Technology areas: Computing & Software • Networking & Security
11 pending office actions • 11 art units • 11 examiners • 0 of 11 (0%) have an AI response strategy ready • 18 patents granted in the last 365 days
Equifax Inc. has 14 pending office actions in Computing & Software. Each matter is assigned to a distinct examiner, and the docket spans 13 distinct art units. This pattern shows broad examiner dispersion with only limited repetition in technical placement.
COBB, MATTHEW is the busiest examiner, with 1 pending matter. The data does not indicate an examiner-level concentration. Counsel may focus on the separate prosecution records while using the shared technology area to maintain consistent terminology, disclosure positions, and claim objectives.
Based on the USPTO statutory response window for each pending office action. 4 of the docket's apps have a known mailing date; the rest are excluded from the tile counts.
Every pending office action with a known statutory deadline, placed on a days-until-due axis. Dots left of Today are overdue; the further right, the more runway. Cases that share a deadline window stack vertically. 4 of the docket's apps have a known mailing date.
Difficulty is derived from the rejection statutes on the most recent pending office action. §101-driven and multi-statute cases are graded Hard; §112-only and obviousness-type double-patenting cases are graded Easy; everything else is Medium. "Unknown" means we have not yet parsed a statute for that office action.
| Bucket | Cases |
|---|---|
| §101 only | 1 (9%) |
| §101 + other | 2 (18%) |
| §103 only | 4 (36%) |
| §102 only | 1 (9%) |
| Double-patenting only | 1 (9%) |
| Double-patenting + other | 1 (9%) |
| Multi-statute (no §101) | 1 (9%) |
How the docket's pending cases split across USPTO tech-center bands.
Manual office-action response work runs about 10 hours per case. The time-saved bands below show what IP Author's prosecution pipeline typically delivers — a conservative 20% on the low end, 35% in the middle, 50% on the high end.
| Examiner | Apps on this docket | Allow rate | Interview lift |
|---|---|---|---|
| COBB, MATTHEW | 1 | 72.9% | +35.2% |
| REZA, MOHAMMAD W | 1 | 87.5% | +11.1% |
| PYZOCHA, MICHAEL J | 1 | 80.2% | +17.3% |
| STEINLE, ANDREW J | 1 | 87.5% | +19.7% |
| TOKUTA, SHEAN S | 1 | 79.8% | +16.2% |
| HAN, BYUNGKWON | 1 | 33.3% | +62.5% |
| SKWIERAWSKI, PAUL J | 1 | 79.4% | +25.1% |
| ANYA, CHARLES E | 1 | 81.7% | +32.9% |
| WONG, WILLIAM | 1 | 31.7% | +26.9% |
| MAHARAJ, DEVIKA S | 1 | 56.7% | +7.7% |
Cases in front of an examiner with an allow rate of 80%+ where the difficulty is Easy or Medium. The top 3 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18348970 | TECHNIQUES FOR MITIGATING BACK PRESSURE, AUTO-SCALING THROUGHPUT, AND CONCURRENCY SCALING IN LARGE-SCALE AUTOMATED EVENT-DRIVEN DATA PIPELINES | ANYA, CHARLES E | 12d |
| 19233644 | REAL-TIME SERVICING OF VERIFICATION QUERIES USING HYBRID DATA SOURCES | REZA, MOHAMMAD W | — |
| 19059907 | HISTORICAL RISK ASSESSMENT FOR RISK MITIGATION IN ONLINE ACCESS CONTROL | STEINLE, ANDREW J | — |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 4 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18306103 | MULTI-STAGE MACHINE-LEARNING TECHNIQUES FOR RISK ASSESSMENT | MAHARAJ, DEVIKA S | 49d overdue |
| 19301049 | CONSOLIDATION OF DATA SOURCES FOR EXPEDITED VALIDATION OF RISK ASSESSMENT DATA | COBB, MATTHEW | — |
| 19175584 | TECHNIQUES FOR CONTROLLING ACCESS TO COMPUTING SYSTEMS BASED ON A RISK SCORE | PYZOCHA, MICHAEL J | — |
| 18719076 | EXPLAINABLE MACHINE LEARNING BASED ON WAVELET ANALYSIS | HAN, BYUNGKWON | — |
