InScope: Revolutionizing Financial Reporting with AI

InScope: Revolutionizing Financial Reporting with Machine Learning

In 2023, Mary Antony and Kelsey Gootnick founded InScope, a San Francisco-based startup that leverages machine learning and large language models to transform financial reporting and auditing processes. The company's beta launch earlier this year marked a pivotal moment in automating GAAP and non-GAAP reporting for mid-market and enterprise clients, streamlining traditionally time-consuming and error-prone operations. InScope's initial product release focuses on automating cash flow statements, simplifying what CEO Antony describes as a "sudoku puzzle" into an effortless, accurate, and reliable process. With five existing customers and six more in the onboarding phase, InScope aims to expand its customer base and revenue tenfold by the end of the year. This growth trajectory has garnered $4.3 million in seed funding from prominent investors such as Lightspeed Venture Partners and Better Tomorrow Ventures, positioning InScope to broaden its product capabilities and customer reach.

Key Takeaways

• InScope, co-founded by Mary Antony and Kelsey Gootnick, utilizes machine learning for financial reporting and auditing purposes, with a focus on streamlining GAAP and non-GAAP reporting for mid-market and enterprise clients.
• The startup's automation of GAAP and non-GAAP reporting, particularly cash flow statements, enhances accuracy and reliability, marking a significant shift in financial reporting processes.
• InScope targets private companies, distinguishing itself from competitors such as Workiva, which predominantly serve public companies.
• The company has secured $4.3 million in seed funding from investors including Lightspeed Venture Partners and Better Tomorrow Ventures, highlighting investor confidence in the company's potential.
• InScope aims to elevate its customer base to 50 companies and bolster its AI capabilities by the year-end.

Analysis

InScope's pioneering use of machine learning in financial reporting has the potential to revolutionize traditional auditing practices, ultimately benefiting mid-market and enterprise clients by minimizing errors and time spent on compliance-related activities. This automation trend may lead to job reallocation within the auditing industry, unlocking opportunities for auditors to focus on higher-value tasks. Notably, renowned investors such as Lightspeed and Better Tomorrow Ventures recognize the scalability of InScope's technology, signaling a probable market expansion and heightened competition within the financial automation sector. In the long run, InScope's success could redefine industry standards, compelling competitors to innovate or face potential obsolescence.

Did You Know?

• GAAP and Non-GAAP Reporting: GAAP, an acronym for Generally Accepted Accounting Principles, represents the standard framework of guidelines for financial accounting. On the other hand, non-GAAP reporting encompasses financial measures that either include or exclude amounts not in congruence with GAAP, providing additional insights into a company's performance.
• Machine Learning in Financial Reporting: This involves the application of algorithms and statistical models to enable computers to enhance their performance in a particular task using data, without explicit instructions, relying on patterns and inference. In financial reporting, machine learning can automate intricate processes, augment accuracy, and reduce human errors.
• Seed Funding: This denotes the initial stage of capital raising for a startup, often allocated for preliminary product development and market testing. Typically sourced from angel investors, venture capital firms, or other investment vehicles, seed funding precedes Series A funding.