In an increasingly data-driven world, the finance departments of many organisations find themselves encumbered by manual processes, despite the availability of advanced technologies designed to alleviate such burdens. According to a survey conducted by HR software provider Paylocity, 38% of finance teams dedicate over a quarter of their work schedules to manual tasks, such as invoice verification. This operational bottleneck has impeded many finance teams from scaling efficiently, as noted by Matthieu Hafemeister, formerly a fintech investor at venture capital firm Andreessen Horowitz.
Hafemeister observes that finance departments often depend on an amalgam of disparate technological solutions patched together within their units, with traditional spreadsheet software like Excel dominating the landscape. Indeed, a significant 82% of finance teams continue to rely on Excel for vital financial planning tasks like budgeting and forecasting. Hafemeister argues that this reliance limits the potential for automation that newer technologies promise.
Having faced these challenges while spearheading growth at fintech entity Jeeves, Hafemeister connected with Ted Michaels, also from Jeeves, to establish a new platform named Concourse. Michaels, who previously held the position of head of finance at Jeeves and is a long-standing friend of Hafemeister, joins him to address these prevalent inefficiencies besetting finance operations.
Concourse is designed to revolutionize financial tasks by integrating seamlessly with existing financial systems, enabling users to analyse data, construct visual representations, and generate complex queries such as "What’s our non-GAAP revenue?" Unlike typical automation tools, Concourse claims to proactively deliver insights that help finance professionals prepare and predict trends, undertaking specific tasks independently rather than merely expediting user-driven operations.
The platform is touted for its distinctive ability to conduct financial workflows of intricate, multi-step operations. For example, Concourse can extract data from corporate dashboards like NetSuite, convert it into CSV format, and input the data into Excel spreadsheets. Hafemeister highlights the platform's utilisation of large language models alongside conventional data analysis techniques to achieve these complex operations.
The incorporation of artificial intelligence (AI) in the finance industry is witnessing notable expansion. According to a survey, 58% of finance teams now employ some form of AI, marking a 21% increase since 2023. Additionally, Grand View Research reports the “AI in fintech” sector is growing annually by 16.5%, valued at $9.45 billion three years prior.
Nevertheless, Concourse faces the challenge of proving its return on investment (ROI) to capture the finance automation market. Gartner confirms that quantifying or merely estimating AI's value remains a primary hurdle for nearly half of organisations pursuing AI adoption. Furthermore, potential concerns about the accuracy of AI outputs and data confidentiality must be addressed. A poll by HR specialist Peninsula revealed that 40% of UK-based executives consider AI errors problematic, compounded by concerns over data privacy.
To mitigate these issues, Concourse implements rigorous fact-checking and validation frameworks to ensure accuracy and security in its AI functions. The platform refrains from using company data in training its AI models without explicit consent, stressing its commitment to privacy and data protection.
Despite these challenges, Concourse has already attracted significant interest and investment. The startup, presently in its beta phase with plans for a broader release next year, has secured $4.7 million in funding from reputable investors, including a16z, Y Combinator, CRV, and Box Group. Initial clients include companies like Instabase and Shef.
Located in New York, Concourse is emphasising product development and team expansion, with a particular focus on bolstering its engineering cohort, consisting currently of six members. The infusion of capital is aimed at enhancing their data integration coverage, developing more robust workflows, and scaling their go-to-market strategy. Hafemeister notes that hiring back-end, machine learning, and AI engineers remains a top priority as the startup advances its technological footprint.
Source: Noah Wire Services