Bank of New York Mellon Corp

3 Innovating new products and solutions • Continuous product innovation and track record of growth (e.g., Buyside Trading Solutions, Collateral One, Borrow Plus) • Connecting traditional and digital financial ecosystems with continued progress on 24/7 payments, digital cash and tokenized infrastructure, combining capabilities from across BNY's platforms Accelerating AI • Investments in our people, infrastructure, platform and broader ecosystem have created a strong foundation on which we are building applied AI solutions into our workflows and across the entire company • AI-integration has started to show tangible benefits across the entire client lifecycle: innovating, prospecting, onboarding, transacting 2026 Mid-year Business Update Serving our clients as One BNY • 14 consecutive quarters of YoY sales growth • Record sales performance in 1Q26 and 2Q26 • Larger, more comprehensive client solutions, with average deal size in 1H26 up >20% YoY • ~10% of clients generating sales in 1H26 are new to BNY Unlocking scale and growth across our platforms • 10 consecutive quarters of positive operating leverage • Completed activation phase of the platform operating model in 2Q26, shifting focus to realizing the full benefits of operating as one company • Tracking toward ~$500mm of incremental investments and ~$450mm of efficiency savings in 2026 Strong execution continues to accelerate growth and strengthen our competitive position ROTCE (excluding notable items) 21% 22% 24% 26% 30% FY22 FY23 FY24 FY25 1H26 29% 30% 33% 36% 39% FY22 FY23 FY24 FY25 1H26 Pre-tax Margin (excluding notable items) 0% 0% 2% 3% FY22 FY23 FY24 FY25 1H26 Organic Fee Growth (YoY) 4% 7% 5% 8% 13% FY22 FY23 FY24 FY25 1H26 Total Revenue (YoY) (b) Represents a non-GAAP measure. See pages 13 through 15 in the Appendix for the corresponding reconciliation of these non-GAAP measures excluding notable items. Note: See page 12 in the Appendix for corresponding footnotes. (a) (b)(c) (b)(d) ~4.5%

3 • Creation of the “digital employee” – Multi-agentic AI solutions that operate alongside human colleagues • Launched Eliza 2.0, a more advanced, agentic experience • Entered into a multi-year collaboration with OpenAI • Deepened engagement with academia to drive research and innovation in AI • Further expanded Eliza's governance and control capabilities, including a single pane of glass for enterprise AI initiatives • Built foundation of secure, resilient and scalable infrastructure • Deployed advanced monitoring, AI and machine learning in our Cyber, Technology and Operations Center for detection and rapid response Evolution of AI at BNY With the creation of the BNY AI Hub in 2023, we established the foundation for our ever-accelerating AI evolution 20252023 2024 • Creation of the BNY AI Hub, bringing together data science, AI and machine learning teams • Identified 30 areas of opportunity for AI deployment across BNY • Expanded cloud and AI collaboration with Microsoft to scale generative AI • Built on-premise GPU infrastructure powered by NVIDIA SuperPODs to supplement our cloud solutions • Launched Eliza, BNY’s AI platform – A multi-agentic, general- intelligence-model- agnostic platform – Integrates models from e.g., OpenAI, Google, Anthropic • Published “Our Commitment to the Responsible, Ethical Use of Data and AI” Up until 2022

4 Our Vision: AI for Everyone, Everywhere, and Everything Success in AI adoption and implementation starts with culture CULTURE BREADTH DEPTH • BNY’s cultural transformation of the past few years, including our ongoing transition into the platforms operating model, have created a fertile ground for AI adoption and implementation • Proprietary AI training and development programs available to every employee, beginning with every analyst as part of their orientation programming – Delivered 171,000 AI learning hours in 2025, spanning live AI bootcamps, curated learning pathways and personalized AI learning courses • 100% of employees have access to cutting-edge technology and deep research capabilities through Eliza, BNY’s AI platform • Approximately 50% of employees are daily users of AI and over 50% are building AI agents, supported by our global AI talent development programs that train our people – both engineers and employees without a technical background – to embed AI directly into daily workflows • ~220 enterprise AI solutions in production, and ~140 digital employees • Enhanced security and resilience • Deepening process excellence across: – High-volume workflows – embedding AI to automate at scale, e.g., multi-currency payments processing – Specialized products – applying domain-trained AI to complex financial activities, e.g., anomaly detection in net asset value ("NAV") calculation – Customized solutions – delivering client-specific solutions, e.g., onboarding, portfolio-level credit risk analysis

