ReadBetween

ReadBetween extracts hidden insights from financial communications through advanced analysis of both spoken and written content. The system combines computational linguistics, speech processing and machine learning to identify patterns and anomalies that reveal informational content beyond explicit statements in corporate communications and client interactions.

By examining acoustic properties alongside textual content, ReadBetween detects communication signals that traditional analysis overlooks. This multimodal approach identifies linguistic markers, communication patterns, and potential fraud indicators, providing a more complete assessment of communication dynamics than single-mode analysis.

The technology addresses methodological gaps across financial communication contexts, offering empirical approaches to questions previously handled through subjective interpretation. For investment professionals, the system tracks communication pattern changes over time, potentially revealing shifts in strategic focus or confidence levels before these appear in financial statements. This capability efficiently processes large volumes of corporate communications to identify systematic risk and uncertainty indicators.

ReadBetween also serves as a sophisticated training tool for financial services personnel. During scenario-based exercises, customer service representatives receive evidence-based feedback on their communication effectiveness across phone and digital interactions. The same analytical capabilities enable real-time identification of communication anomalies during client interactions, adding fraud detection security to routine customer communications.

This multi-faceted functionality demonstrates the framework’s versatility across multiple contexts. The technology leverages proprietary methodologies specifically calibrated for financial environments, delivering targeted accuracy that generic communication analysis solutions cannot match.

Dr James Bowden, Co-Founder

Dr James Bowden is a Senior Lecturer in Financial Technology at Strathclyde Business School and co-investigator within the Financial Regulation Innovation Lab (FRIL). His research applies unstructured datasets including text, audio, and images to financial challenges, with publications in leading finance journals and commentary featured in domestic and international media. James co-directs the MSc Financial Technology programme and coordinates research teams developing industry-relevant solutions for regulatory technology. He brings practical market experience from his previous roles as at Russell Investments (now FTSE Russell), and Merrill Lynch.

Professor Mark Cummins, Co-Founder

Mark Cummins is Professor of Financial Technology and Fintech Cluster Lead at Strathclyde Business School. He is a Principal Investigator within the Financial Regulation Innovation Lab (FRIL), fostering collaboration between academia and industry to tackle regulatory challenges through emerging technologies. With experience as a Quantitative Analyst at BP Oil International, Mark bridges academic research and practical industry application. He has secured £4.5 million in funding for innovation projects and specializes in AI applications for finance, including Multimodal Generative AI and quantum finance. His work focuses on developing commercially viable solutions that shape the future of financial services and regulatory technology.