Company patents
Bank of America Corporation
Bank of America Corporation exhibits a strong and consistent focus on cybersecurity, with Network Security & Access Control (21.0% of portfolio) and Computer Security (19.7% of portfolio) being its top two categories, surprisingly maintaining high patenting activity despite a general decline across most categories so far in 2026. While Business Methods & Fintech (20.4% of portfolio) is a significant area, its patenting saw a notable decline of 24.6% in 2025, indicating a potential shift in priority, contrasting with the emerging focus on System Reliability & Diagnostics, which grew by 31.4% in 2025.
Patent Trend by Technology Area
Yearly patent publications since 2023
Product themes
Product-level themes inferred from filings since 2023, with category chips showing where each theme appears. Select a theme to filter the patents below.
5,033 US filings (since 2023) · 12 categories · 46 themes
Systems and methods for authenticating users, devices, or applications, authorizing their access to resources based on policies, and managing digital identities across various platforms.
Systems and methods for encrypting data at a fine-grained level (e.g., per data unit or based on sensitivity) and controlling access to it, often involving delegated authorization, contextual policies, or secure data sharing.
Systems and methods for collecting, processing, and ensuring the quality and consistency of data used for network monitoring, asset management, and operational decision-making, including conflict detection and reliability scoring.
Systems designed to streamline and automate various commercial transactions, including mobile-enhanced processes, secure online checkouts, customer service interactions, and privilege issuance, often leveraging digital authentication.
Mechanisms to facilitate the secure exchange of data between different entities or systems while enforcing usage policies, managing digital content rights, and ensuring data consistency during replication or transfer.
Applying artificial intelligence and machine learning techniques to enhance cryptographic systems, such as generating encryption models, improving zero-trust architectures, or enabling privacy-preserving computations like federated learning.
Systems and methods for identifying and blocking unauthorized access, malicious activities, or abnormal behavior within a network by analyzing traffic, system logs, or behavioral patterns.
Systems and methods for automatically deploying, configuring, and updating network devices and services, including software updates, client onboarding, and topology management across various network types.
Technologies for securing, managing, and transacting with virtual currencies, non-fungible tokens (NFTs), and other blockchain-based digital assets, including hardware wallets and tokenization schemes for various purposes.
Techniques for distributing computational tasks, data storage, and service logic across cloud data centers, edge devices, and user equipment to improve performance, resilience, or resource utilization. This includes architectures for split rendering, decentralized ledgers, and microservices.
Focuses on using distributed ledger technology (DLT) like blockchain to secure financial transactions, manage digital identities, or ensure data integrity and traceability across various applications.
Methods and systems for efficiently allocating computing resources, balancing workloads, and managing power states to improve performance, reduce energy consumption, or enhance reliability in computing platforms.
Methods and systems for integrating, transforming, and managing complex or domain-specific data from disparate sources into a unified structure, often for specific applications like social networks, genomics, or business forms.
Systems and methods utilizing artificial intelligence, particularly large language models and neural networks, to extract, summarize, generate, or categorize information from unstructured or semi-structured data sources.
Involves systems designed to automatically detect errors or failures and initiate predefined or intelligent corrective actions, recovery procedures, or notifications to minimize downtime and manual intervention.
Techniques for monitoring system components and behaviors to anticipate failures, performance degradation, or anomalies, often leveraging machine learning for pattern recognition and forecasting.
Developing and applying machine learning algorithms that leverage quantum computing principles, such as quantum circuits or autoencoders, for tasks like simulation or data processing.
Systems and methods for automating multi-step tasks, business processes, or service interactions, often involving AI agents, programmable interfaces, or formal orchestration languages to streamline operations.
Platforms and methods for aggregating data from diverse sources, generating dynamic content, and delivering it efficiently to users, often involving social media, programmatic advertising, or interactive experiences within cloud environments.
Systems and methods designed to ensure adherence to regulatory rules, corporate policies, or contractual agreements, often involving automated validation of electronic transactions, smart contract enforcement, or API governance.