Cases in front of an examiner whose interview lift is 10 percentage points or more — i.e. interviewed cases historically resolve more favorably than non-interviewed ones. The top 8 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18348970 | TECHNIQUES FOR MITIGATING BACK PRESSURE, AUTO-SCALING THROUGHPUT, AND CONCURRENCY SCALING IN LARGE-SCALE AUTOMATED EVENT-DRIVEN DATA PIPELINES | ANYA, CHARLES E | 12d |
| 18252660 | EXPLAINABLE MACHINE-LEARNING MODELING USING WAVELET PREDICTOR VARIABLE DATA | WONG, WILLIAM | 23d |
| 19301049 | CONSOLIDATION OF DATA SOURCES FOR EXPEDITED VALIDATION OF RISK ASSESSMENT DATA | COBB, MATTHEW | — |
| 19233644 | REAL-TIME SERVICING OF VERIFICATION QUERIES USING HYBRID DATA SOURCES | REZA, MOHAMMAD W | — |
| 19175584 | TECHNIQUES FOR CONTROLLING ACCESS TO COMPUTING SYSTEMS BASED ON A RISK SCORE | PYZOCHA, MICHAEL J | — |
| 19059907 | HISTORICAL RISK ASSESSMENT FOR RISK MITIGATION IN ONLINE ACCESS CONTROL | STEINLE, ANDREW J | — |
| 18950422 | DATA VALIDATION TECHNIQUES FOR SENSITIVE DATA MIGRATION ACROSS MULTIPLE PLATFORMS | TOKUTA, SHEAN S | — |
| 18719076 | EXPLAINABLE MACHINE LEARNING BASED ON WAVELET ANALYSIS | HAN, BYUNGKWON | — |
| Art Unit | Apps |
|---|---|
| 3661 | 1 |
| 2407 | 1 |
| 2409 | 1 |
| 2497 | 1 |
| 2419 | 1 |
| 2121 | 1 |
| 2439 | 1 |
| 2194 | 1 |
| 2144 | 1 |
| 2123 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19301049 | CONSOLIDATION OF DATA SOURCES FOR EXPEDITED VALIDATION OF RISK ASSESSMENT DATA | COBB, MATTHEW | 3661 | §102§103 | Non-Final OA | — | Pending | Aug 15, 2025 |
| 19233644 | REAL-TIME SERVICING OF VERIFICATION QUERIES USING HYBRID DATA SOURCES | REZA, MOHAMMAD W | 2407 | §103Other | Non-Final OA | — | Pending | Jun 10, 2025 |
| 19175584 | TECHNIQUES FOR CONTROLLING ACCESS TO COMPUTING SYSTEMS BASED ON A RISK SCORE | PYZOCHA, MICHAEL J | 2409 | §101§102§103 | Non-Final OA | — | Pending | Apr 10, 2025 |
| 19059907 | HISTORICAL RISK ASSESSMENT FOR RISK MITIGATION IN ONLINE ACCESS CONTROL | STEINLE, ANDREW J | 2497 | DP | Non-Final OA | — | Pending | Feb 21, 2025 |
| 18950422 | DATA VALIDATION TECHNIQUES FOR SENSITIVE DATA MIGRATION ACROSS MULTIPLE PLATFORMS | TOKUTA, SHEAN S | 2419 | §103DP | Non-Final OA | — | Pending | Nov 18, 2024 |
| 18719076 | EXPLAINABLE MACHINE LEARNING BASED ON WAVELET ANALYSIS | HAN, BYUNGKWON | 2121 | §101§103§112 | Non-Final OA | — | Pending | Jun 12, 2024 |
| 18365781 | SIMILARITY HASHING FOR ACCESS CONTROL | SKWIERAWSKI, PAUL J | 2439 | §102 | Non-Final OA | — | Pending | Aug 04, 2023 |
| 18348970 | TECHNIQUES FOR MITIGATING BACK PRESSURE, AUTO-SCALING THROUGHPUT, AND CONCURRENCY SCALING IN LARGE-SCALE AUTOMATED EVENT-DRIVEN DATA PIPELINES | ANYA, CHARLES E | 2194 | §103 | Final Rejection | 12d | Pending | Jul 07, 2023 |
| 18252660 | EXPLAINABLE MACHINE-LEARNING MODELING USING WAVELET PREDICTOR VARIABLE DATA | WONG, WILLIAM | 2144 | §103 | Final Rejection | 23d | Pending | May 11, 2023 |
| 18306103 | MULTI-STAGE MACHINE-LEARNING TECHNIQUES FOR RISK ASSESSMENT | MAHARAJ, DEVIKA S | 2123 | §101 | Non-Final OA | 49d overdue | Pending | Apr 24, 2023 |
| 17645517 | MACHINE-LEARNING TECHNIQUES FOR TIME-DELAY NEURAL NETWORKS | LEY, SALLY THI | 2147 | §103 | Final Rejection | 13d | Pending | Dec 22, 2021 |
IP Author helps IP teams respond to office actions faster with AI-generated responses, examiner analytics, and prosecution intelligence.
Start Free TrialEquifax Inc. has 11 pending office actions as of October 2026, spread across 11 art units and 11 examiners.
Matthew Cobb has the most, with 1 of Equifax Inc.'s pending office actions.
Mostly Networking & Security (USPTO Tech Center 2400), based on where its pending office actions are examined.
