Micron Technology Got a Secret Money Making Recipe

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Micron Technology (NASDAQ: MU) is a global memory and storage solutions provider influencing information into intelligence, thereby helping the world learn, communicate and advance better. An innovator in the DRAM business, Micron Technology drives breakthrough innovation with a vast portfolio of technologies with artificial intelligence and autonomous vehicles. 

Today, Micron Technology is earning millions from its cash deposits courtesy of its internal artificial intelligence framework. Micron Technology’s robust artificial intelligence framework helps invest in funds generating higher returns in a low-interest-rate environment, which has troubled many finance experts across industries. But as the story unfolds, global treasurers have a clue to how Micron manages money.

A little study reveals that Micron has solid relationships with over 20 global banks for its quality supply of memory chips and data center storage devices. Speculations limelight on Micron as other companies all over the U.S. fetch close to zero returns from their stash of cash accumulated throughout the pandemic. Banks disinterested in accepting cash deposits is the major challenge.

According to S&P Global Market Intelligence, S&P 500 companies rose $2.07 trillion in 2019 to $3.03 trillion in 2020, and in the first quarter of 2021, reported $3.79 trillion in cash. Micron made $7.8 billion in the first quarter of 2021, which fell from $8.3 billion in 2020 ( $8.2 billion ± $200 million) but remains higher than the first quarter of 2019. Refer to market intelligence here.

Micron Technology Got a Secret Money Making Recipe
Image Description: Business people discussing the charts and graphs showing the results of their successful teamwork. 

According to the treasurer of Micron Technology, Greg Routin, “In this low-rate environment, given the amount of cash that we maintain, every basis point counts and translates to millions of dollars.” The CFO of Micron, David Zinsner, informs about a complicated matrix that makes an investment asset worthy of consideration, in which their AI investment asset recommender serves brilliantly.

Before developing this AI investment asset allocator, Micron Technology relied on employee recommendations for high-performing asset classes that greatly undermined the returns made possible by the new AI tool. In fact, the CFO thinks of it as the best cash management advisor to the finance and treasury, literally freeing them for more strategic work.

Micron CFO Zinser seems to be pretty ambitious with the AI tool, for he thinks of the possibility wherein the tool can complete the transaction beyond just recommending assets. That would be the kind of achievement Mr. Zinser would look forward to. So that would not only mean freeing up associates from the task of asset recommendation, asset investment, and monitoring.

Micron’s internal team had originally developed the AI investment tool to drive automation across departments. But today, in a situation where businesses have overwhelmed banks with cash deposits, banks have intentionally dropped the interest rate to deter businesses. Now with large funds, companies are in a dilemma around managing the cash flow for optimum returns.

The way Micron’s AI tool has recommended fund allocation toward higher-yielding bank accounts away from lower-yielding money-market funds has led to increased trust and dependency on the tool internally. Now Micron has come to know how International banks with smaller retail footprints have paid higher yields than some local U.S. banks. CFOs and fund managers take note to improve fund allocation strategy.

Now, if businesses have to follow suit, bring together your Business Intelligence (BI) and AI team AI to develop an AI bot that actively looks out for investment options such as overnight bank deposits, time deposits, money-market funds, currencies, etc. The cash at Micron is proportionate to the increased market demand for semiconductor and storage chips.

AI investment management tools are disrupting the conventional ways portfolio managers planned, managed, and executed investment funds, resulting in explosive growth as estimated by Deloitte. The Big Four consulting firm indicates how AI-powered digital tools will manage a growth forecast in wealth management from $5 trillion to $7 trillion by 2025 in the US alone.

While AI plays a very promising role, as evidenced in how Micron Technology has put its cash to task for higher yield, let’s be clear of the fact that AI is not “the solution” to the age-old quest for investment outperformance. The AI gets to be only as smart as the next panel of investment specialists who will guide the AI modeler into achieving the output but at scale. Portfolio managers will not run out of their businesses. Rather, by helping businesses develop in-house AI technology, they can ascertain a consistent flow of alpha.

According to the 2019 report by CFA (Chartered Financial Analyst) Institute, “few investment professionals are currently using programs typically utilized in ML techniques, including coding languages such as Python, R, and MATLAB” and that most portfolio managers “continue to rely on Excel (indicated by 95 percent of portfolio manager respondents) and desktop market data tools (three-quarters of portfolio manager respondents) for their investment strategy and processes.”

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