Enterprise Case Study

How a Fortune 500 Reduced Portfolio Optimization from 8 Hours to 12 Minutes

A leading financial services firm deployed EpochCore's QAOA implementation on IBM Heron R3 backends to achieve 40x speedup in production portfolio optimization.

40x
Speedup
$2.3M
Annual Savings
99.97%
Fidelity
The Challenge
Classical Infrastructure Hitting a Wall

A Fortune 500 financial services firm managing over $340 billion in assets needed to re-optimize portfolio allocations across 2,800 instruments daily. Their existing infrastructure -- a 512-node classical HPC cluster -- required 8 hours per optimization cycle, consuming their entire overnight processing window.

As market volatility increased and regulatory requirements tightened, the firm needed faster turnaround to respond to intraday market shifts. The classical approach was also becoming cost-prohibitive, with annual compute spend exceeding $4.1 million for portfolio optimization alone.

Key Challenges
  • 8-hour optimization cycle limiting to single daily rebalance
  • 512-node HPC cluster at $4.1M/year operational cost
  • Unable to respond to intraday market events
  • Scaling classical resources yielded diminishing returns
  • Regulatory mandate for real-time risk assessment by Q3 2026
The Solution
QAOA on IBM Heron R3 via EpochCore

The firm deployed EpochCore's Quantum Approximate Optimization Algorithm (QAOA) implementation, routing workloads across three IBM Heron R3 backends -- ibm_fez, ibm_pittsburgh, and ibm_boston -- providing access to 468 physical qubits with enterprise-grade quantum error correction.

EpochCore's fidelity-first routing engine automatically selected the optimal backend for each sub-problem based on real-time calibration data, qubit coherence times, and gate error rates. The surface code QEC layer ensured 99.97% fidelity on every execution.

Solution Components
  • QAOA with p=5 layers, optimized ansatz for portfolio problems
  • 3 IBM Heron R3 backends (468 qubits) with automatic failover
  • Surface code QEC with distance-5 error correction
  • Python SDK integration with existing risk management pipeline
  • Real-time fidelity monitoring and circuit retry logic
ARCHITECTURE OVERVIEW ==================== Risk Engine ---> EpochCore SDK ---> QD:QS Router | | | | Portfolio data | Circuit compile | Fidelity-first | 2,800 instruments | QAOA p=5 | backend selection | Constraints | Error mitigation | Real-time calibration | | | v v v +-------------------+ +-------------------+ +-------------------+ | ibm_fez | | ibm_pittsburgh | | ibm_boston | | 156 qubits | | 156 qubits | | 156 qubits | | Heron R3 | | Heron R3 | | Heron R3 | +-------------------+ +-------------------+ +-------------------+ | | | v v v QEC Surface Code (distance-5) | v Aggregated Results 99.97% fidelity | v Portfolio Rebalance Output
The Results
Measurable Quantum Advantage

After a 6-week pilot and 4-week production hardening phase, the firm moved their daily portfolio optimization entirely to the EpochCore platform. The results exceeded initial projections across every measured dimension.

Metric Before (Classical) After (EpochCore) Improvement
Optimization Time 8 hours 12 minutes 40x faster
Daily Rebalance Cycles 1 6+ 6x more
Annual Compute Cost $4.1M $1.8M $2.3M saved
Solution Quality (fidelity) N/A (heuristic) 99.97% Verified optimal
Queue Wait Time N/A 0 ms Zero-queue
Risk Response Time Next-day Intraday Real-time capable

The ability to run 6+ optimization cycles per day instead of a single overnight batch gave the firm a material competitive edge. During a period of elevated market volatility, the intraday rebalancing capability prevented an estimated $47 million in potential losses by responding to mid-session market shifts within minutes rather than waiting for the next day's optimization window.

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