial advisors would input each data point, creating colorful, table-based summaries with some custom details. These were not living documents, so any changes required a full revision and redistribution.
I did comparative analysis with some muni and non-muni programs that were similar. Familiarity and comfort is important to our users. It was important to understand the products in the industry to understand muni participants' expectations, so I know how to introduce modernity, where to maintain convention, and what to chuck completely.
Everybody Is Confused: The anatomy of a bond issuance is complicated. Yes, the main player is the issuer, however, there are many players involved in the process from inception to issuance day (and beyond). Not only is it complicated to the outside eye, but it’s even an arduous process to those internal stakeholders.
Historical Data Is a Mess: There are multiple platforms that have bits and pieces of data, but not quite the whole picture. On top of that, there are discrepancies among each data source. And on top of that, sometimes issuers engage in private debt issuances that aren’t logged into public databases. When there are inconsistencies or missing data in the tool, it renders the entire tool useless.
The only platform with accurate data is Intercontinental Exchange® (ICE), and we signed a partnership with them in 2020.
After Discovery, we (product and design) came up with the feature requirements.
As a user I need the ability to...
As a user I would like the ability to...
Figuring out how to structure the product was one of the most intensive parts of the whole project. We had many calls with our CEO and Director of Issuer Success, two former issuers for Massachusetts and California. They gave me the perfect metaphor, legos.
Thinking of each piece as a lego clicked for me. It helped me find the prime visualization: column charts. If each bond was a lego, we could stack them vertically and horizontally to show different things.
We looked back on our comparative analysis to determine the right structure. The way to look into debt was issuer > series > issuance > bond. Once we understood that flow, we had to see how that convention and standard made sense for us. We wanted the top level to be the overall debt outstanding. From there, we went through a few iterations to land on the right structure and information we wanted to give to our issuers.
We wanted to stand out among other products for our usability and design, incorporating enough room for dozens of series, big, pretty charts with ample white space, WCAG approved text size, and historical data.
We knew the crux of the product was data visualization and flexibility, so we started with column charts and filters that dynamically render the chart and the table. Whatever the chart was showing, then, so too would the bottom table. Research showed that analysis in different views at each level of the debt structure, drilling down from the top, was valuable.
Yearly: Yearly view would show the distribution of debt over time year over year, each year being a column broken down into principal and interest.
Monthly: Monthly view would take a single year and zoom into it, where you could see the distribution of debt month by month.
Series: This view was the same as yearly, just with the added data points of series within each year.
There were countless tweaks and rounds of iteration.
Finally, we refined the design for Debt Profile, the visualizations part of the product, to where the usability tests were receiving no negative feedback.
Once we had the visualizations down, we were able to build the data management side of the product. In Data Management, a user could manually add debt, hide series, and view the raw numbers that were powering the visualizations.
The Debt Data journey is one I’m really proud of, from the first time I heard about the project in 2018, to getting the resources to work on it in 2020, to MVP launch in 2021 and beyond.
The following year, it won Best Data Initiative of the Year at the 2022 US Fintech Awards.
As more customers started using Debt Data, the performance metrics rolling in showed that it was a massive success. It was the top used optional offering in the BondLink product suite, with 80% of our users opting in to use us for their debt management solution.
Explore the prototype to see the full MVP in action.
With more usage came more ideas and feedback for ways to enhance Debt Data. We identified key areas of improvement and started the Debt Data 2.0 journey. To see where the product currently stands and how we got to the present, read my case study on 2.0.
Scroll back up to the tabs to continue to the 2.0 case study
How might we develop the tool further to support complex scenarios and better serve our largest customers?
2022 Winner at the US Fintech Awards
BondLink has won a spot on the annual GovTech 100 list consecutively since the design team started in 2018
unique pageviews than benchmark metrics
utilized tool in our product offerings
in average time spent on page than benchmark metrics
If you need to read about the Debt Data MVP, head on over to that case study in the other tab. Otherwise, here’s the elevator pitch:
"Immediately know your municipal bond data in one trusted view that you can filter and chart for annual planning, issuance preparation, past and upcoming payments analysis, and forecasting. It is easy to get started. Send us a list of your CUSIP-9s, and we’ll plug them into municipal bond market data fed daily from ICE to provide an even deeper understanding of your debt obligations and opportunities."
We launched in 2021, and the following year, Debt Data won Data Initiative of the Year at the US Fintech Awards.
But the MVP was only the start. As a new offering beyond investor relations tools, we saw potential for much more. Research revealed that the tool needed to support more complex scenarios to serve our largest customers.