Techniques for protecting data at rest or in backup, ensuring its integrity, confidentiality, and verifiable origin, often involving encryption, unique identifiers, or secure repositories.
AI systems designed to engage in natural language dialogue, maintain conversation state, understand user intent, and generate relevant responses, often across multiple communication channels or modalities.
Systems that process data to provide personalized recommendations, predict events, or automate decision-making processes based on learned patterns, user behavior, or environmental factors.
Technologies enabling the creation and management of virtual computing environments, including virtual machines and virtual desktops, with an emphasis on secure and efficient remote access, updates, and performance.
Techniques and systems designed to monitor network health, diagnose issues, optimize traffic flow, and ensure continuous operation and reduced downtime in complex network environments, including cloud and storage area networks.
Systems and methods for securely and reliably delivering, installing, and managing software or firmware updates to distributed or embedded devices, often considering network conditions, resource constraints, or storage repartitioning.
Methods and frameworks for systematically verifying the correctness, performance, and security of software systems, including infrastructure as code, virtual workloads, APIs, and identifying potential vulnerabilities or inconsistencies.
Methods and systems for monitoring, controlling, and managing Internet of Things (IoT) devices and their communication networks, often involving adaptive or intelligent frameworks for data acquisition, relay, and automation.
Techniques and tools for automatically identifying, resolving, building, and packaging software dependencies, including managing versions, branches, and ensuring the integrity and security of the dependency chain.
Tools and processes for assessing, monitoring, and improving the security configuration and external accessibility of resources deployed within cloud computing environments.
Utilizing dedicated hardware components, secure enclaves, or trusted execution environments to perform cryptographic operations, enhancing security, performance, or isolation from software vulnerabilities.
Systems and methods for automating the lifecycle of machine learning models, including pipeline deployment, model management, versioning, and configuring for different inference environments.
Methods and systems for identifying, extracting, and structuring specific entities, relationships, or insights from text-based documents, often involving techniques like named entity recognition, relation extraction, or summarization.
Technologies for establishing and maintaining secure communication channels between devices or networks, often employing encryption, secure protocols, or virtual private networks (VPNs).
Techniques employed within compilers or related tools to analyze program code, identify entities for compilation, and optimize execution on target hardware, including reconfigurable systems, to improve performance or resource efficiency.
Systems that use user data, preferences, and machine learning to generate tailored advice, product recommendations, goal-setting plans, or contextual information for individuals across different domains.
Techniques for generating human-like text or other content using large pre-trained models, often involving prompt engineering, speculative decoding, or multi-modal inputs for content creation.
Methods and systems for generating, distributing, updating, rotating, and securely destroying cryptographic keys to maintain data confidentiality and integrity over time, including quantum key distribution.
Encompasses strategies and technologies to ensure the availability, integrity, and recoverability of data and systems, including robust backup, replication, error correction, and efficient data restoration.
Utilizing machine learning, particularly deep learning, to analyze medical data such as images, sensor readings, or physiological signals for disease prediction, diagnosis, or treatment assessment.
Specialized hardware, architectural designs, and computational methods to improve the speed, efficiency, and security of artificial intelligence and machine learning model execution, particularly for inference and data processing.
Techniques and systems for reducing energy consumption in computer networks while maintaining or improving performance, often involving predictive modeling, simulation, and dynamic adjustments to network infrastructure.
Techniques for improving the performance, efficiency, or practicality of fully homomorphic encryption (FHE) schemes, often involving hardware accelerators or optimized algorithms for operations like bootstrapping and key-switching.
Focuses on establishing and enforcing quality standards for software development, deployment, and infrastructure configuration, utilizing automated validation, testing, and governance frameworks.
Techniques for combining and analyzing information from multiple distinct data modalities (e.g., text, image, video, audio, sensor data) to derive richer insights or improve system performance and decision-making.
Methods for training machine learning models across multiple decentralized devices or servers while keeping data localized, often involving aggregation of model parameters and secure communication.
Patents
Showing 1-10 of 7424