Davide Martucci (Next Gate Tech): Redefining Data Management for Financial Services
In the financial sector, clean and harmonized data sets are far from being an industry standard. That is why in 2019, Next Gate Tech was founded, with the promise of harmonizing and enriching data coming from different sources in a fully automated manner.
Can you present your company in a few words?
Next Gate Tech is a fintech focusing on developing new technologies for the fund and asset management industry operations. Our SaaS platform provides extensive data harmonization and analytics capabilities, allowing our clients to obtain meaningful insights. Next Gate Tech has today 30+ employees in our Luxembourg and London offices and is composed of tech talents such as quantitative developers, software engineers, data scientists and cybersecurity specialists, amongst others, working alongside other profiles coming from the asset management and fund industries, including from portfolio management, risk management, depositary and fund administration areas. It is the synergy between the technology and industry experience in our teams which allows Next Gate Tech to create an efficient platform for our clients. We know the challenges they face because we lived these same pain points ourselves earlier in our careers.
“We believe that the collection, harmonization and storage of data should be fully automated nowadays.”
What are the main trends that influence your activity?
On the fund industry side, we see more and more companies willing to embrace innovation around “exception-based” processes. Where exceptions have historically just been an end production number requiring manual investigation as to origin and cause, machine learning technology is now a key enabler for exception pre-classification and providing one central point of access to all relevant background data to that exception. Increasing fee pressures, a complex regulatory environment and a more competitive landscape are important drivers for the optimization of resource allocation within the most critical operational processes. Machine learning processes are at the core of Next Gate Tech since the very beginning. We use different models and analytics approaches that we apply across the entire flow; from collecting, validating, enriching, harmonizing and delivering data into an easy-to-read format to the generation of insights and analytics.
How are your customers' needs evolving?
While industry needs have been evolving throughout the past decade, the technologies used within the fund industry operations are, for the most part, still legacy technologies dating back to the beginning of the 2000s or even before. Our customers have to deal with the ever-increasing size of data sets, which can then have a detrimental impact on system performance and are time consuming to maintain. Our customers are looking for new approaches or new technologies to automate their day-to-day tasks at the same time as managing the risks associated with those tasks. We believe that the collection, harmonization and storage of data should be fully automated nowadays. The fund industry needs solutions that can read and understand patterns to be able to face the “unknowns”. Many operations within the financial sector still require a significant amount of manual intervention. We are concentrating on developing a technology that manages clean and validated data for our customers, enabling them to be able to focus on their core business.