The MVP gained traction and started to drive interest from prospective revenue-generating partners. However, we received consistent feedback that our largest issuers have complex needs due to their complicated issuances, and the tool did not support that complexity.
With a tool that manages finances, especially monetary amounts in the billions, if it doesn't check all the boxes, it checks none of the boxes.
We hypothesize that the updates will increase adoption and overall UX if we build upon the MVP specifically for Issuers with large and/or complex structures.
I'm proud of the work we did with the MVP because, for most issuers, it did check all their boxes. We conducted ten feedback sessions, going through common task flows to garner feedback on the next steps.
We noticed a pattern: large issuers, like state or capital city issuers with complex, frequent bond sales, faced similar challenges that smaller issuers did not. As our top revenue-generating clients, these large issuers needed quick, tailored solutions.
Our interviews and feedback sessions went through three top use cases:
After the targeted research sessions with large customers, we figured out that we needed to incorporate specific enhancements in a few key areas before Debt Data could work for them:
For issuers, the tool felt fully automated—no more manual data entry or #VALUE! But on our end, it was manual. Our backend team worked–honestly–what looked like miracles to me while coordinating with ICE’s database. To launch quickly, we temporarily took on the task of matching issuer data until we could build a truly automated solution.
The manual process looked like this.
That process was not sustainable. Finding a way to automate it not just for the issuer but for us, too, became the fourth and final key area in our 2.0 enhancements.
Each significant feature had 3-5 requirements for implementation.
Background: Some of our customers are obligors, and some are programs. In our taxonomy, we call them issuers no matter what because every other platform in the industry uses "issuer" as an identity; not every platform breaks them down further to indicate which issuers are obligors. This opaqueness can lead to some issues in the data shown because an obligor issuer doesn’t have a way to separate their programs from each other. For an issuer who is a program, their debt data might include debt from a different program under their obligor.
Problem statement: Every municipal entity contains some nuance in its structure, which makes assigning the debt data in our database to the correct entity laborious and groups unrelated CUSIPs. Currently, the primary way Debt Data organizes and shows debt is by series. We need to provide a new view of the data that shows all the debt under a single CUSIP-6/program, not just by series.
On the platform, we called this CUSIP-6s.
Because it was a paradigm shift, I had to create assets for the team to explain the changes in 2022.
I’m the Debt Director for the City of Charlotte.
I use BondLink’s Debt Data tool to evaluate funding options for upgrading our airport in 2022. Today, my Debt Profile includes all the information I need, but it’s aggregated under the City of Charlotte as a single issuing entity.
I need BondLink to provide a way for me to segment out my airport fund in my Debt Profile so that I can complete my analysis.
Background: Every issuing entity uses bond sale proceeds for projects. No database tracks the usage of those bond sale proceeds. However, in our research, we received multiple instances of the same feedback—active users want to be able to segment their debt in custom ways, particularly for tracking projects and fund usage.
Problem statement: Issuers organize around different levels and categories that are not baked into the financial data. We need to allow our users to manually group CUSIPs so they can look at their debt profiles in specific views and have more control.
On the platform, we called this feature Tags.
I’m the financial officer for the University of Massachusetts.
I use BondLink’s Debt Data tool to track our outstanding debt and assess where we allocated funds. Debt management solutions do not organize debt by project allocation.
I need BondLink to provide a way for me to use custom categories to analyze our debt in different ways.
Background: As overall market conditions changed, issuer behavior changed. In 2021 and earlier, interest rates were low, so issuers wanted to refinance old debt that had higher interest payments via bond sales called refundings. In refunding sales, the issuer must put their funds in escrow, where a trustee handles the investor disbursement. To issuers, as soon as their money goes into escrow, that debt is off their books. To investors and the market, escrowed funds are still outstanding. In Debt Data, we don't have that nuance in the data. Users needed to be able to follow the trail of funds.
Problem statement: Issuers and the market are at odds with the definition of an escrowed CUSIP-9 (due to refunding sale types). At this point, our Debt Profile sides with the market’s definition—leading to issuer user confusion and unhappiness. We need to identify and show the user which CUSIPs were involved in any complex transactions without corrupting the underlying data we receive from our vendors.
On the platform, we called this Refundings & Money in Escrow.
Because my team found my info sheets helpful, I continued to create them to explain any significant changes, including complex bond issuances.
I’m the Assistant Director of Finance for the State of Arkansas, so I’m responsible for overseeing and servicing all of our outstanding municipal debt.
