Franklin Templeton CEO said blockchain offers cost savings and fewer errors for tokenizations compared to the traditional system.
Jenny Johnson, CEO of Franklin Templeton, delivered insights at the 27th Annual Milken Institute Global Conference in California, highlighting blockchain’s efficiency and cost reduction in asset tokenization and sharing thoughts on generative AI benefits.
Johnson revealed a parallel experiment spanning six to eight months, comparing traditional and blockchain methods for processing account records. Results favored blockchain for its cost-effectiveness and reduced errors.
“We used to run our own in-house system, one of the few firms that did, and the one that we built on blockchain. So these are the records of the shareholders, and we parallel processed for a period of 6 to 8 months,” Johnson explained. “We were astonished by how much less, how much cost it was to run on blockchain. It’s very effective technology, and we think it is going to open up a lot of new investment opportunities.”
Johnson envisioned a future where all ETFs and mutual funds migrate to blockchain technology, foreseeing substantial cost savings from streamlined data verification processes.
“In the case of blockchain, there’s only one source of trust. That transaction happens, everybody has the source of trust, and so that drives out a lot of costs. And when you can drive out the friction in transactions, you can start to invest in new areas,” she elaborated.
Franklin Templeton’s notable equity tokenized fund, the Franklin OnChain US Government Money Fund (FOBXX), represented by the BENJI token, held a market capitalization of $368 million as of May 12, according to Dune Analytics.
Data is the new oil.
Johnson also discussed generative AI’s role in asset management, likening data to the next oil boom. She emphasized the advantage of large asset managers in AI development due to their vast proprietary data resources.
Franklin Templeton has already integrated an AI bot into their help desk, capable of addressing 60% of inquiries. Johnson anticipates even greater potential through a multi-faceted AI model, envisioning personalized investment strategies as a result.
