SiriusXM uses machine learning models to predict the daily cadence of cash flows

Best use of AI in Corporate Treasury

Highly Commended Winner

SiriusXM

Photo of Jaylenn Murdamoothoo, J.P. Morgan collected the award of behalf of SiriusXM.

Michael Bianco

Associate Director, Treasury

United States

SiriusXM is a North American audio entertainment company that delivers satellite radio, streaming music and podcasts for in-car and mobile listeners. The platform provides ad-free music, live sports, news and talk shows across its subscription and ad-supported platforms.

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The challenge

SiriusXM’s treasury team manages complex, idiosyncratic cash flows that create strategic financing challenges. For example, the company’s advertising revenue arrives on unpredictable schedules as agencies often pay at their discretion.

In the meantime, disbursements can spike irregularly, creating frequent cash gaps that required SiriusXM to draw on its revolving credit line on a sporadic basis, sometimes multiple times weekly. For forecasting, SiriusXM relied on an MS Excel model built on historical transactions data, but it didn’t provide sufficient granularity needed for precise day‑to-day cash positioning.

When Michael Bianco joined SiriusXM as Associate Director, Treasury, he sought to understand the cash flow patterns more rigorously. He recognised an opportunity: if the treasury could accurately predict the percentage of monthly receipts and disbursements hitting the account each day, SiriusXM could make smarter decisions about when to convert expensive prime-rate borrowings to more affordable Secured Overnight Financing Rate (SOFR) loans.

The solution

SiriusXM worked with J.P. Morgan Payments to implement Cash Flow Intelligence (CFI), an AI-powered forecasting and analytics platform embedded directly in J.P. Morgan Access.

CFI uses proprietary machine learning models developed by J.P. Morgan Payments engineers to analyse historical transaction patterns and predict the daily cadence of cash flows with precision.

CFI automatically categorises transactions into rules-based groups – sales revenue, operating expenses and vendor payments – and predicts what percentage of monthly receipts and disbursements will hit the account each business day. This granular daily visibility gave the treasury organisation the insight needed to optimise borrowing and repayment decisions.

Best practice and innovation

The judges commended SiriusXM for its structured, holistic approach to improve not only cash flow forecasting but also actual cash flow.

Rather than accepting generic forecasting capabilities, SiriusXM actively worked with J.P. Morgan Payments to customise CFI for its specific needs. Treasury worked with J.P. Morgan Payments to transform aggregated automated clearing house (ACH) disbursement data into granular, line‑item visibility.

Through ongoing collaboration with the CFI development team, SiriusXM gained the ability to view individual payee details within large ACH payments, sometimes totalling US$50m with numerous transaction lines. This enhancement helped the treasury to validate forecasts with unprecedented precision and understand exactly when specific vendor payments would clear.

SiriusXM also demonstrated best practice in evidence-based AI adoption. The company built its own historical forecasting model to benchmark CFI’s accuracy, then tracked the application’s predictions against actual results for months before making tactical financing decisions based on its output.

Key benefits

Cost savings.
Process efficiencies.
Increased automation.

SiriusXM now accurately predicts the daily cadence of receipts and disbursements, allowing treasury to strategically time when to draw on its revolver at prime rate or convert to cheaper one-month SOFR borrowing. SiriusXM believes it meaningfully decreased interest expense by optimising its borrowing and repayment decisions, on the order of US$500,000 in 2025.

Beyond cost savings, the company also transformed its treasury operations. The CFI application provides confidence in daily cash positioning, allowing treasury to make informed financing decisions quickly. The enhanced ACH visibility gives treasury the ability to validate forecasts and understand exactly when vendor payments will clear.

The treasury team, previously unfamiliar with AI technology, now actively seeks opportunities to apply AI to treasury challenges. This cultural shift positions the treasury team to use emerging technologies rather than resist them.

Sam Bomes

Executive Director, Media and Entertainment Payments Sales Manager, J.P. Morgan

SiriusXM leveraged AI-driven Cash Flow Intelligence (CFI) from J.P. Morgan to revolutionise its forecasting and analytics capabilities. By automatically categorising transactions and predicting daily cash flows with high precision, SiriusXM’s treasury can now make better informed borrowing decisions. Working closely with our team, SiriusXM also enhanced ACH visibility to line-item detail, significantly improving day-to-day cash positioning decisions. We applaud SiriusXM for harnessing the power of AI to elevate their treasury operations and, on behalf of J.P. Morgan, we congratulate them on this highly commended recognition.

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The Adam Smith Awards are the industry benchmark for best practice and innovation in corporate treasury. The 2026 awards attracted 635 nominations. To find out more please visit treasurytoday.com/adam-smith-awards

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