Currently, I enjoy using BondLink’s Debt Profile for on-demand analysis, investigation, and insights. However, I’ve led eight Refunding deals this year, and all of those appear to be double-counting which completely breaks my analysis.
I need BondLink to handle escrowed CUSIP-9s in a way that makes better sense for my uses without compromising the underlying raw data.
Background & problem statement: Issuers need historical data to help with disclosure reporting, turnover/succession planning, and relative performance analysis. With access and ownership of their entire debt history, issuers could report more, plan more effectively, and analyze deeper.
On the platform, we called this Historicals.
I’m the Chief Financial Strategist for New Mexico Finance Authority.
I use BondLink’s Debt Data tool to generate year-end disclosure reports. My report requires at least 10 years of past issuance information. Currently, my Debt Data doesn’t show any historical data, so I can't produce my reports using BondLink exclusively.
I want BondLink to complete my Debt Data with our entire history so that I can produce my reports more efficiently and discontinue my expensive subscription with the competitor.
Background: Our process for importing new CUSIPs was time-intensive and inefficient. It took resources from our team and didn't give the user any insight into or control of the data. With an engineering push, we could figure out a way to automate this process, take the task of issuers needing to send in their CUSIPs off their shoulders, and remove the need to match data manually.
Problem statement: Our automated tool still involves manual labor when adding new debt to the profile, with users sending new CUSIPs. We need to develop an automated, user-controlled review mechanism that flips the process and sends new data to the user for acceptance or rejection.
On the platform, we called this Data Review.
I’m a customer success representative for many issuers with limited resources on their finance teams. They love our Debt Data tool because it relieves them of a tedious task.
I have a hard time organizing the data needed to power their debt data because they don't have the people to produce all the CUSIPs and keep track of their outstanding debt changes. When I finally get ahold of the CUSIPs, if there are any issues, rectifying them will take a long time and add more work for the issuers instead of helping them.
I need our tech team to create a solution that automates wrangling all their CUSIPs for them.
I'm the Treasurer for the City of Boston.
I use BondLink's Debt Data tool to plan for each bond sale. We have frequent bond sales and therefore, many different CUSIPs and fluctuations to our outstanding debt. Right now, I don't see when new CUSIPs are added to my Debt Data or have control over the data.
I need BondLink to grant me access to the new CUSIPs so that I can review what goes into the profile.
We had to determine where these upgrades would live in the product. The portal where the Debt Data product lived was called the Issuer Portal.
In Debt Data MVP, there were three sections: Debt Profile, Data Management, and Settings. New pages were in purple boxes.
For tags and data review, budgeting tools use workflows that we could apply to our use cases.
To analyze trends in how someone is spending, personal finance apps allow users to put each transaction under a category. This is a flow that would work for tags.
To refine activity and reconcile any duplicates or errors, a user must connect the tool to their bank account, so the transactions appear automatically in the tool. This could work for data review.
Many of the enhancements were in-page—component additions or changes. However, we needed to figure out where to fit in the more extensive features, such as tags, data review, and programs/CUSIP-6s.
Type of design change: new tab, new table, new elements, terminology changes
The Data Management section was a table with each row being a series. We had to give them the choice to view debt by program/CUSIP-6, so we put the page under a tab called series and added a new one with the debt organized by CUSIP-6.
Historical debt, including matured CUSIPs, was added to the page, denoted by a medium grey cell to distinguish it from the light grey cells denoting hidden debt.
Type of design change: new tabs, new elements, terminology changes
The Series Data pages for individual series were one page before. After the enhancements, we separated the information into two tabs. We created a secondary navigation with links to the series visualizations in the Debt Profile and a new 2.0 page, the history of actions logged regarding this series.
Type of design change: new page, new table, new form
The settings page was a fast-follow addition between the MVP and official 2.0 releases. It was previously in a modal accessible from a button on the All Debt Data page under the Data Management section. We received feedback that users needed options regarding their time settings. Each issuer chooses a unique timeframe, so a bond sale that happened in 2023 to one issuer may be a 2024 sale if a different issuer had it.
We also put the Tags section under Settings. There would also be a tag summary page where a user could view all the debt categorized together under different tags.
Type of design change: multiple new pages and forms, component additions to other existing pages
The workflow for reviewing data included many changes and new items. The entries to the Data Review flow were in a few different places:
Annotations are screenshots from the actual specs handed off to engineering.
Although the updates are combined in this case study, we released them in phases, achieving milestones that ultimately made this BondLink’s most used feature.
