I am struggling to integrate data from disparate sources and data quality issues are hindering my analysis.

Asset managers are facing a challenge keeping up with a wide range of data sources. Old technology and new data suppliers intensify this struggle. Even for those operating a data lake there are issues of data quality, timeliness, and governance.

Many smaller firms wait for their desktop terminal to include alternative data. But extracting it for your own workflows is clunky and unreliable. Furthermore, some large data providers accept a less than 90% accuracy rate.

The alternative may seem daunting. Data silos, cloud-based platforms, and Extract, Transform, Load (ETL) workflows are a lot to master. That’s where we can help.

How can I leverage AI and machine learning to automate data processing and extract valuable insights?

We met our first Fintech client 14 years ago. It had manual processes prone to human error and needed to free developers to work with the data not on it. The business was growing, and clients were demanding more services. Data capture and preparation was taking 80% of the time.

We took over the task of automating data integration, detecting anomalies and filling in blanks. This allowed the client to test new and alternative data providers. We even handled conversations with suppliers about data quality. There were a lot of those.

The client’s developers were freed to design and build amazing software that exceeded the expectations of their clients. Growth accelerated as a result.

After establishing trust, we moved into machine learning for pattern recognition, predictive modeling and sentiment analysis. Then the company was bought out.

We started over with the acquiring company. It was much larger and an early adopter of natural language processing. Once again, we built trust by secure and timely data processing before expanding into data visualization and support services. We are proud to serve this client to this day.

Competing with Giants

Is your asset management firm ready to take advantage of the explosion in artificial intelligence tools? Do you want to extract insights from text and documents, use image recognition and advanced analytics for complex data? Is your preference to spend time building tools and processes to prepare the data, or to move straight to the analysis and understanding?

Deloitte identifies four pillars for transformation of asset management using AI. These are generating alpha, enhancing operational efficiency, improving product and content distribution, and managing risk.

Deloitte cites how Blackrock, Man Group and UBS Asset Management adopt the technology. You may be a much smaller firm, but the investment need not be prohibitive.

MSBC Group and RemoraTech have helped fintechs compete with behemoths since 2010. We’ve allowed asset managers to compete since 2017 by working with the largest data platforms. We’d love to boost your competitive advantage starting today.

Please contact me at p.bhavsar@remoratech.io for a no obligation chat about your data management concerns.