Discover how Raw Knowledge drove a 70% reduction in data extraction times and opened new revenue streams using their innovative Managed Smart Data Platform to support the automated delivery of excess reportable income (ERI) data.
Raw Knowledge’s challenge with ERI data
At Raw Knowledge, we have been sourcing, processing, and delivering high-quality excess reportable income (ERI) data since the very start of the offshore reporting funds regime.
We provide our clients with a full dataset for tax reporting, including fields rarely provided on a fund manager’s original documentation. The extraction, ingestion and processing of this data had been a completely manual process for our team, requiring large amounts of time-consuming validation.
We required the equivalent of three members of staff, working at full capacity, to complete the processes with the highest degree of accuracy possible. Further, due to the complex and bespoke nature of the data requested by our clients, these processes were becoming increasingly dependent on team members with the highest level of data handling expertise.
It was important to us that we avoided any dependencies on specific people, but we knew that to have a truly sustainable solution for our data delivery, we could not pour more money into recruitment or more intense training for our existing staff.
Instead, we knew that we needed a solution that would eliminate these bottlenecks and streamline the way we extracted, processed, and verified our data. We also wanted to ensure that our processes would be scalable and sustainable to accommodate our rapidly growing customer base.
Building an innovative new solution
We are lucky at Raw Knowledge to form part of the wider Industrial Thought Ltd Group. As part of this, we have access to our parent company, Industrial Thought’s, product development and technology innovation hub, Thought Train.
Thought Train had been working quietly behind the scenes on a data platform that was primarily focused on the extraction, ingestion and processing stage of data management. It felt like a natural fit to combine forces with Thought Train to see how we could extend this platform to suit our needs around ERI data, as well as develop the data delivery side of the platform.
The key development needed was to extend the front-end of the platform, expanding its ability to scrape and then validate the ingested data. As a lot of Raw Knowledge’s data came from PDFs, it was important that the platform had the ability to handle unstructured and semi-structured data formats with ease.
The data management platform, which would eventually be named the Managed Smart Data Platform, was built using a low-code/no-code approach and sat on metadata-driven lakehouse architecture. This meant that adding datasets was straightforward and seamless, allowing us to begin testing the platform almost immediately.
Instant results with the Managed Smart Data Platform
The use of the Managed Smart Data Platform in the delivery process of Raw Knowledge’s ERI data officially began at the end of 2024. In just six short months it delivered profound operational improvements, cost-savings across the business, and helped scale our data capabilities significantly.
In our early stages of use, we witnessed a 70% reduction in the time taken to extract data and produced a 90% accuracy rate once this data was ingested. This helped to support an immediate 60% reduction in manual reconciliation activity, significantly improving our team’s efficiency, speeding up data delivery times for our clients and resulting in cost-savings across the business.
Human involvement remains a fundamental part of our current operational processes as we believe this collaborative approach, integrating human engagement with machine learning, enhances the accuracy and reliability of our platform.
The efficiency gains made as a result of the Managed Smart Data Platform meant our team could be redeployed to higher-value tasks such as client relationship management and customer service delivery. They also felt empowered to be more proactive with our clients.
In the past, we had to primarily focus our attention on responding to the needs of clients as they arose. Now, our team can take the time to fully consider how a client’s data needs may evolve over time and adapt our service accordingly to ensure they remain fully supported.
Bitesize Case Study: Fast-Tracking Data Correction with the Managed Smart Data Platform
The challenge: A fund manager had republished several years’ worth of ERI data, correcting errors that had previously appeared in their reporting. Raw Knowledge’s datasets needed to be updated and impacted clients needed to be informed.
Before the Managed Smart Data Platform: Correcting our datasets would have taken around four weeks. The Raw Knowledge team would have had to drop everything to cross-reference the data, update our datasets, and send the updated information to the impacted clients. This would’ve been an entirely manual process.
With the Managed Smart Data Platform: Correcting our datasets, triple-checking its accuracy and sending the updated information to the impacted clients would now take less than a day thanks to the automated processes facilitated by our platform.
Facilitating long-term transformation
The Managed Smart Data Platform monitors corrections, adjustments and activities made to datasets by our team, supporting continuous business process improvement. This technology feedback loop and the deployment of Generative AI and AI agents, along with the low-code/no-code, metadata driven platform architecture, means these improvements to processing can quickly be deployed and assessed.
As a result, we foresee our data extraction, ingestion and processing times reducing further as the platform becomes more embedded in our business.
The platform’s business impact extends far beyond the immediate efficiency gains seen across our ERI data processes, however. It was also essential in catalysing our evolution as a business.
We have, since our beginnings as part of our sister company, Financial Software Ltd, been a business focused on providing financial data to support UK tax reporting, particularly ERI reporting. The introduction of the Managed Smart Data platform has changed that, empowering us to look at diversifying across the data market or extending beyond the financial services industry entirely.
What’s next for the Managed Smart Data Platform?
We’ve seen the value the Managed Smart Data Platform is driving in our business. Now we want to work with a forward-thinking business to see what this pioneering platform can do for others. We want to work with you to understand your pain points around data management and adapt our platform to meet your unique needs.
Together we would draw up a blueprint for what your Managed Smart Data Platform could look like: which of our core capabilities would best serve your current and future data management needs, how you’d like your final data to be presented and every step in between.
Once you’re happy, we’d get to work.
There’d be regular check-ins, open communication, and a continuous refinement process so what we build fits your business and its requirements exactly.
When your tailored platform is live and fully integrated into your systems, our collaboration won’t end there.
We want to stay in contact to understand how your business is evolving, recommend ways you can keep your data compliant with the latest regulation, and new ways our platform can keep driving your business forward.
The global data landscape is growing in complexity and volume every day. Failure to keep pace with this evolution could hold your business back. Ensure your firm maintains a competitive advantage by collaborating with us as we advance our future-proof, trusted source platform.
Join us as we lead the innovation on which the financial services industry of the future is built.
