• Expense Classifier & Mortgage Request Automation Tool

    In a bid to enhance customer engagement and streamline internal processes, our client sought to improve their mobile banking app by introducing an accurate expense classification feature. This tool would help users manage their finances more effectively by providing insights into their spending habits.

    Simultaneously, the bank aimed to reduce the time-consuming nature of mortgage request processing. Traditional methods involved extensive manual data entry, leading to delays and decreased customer satisfaction. Automating this process promised significant improvements in efficiency and response times.


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  • Big Data & Machine Learning Solutions for the Asset Management Industry

    In the competitive asset management industry, timely and actionable insights are crucial. Traditional analysts often rely on quarterly reports and standard data sources, which may not suffice in rapidly changing markets. Our client aimed to leverage proprietary data to generate daily analyst-level insights, outpacing competitors and making more informed investment decisions.


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  • Design, Development, and Backtesting of Hedge Fund Trading Strategies

    In the highly competitive hedge fund industry, gaining an edge over the market requires innovation and precision. Our client, a hedge fund managing several hundred million in assets, sought to enhance their trading performance by developing a suite of diverse trading strategies, automating the testing and backtesting processes, and assessing the impact of external market factors. In parallel, the client aimed to co-develop infrastructure that supports both backtesting and live trading with robust data quality controls.


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  • Sustainability Reporting for EU Taxonomy Compliance

    With the rise of regulatory requirements, particularly driven by the EU Taxonomy, corporations are increasingly tasked with providing detailed sustainability reports alongside traditional financial metrics. For our client, a major player in the engineering and manufacturing industry, integrating this sustainability data with existing financial systems proved a complex challenge. The data required for this reporting, much of it managed by Environmental, Health, and Safety (EHS) departments, had to be aligned with financial reporting structures.

    The urgency of the project—due to tight regulatory deadlines—further complicated matters. Developing a custom data capturing system from scratch wasn’t feasible given the time constraints, making rapid, flexible deployment a priority.


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