On May 3-4, FINOS will run a Hackathon event, hosted by BMO (Times Square, New York City), to collaborate and innovate in solving real life problems within the financial space; the event is now open to all developers!
Here are the first three use cases for the hackathon - a full list of challenges is being built collaboratively by FINOS Members on Github!
It's a common problem that discretionary trades want to be able to produce charts using data from a variety of sources, there are various dealer tools that offer this (Barclays BARX, Goldman Sachs PlotTool, JPMorgan DataQuery) but each will only have the data available within the respective bank. In addition most consumers of these tools will have their own datasets, plus those from market data providers. If you want to pull various pieces of data together this typically requires establishing a market data team to source data from the various vendors into a bespoke platform. If it were possible for a user to do this on the desktop then they would be creating a chart based on data directly accessed from the golden source systems. More Details
Facilitate communications between Buy-side and Sell-side by initiating a message to an existing chat group from an order in your order blotter. Use FDC3 intents to initiate a chat from an order on a blotter. Create a service to transform the “broker” or “instrument” on blotter to correct the chat name for that user. Potential to leverage Legend project to store and manage translations. More Details
By using LCR, Morphir can quickly identify and extract data from large datasets without needing to traverse the entire dataset for each pattern evaluation. This can result in significant performance improvements, especially when dealing with complex structures that have many potential matches. More Details
| FDC3 Data Mesh for Charting |
It's a common problem that discretionary trades want to be able to produce charts using data from a variety of sources, there are various dealer tools that offer this (Barclays BARX, Goldman Sachs PlotTool, JPMorgan DataQuery) but each will only have the data available within the respective bank. In addition most consumers of these tools will have their own datasets, plus those from market data providers. If you want to pull various pieces of data together this typically requires establishing a market data team to source data from the various vendors into a bespoke platform. If it were possible for a user to do this on the desktop then they would be creating a chart based on data directly accessed from the golden source systems. More Details |
| Enhance Chat Integration with Contextual Transformation on FDC3 |
Facilitate communications between Buy-side and Sell-side by initiating a message to an existing chat group from an order in your order blotter. Use FDC3 intents to initiate a chat from an order on a blotter. Create a service to transform the “broker” or “instrument” on blotter to correct the chat name for that user. Potential to leverage Legend project to store and manage translations. More Details |
| LCR on Morphir |
By using LCR, Morphir can quickly identify and extract data from large datasets without needing to traverse the entire dataset for each pattern evaluation. This can result in significant performance improvements, especially when dealing with complex structures that have many potential matches. More Details |
| Capture Information from Chats to Enhance Data that is Not Captured |
A lot of missed opportunities (missed tickets/trades) are kept within chats etc, if we start capturing these and tie them to certain securities or sectors, we can use this additional information to derive more accurate hit ratios on clients and securities. More Details |
| ESMA Templates Transformations for Non-EU Originators / Providers |
This is going to be even more relevant for non-agency transactions, which rely more on the EU investors base. The problem is that non-agency transactions come with custom loan-level data templates (i.e. every bank has its own loan-level data "standard"). Each of them will have to translate their custom templates to the ESMA one and apply rule checks to make sure that the "transformation" worked well (we can provide an example of rule checks that every US bank will have to implement eventually). More Details |
Ask a question or drop a comment on the use cases on our community GitHub!
Ask a question or drop a comment on the use cases on our community GitHub!
