Fixed Income Data & Credit Analytics Platform
#BONDMARKETS #FINTECH #FINANCIALMARKETS #SIMPLIFIEDMARKETS
What Is Synch?
Synch offers the most advanced, efficient and streamlined fixed income data and credit analytics to finance professionals
Lack of Digestible Analytics
Some large corporations, Investment funds and banks can afford industry-standard terminals, but their fees are very high. Besides, a lot of unnecessary information is also provided. The quality of the solution is good but it remains costly and has a long learning curve.
For smaller players who cannot pay the fee for a terminal, the information comes with a delay and is diluted or interpreted by the data providers. These smaller players have to navigate through multiple channels to get valuable information.
A Curated Ecosystem for Bond Professionals
Synch is a single, curated ecosystem for bond professionals to source and analyse bonds with relevant, reliable and up-to-date data, in a cost-effective manner.
Besides Bond information and News, thanks to partnerships with ICE, FactSet and DowJones, Synch provides its users with comprehensive consistent data, specialised for fixed income trades in a timely and costly manner.
Key Challenges We Faced on the Product and Tech Sides
UX for Massive Sets of Data
The navigation is user-centric and made to fit the analysis process. This results in a fast learning curve and improved clarity for the user. Synch also presents the top KPIs first, in a condensed light format for quick appreciation by the user. In a deeper dive, we allow users to drill down into an exhaustive set of data in case analysis is required.
Connecting Multiple Data Points From Different Suppliers
When connecting to multiple data vendors, each vendor delivers its data in a different structure. The challenge is to have a deep vision of each vendor’s data structure and connect each data point in a way that’s truthful and efficient to the ETL process.
With a combination of three infrastructure choices, we designed a system able to easily integrate more data sources and digest bigger datasets if needed.
- Microservice stack – The system consumes from each data source thanks to a modular component that can be quickly configured to various data sources and exchange protocols. Horizontal scaling consists of copying and configuring this module to the new source making it easy to integrate.
- Queues – To accommodate having several and potentially conflicting data sources, the system uses a queue to manage chronologically conflicting tasks. It ensures that no information is left aside and increases the reliability of the data ingestion flow.
How We Did It
We focused on the business vision and created a comprehensive brief for the project by gathering all the research on the market, competitor benchmarks and any other necessary information. Then we met with the client in an immersive session to craft a value proposition and set the main assumptions to prove. Finally, we created the ultimate list of user stories and features necessary to prove those main assumptions within the MVP.
Product Rationale and Tech Scope
After an immersive session with all the stakeholders, we had all the information we needed to create the ultimate list of User Stories and features necessary to prove the main assumptions in a Proof of Concept (POC). Our experts in Product, UX/UI and Tech Architecture focused on finding the answers to all of the questions raised throughout the scope preparation. On the tech side we elaborated a memorandum tackling our suggested approaches for tech stack selection, database technology and orchestration. Together with Bocconi University and AlixPartners we started defining the useful datasets and the algorithm behind the lending decisions.
We developed a non-functional prototype to simulate user interaction. The experience of using the clickable prototype was very much like the final product itself, this was the adequate phase to test the information architecture, the UX and most importantly to present all involved counterparts a concrete outcome.
With the decisions closed in the previous steps, we went on developing the product through agile cycles.
Once the product went live we started to gather end-user feedback and improve the product. New iterations were made in parallel with new features so that the end-user has the best experience possible.
Case Study PDF
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Synch provides a 3D vision of the Bond market, being that, information about the bond itself, information about the issuer and news. By connecting these three dimensions the user can quickly and securely complete contextual analyses of a bond or an issuer.
Synch has embedded a number of smart algorithms across the system. Many are invisible as they are used to deliver some powerful end points to the user experience. Others are user-enabled such as the automatic comparison tool which is able to scour the market for similar bonds to the one being analysed.
With watchlists, each user has a powerful way to monitor and take decisions around any subset of securities of interest giving a powerful point of reference to the user. The watchlist can be generated static and dynamically. In addition, comparative analysis can also be performed relative to a watchlist in a single click, dramatically increasing the validity and consistency of the analysis process.
Using powerful filters and saving those filters lets the user easily analyse an investment strategy and see the outcomes of that strategy.
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