How an asset management firm uses Nexla to empower its analysts and reduce time to support custodian requirements
The finance asset management firm needs to send daily account level data to the custodians. There is a high degree of data heterogeneity across custodians around what data elements are needed (tax lots should be sent as a separate file versus attached to positions etc.), what format the data needs to be in (JSON, XML, CSV), and the destination type where the data needs to be delivered (FTP Servers, S3 buckets, REST/SOAP API). Before using Nexla, sending data to a new custodian took 2 months of engineering and analyst time in order to first understand the custodian specification and then to code and test to the specification. Custodians also change their specification from time-to-time, either to enhance the reconciliation process or to meet changing regulations. This meant the firm needed two to three weeks to code and test changes to the reconciliation process.
Using Nexla’s Data Operations platform, the firm was able to reduce the time to send data to a new custodian from 2 months to 3 days. Enhancements to existing custodian could be done by a non-engineer in less than a day.
An analyst signed on to Nexla platform and pointed it to the FTP folders containing the firm data. Nexla automatically detected schemas from different files for trades, positions, tax lots, securities. and corporate actions. The analyst was able to use Nexla’s simple yet powerful schema editor to join different datasets, perform lookups against master data, and mathematical operations to create a recon view of the firm’s data. This dataset was then filtered by custodian id and shared on Nexla with other firm-wide analysts working with specific custodians. Each of the custodian analysts loaded the shared dataset, transformed it to custodian specification, and then sent data to the custodian destination (FTP, API, S3) using Nexla’s built-in connectors.
- Analysts reduced debugging time substantially as Nexla was able to provide record level data lineage for any records needed further investigation
- Analysts were able to run as-of-date reconciliation using an old version of transform
- Different analysts were able to collaborate on the platform, passing the baton to the respective team member in charge of each stage of the workflow
- Enhancements to existing recon processed needed minimal engineering effort
- Schemas and fields for datasets were versioned in Nexla Data dictionary
- Transformation logic was versioned on Nexla with ability to roll back/forward
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