2 min read

Delivering a bespoke, onsite data strategy for a global investment firm

Varun Kale 18 December, 2023

FINANCIAL SERVICES

How QuantSpark helped an ESG focused global investment management firm create value via an on site Data Strategy Secondment.

 

Executive summary

With a dedicated onsite presence two to three days a week, QuantSpark directly engaged with on-the-ground client teams. This setup allowed QuantSpark to understand and react to the clients needs, developing one off pieces of analysis, strategic plans and roadmaps specifically tailored to the client.

QuantSpark played a critical role in improving the client's data analysis capabilities, delivering detailed analytics, building bespoke dashboards, and implementing custom Excel integrations, adding considerable value and streamlining the decision-making process.

QuantSpark worked directly with the Trading and Research teams to understand their data needs, allowing for faster decision making, and saving valuable employee time.

 

 

The challenge: Efficiently disseminating real-time data

QuantSpark delivered a bespoke, onsite data strategy service to help a global investment management focused on Environmental, Social, and Governance (ESG) factors. QuantSpark had previously worked with the client to implement a robust data collection system, utilising Python to scrape Excel models, storing and structuring the data in a Redshift Data Warehouse. This created a new challenge for the client: how best to use the wealth of data now readily available to them?

The client lacked in-house data specialist capability but knew that a deep understanding of their data landscape was also pivotal to delivering fit for purpose solutions. This lack of expertise made it challenging to disseminate real-time data efficiently to the Investment Team, causing a lag in exploiting the full potential of their available data.

QuantSpark’s data capability, combined with their deep industry knowledge, provided the perfect combination to support.

 

How QuantSpark’s expertise was leveraged

Through Power BI data flows, QuantSpark developed dynamic Excel templates and custom visuals for the client, granting them real time data access to their portfolio and company level data. This unlocked their ingenuity in performing custom analyses and creating bespoke visualisations, thus encouraging innovative, data-driven decision making.

Beyond basic data access, QuantSpark took a step further to amalgamate diverse data sources into comprehensive Power BI dashboards. These dashboards not only incorporated internal analytics and company models but were also enriched with real-time pricing data from Bloomberg. The result was a complete, always up-to-date view of data that helped the client make smart, timely decisions based on solid data.

QuantSpark carried out in-depth data analyses, which were then converted into clear, insightful reports and presentations. Our client leveraged these resources for both internal discussions and external conferences, thereby enhancing transparency and strengthening client relationships.

The deep understanding we gained from being embedded in the client’s business also allowed us to scope out and identify future value-add opportunities that would save client time and enhance their investment decision-making capabilities.

We proposed innovative initiatives such as the automation of ESG data pipelines from multiple providers such as SBTi and the exploration of advanced machine learning opportunities, setting the stage for long-term improvements and evolutions in their operations.The Impact: Clawing back suboptimal prices.

 

Impact

QuantSpark's regular on-site presence enabled an open line of communication with the client, making it easily accessible for any unique custom analysis or reporting requests they had. This was essential in catering seamlessly to their specific needs.

Our strategic planning and roadmaps paved the way for increased efficiency, while our advanced analytics, bespoke dashboards, and Excel integrations helped streamline their data management and decision-making processes.