From its simple beginnings of data crunching to now generating autonomously produced content, AI is continuing to transform the digital space. Its newest version, generative AI, has piqued consumer interest with its ability to generate human-like content, images, and audio - setting a precedent for what's technically achievable. This technology opens a new door of possibilities for B2B startups; ones that are creating the algorithms (such as OpenAI) and ones that are implementing them into real-world applications.
Needless to say, AI is already embedded in businesses across multiple industries. However, generative AI introduces a heightened level of personalization, enabling enhanced accuracy and relevancy for output information. For example, I asked my cell phone provider’s chatbot “What’s the difference between iPhone 12 and 14”? The chatbot needed to direct me to an agent to give me a response. With generative AI, the chatbot would’ve been able to ingest all of the relevant information from the site, summarize it, and provide an accurate human-like response - saving time and resources for the company. It's no wonder why major players like Google and Microsoft are working hard to capitalize on generative AI’s potential. Accordingly, Google has released its chatbot Bard while Microsoft is reigniting its search engine, Bing.
We are still in the early days of expanding generative AI to enterprise use cases, mainly because the margin of error, albeit low, is still considered risky for businesses. However, our team at NVP is particularly excited for the potential use cases within our thematic focus in financial services - particularly accounting, fraud detection, and lending.
The process of accounting, especially handling accounts payable and receivable, can be a daunting task. But with the implementation of generative AI, businesses can automate important but repetitive tasks such as invoice creation as well as invoice ingestion + processing. Generative AI can learn from vast amounts of data, allowing it to efficiently handle tasks that were once done manually including summarization. This, in turn, saves businesses valuable time and resources while improving the overall efficiency and accuracy of their financial operations.
Financial criminals have become more innovative in their techniques, increasing the need for fraud detection solutions. These solutions identify potential issues by monitoring customer transactions for suspicious behaviors. Generative AI can revolutionize fraud detection with its forward-thinking ability to forecast potential scenarios. Its capacity for synthetic simulation gives it heightened vigilance and precision when uncovering fraudulent behavior.
The emergence of alternative data has enhanced credit models, allowing small businesses to access lending products that may have previously been out of reach. Generative AI can take the underwriting process a step further by leveraging non-traditional historical and real-time data points to better assess a company's financial health - providing unprecedented levels of loan eligibility determination speed and accuracy.
Generative AI is on the horizon and poised to make a major impact on business operations. With regulated businesses such as financial institutions having to grapple with the challenges that come with AI - compliance, risk management, and data privacy- new generative AI technology solutions would need to incorporate proprietary frameworks that offset potential risks.
As we continue to explore the possibilities that generative AI offers, we look forward to seeing the use cases that are uncovered. If you are building or interested in the space, reach out to Kiswana@Newark.VC to connect!