Scout InsurTech Interview with PredictNow.ai

PredictNow.ai is a financial machine-learning software company. They seek to help businesses improve their human decision-making and existing processes with machine learning predictions and optimizations. Michael Fiedel sat with Founder, Ernie Chan, to learn more about how PredictNow.ai is impacting the industry.

Who are your clients?

Our primary client at the moment is a major U.S. bank. We are collaborating with them to create a synthetic, AI-driven index that supports structured products for the insurance industry. The ultimate end clients for this index include insurance companies who purchase call options tied to the index for their annuity products. We are also engaging with several international banks for applications of AI in trading operations.

What does your product do?

PredictNow.ai leverages machine learning to create dynamic, adaptive models that optimize decision-making. Our core product involves using AI to construct synthetic indices that optimize risk-adjusted returns. These indices serve as the foundation for structured financial products, including those targeted at insurers. Our AI is also being applied to broader business optimization scenarios, such as dynamic pricing in shipping or retail promotional discount optimization, demonstrating cross-industry applicability beyond asset management.

How much capital have you raised?

Capital details were not explicitly shared, but the business has been spun out of a moderately successful hedge fund that I founded in 2011. We have operated profitably without taking external venture funding and have received acquisition interest, indicating sound financial health.

Was the company born from within or outside the industry?

The company was born from within the asset management and AI research space. My career began at IBM as a language modeling researcher, and I have over two decades of experience combining AI with financial applications. PredictNow.ai is an outgrowth of my hedge fund’s internal AI systems and reflects my longstanding expertise and passion for applying machine learning to real-world financial problems.

What growth metrics have you accomplished over the last 12 months?

We completed multiple successful proofs of concept with large banks, including one structured product that’s currently in the marketing phase with an insurance industry client. We have diversified interest across financial and international institutions and have actively developed market-ready solutions in asset management optimization. While not quantified, these milestones demonstrate a maturing product entering commercial deployment.

Within your domain, what is the current challenge that the industry is facing?

There’s a significant gap between advanced AI research and its real-world enterprise application. Many large corporations possess very limited internal AI capabilities. Executives often conflate AI with only large language models and overlook its broader utility. There's also a lack of understanding about the richness of non-textual data (such as transaction data) and how it can be used for business optimization. This disconnect between deep tech and enterprise adoption presents a major opportunity.

How does PredictNow.ai take a unique approach to providing value?

We are both domain experts in asset management and AI specialists, which is rare. Unlike researchers from DeepMind or OpenAI, who may lack direct application experience, we have built and tested models in live asset management environments. This dual expertise allows us to craft high-quality inputs for our models, which is just as critical as the model itself. Our edge lies in understanding both the modeling and the real-world business context where the models will operate.

What inspired the team to start this company?

I’ve been a serial entrepreneur since 2000 and started my hedge fund in 2011. PredictNow.ai stems from a personal passion for AI, which dates back to my early days at IBM. While my hedge fund has been successful and profitable, my deeper interest has always been in AI technology itself. PredictNow.ai is a return to that original passion, with the ambition to scale this platform and ultimately make it an attractive acquisition for a major technology company.

Can you share any goals for the next 12 months?

Our main goal is to scale the use of our AI-generated synthetic index, attracting multiple insurance and financial institutions to adopt structured products built around it. We’re also looking to expand into adjacent verticals such as:

• Shipping, through dynamic, context-aware pricing models

• Consumer packaged goods, by optimizing promotional strategies through simulated shopping and real-time AI decision-making 

More broadly, we aim to demonstrate how AI can dynamically adapt business parameters based on changing environments, rather than relying on outdated static rules.

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