5 30 30 33 36 2022 2023 2024 2025 Medium- term 21.1 21.8 23.8 26.4 2022 2023 2024 2025 Medium- term OUTPUTS PROSPECTING TRANSACTINGINNOVATING STREAMLININGONBOARDING ~50% Of any annual account plan is drafted using AI as of 2025 ~60% Faster client account plan completion in 2025 vs. 2024 ~25% Of new onboardings supported with an AI- enabled process in 1Q26 >20% Faster completion of certain onboarding processes for corporate clients in 1Q26 vs. 1Q25 ~70% Of restricted party screening for payments reviewed by AI >30% Faster resolution of restricted party screening when reviewed by AI >10% Of custody settlement transaction status inquiries addressed by AI as of 1Q26 >80% Faster investigation of settlement inquiries when addressed by AI in 1Q26 vs. 1Q25 >40% Of code authored by AI in 1Q26 >10% Increase in software releases in 1Q26 vs. 1Q25 $338 $339 $355 $401 2022 2023 2024 2025 $99 $103 $116 $143 2022 2023 2024 2025 Our Strategy and Execution: Reimagining BNY with AI at our Core Breadth and depth of adoption enables deep AI-integration into our workflows across the entire company PROFITABILITY Revenue per Employee(a)(b) ($'000) (excluding notable items) Pre-tax Income per Employee(a)(b) ($'000) (excluding notable items) Pre-tax Margin(a)(c) (%) (excluding notable items) ROTCE(a)(d) (%) (excluding notable items) 38 +/- 28 +/- SCALABILITY PRODUCTIVITY INPUTS Our work to reimagine BNY is showing results, and will increasingly be enabled by AI (a) Represents a non-GAAP measure. See pages 14 and 16 in the Appendix for the corresponding reconciliations of the non-GAAP measures excluding notable items. (e) Represents a forward-looking non-GAAP financial measure. See "Cautionary Statement" on page 17 for information regarding forward-looking non-GAAP financial measures. Note: See page 13 in the Appendix for corresponding footnotes. Medium-term refers to a 3-5 year horizon. (e) (e) Examples:

BNY had a strong start to 2026 with record revenue of $5.4 billion in the first quarter, up 13% year-over-year, reflecting broad-based growth across our Securities Services and Market and Wealth Services businesses. We delivered over 800 basis points of positive operating leverage, while investing in new products, capabilities, AI, and – critically – our people and culture. Taken together, we reported a pre-tax margin of 37%, generated an ROTCE of 29%, and grew earnings per share

13 Footnotes Page 5 – Our Strategy and Execution: Reimagining BNY with AI at our Core (b) Revenue per employee, excluding notable items and pre-tax income per employee, excluding notable items represent total revenue, excluding notable items and income before income taxes, excluding notable items, for the respective time periods, divided by the 5-point annual average of full-time employees as reported for the respective time periods. Prior to 2024, full-time employees included interns. Revenue per employee was $401,600 for the year ended December 31, 2025, $355,460 for the year ended December 31, 2024, $335,806 for the year ended December 31, 2023 and $327,566 for the year ended December 31, 2022. Pre-tax income per employee was $141,160 for the year ended December 31, 2025, $111,646 for the year ended December 31, 2024, $81,271 for the year ended December 31, 2023 and $68,966 for the year ended December 31, 2022.

At key career transition points, from internship to executive management, we offer programs and development opportunities to help employees advance their careers and progress within our organization. Our extensive training and development opportunities are designed to enable employees to grow professionally and advance within our organization. In 2025 we built out our AI training offerings so all employees can develop this important

future skill and contribute to our “AI everywhere for everyone” philosophy.

We also consider data-related risks in the execution of our business objectives and processes, including the development of new products and services, including artificial intelligence applications. We remain committed to increasing the effectiveness of our data management practices which are designed to enable us to deliver products and services to our clients across the investment lifecycle.

Model Risk Management is a function within our second line of defense and is responsible for developing and managing the frameworks and processes through which models are initiated, documented, validated, monitored, and governed throughout their useful life from development to retirement. These processes include enforcement of standards for developing models, risk assessment and validation of models, change control, and monitoring the ongoing performance of models. The function is independent of model developers and users. Model Risk Management’s framework includes use cases employing artificial intelligence, including large language models, and Model Risk Management is among the functions integrated into the Company’s broader, cross-functional artificial intelligence risk management framework. Model Risk Management is responsible for maintaining an active inventory of models, and models must be declared to Model Risk Management for evaluation by the Company’s staff.

The current U.S. presidential administration has issued executive orders associated with, among other things, federal policy concerning tariffs, artificial intelligence, and digital assets. As the federal government’s posture on these and other matters continues to evolve, BNY is reviewing the impacts of these orders on its business and operations.

EU Artificial Intelligence Act

On July 12, 2024, the EU’s Regulation on Artificial Intelligence (“AI Act”) was published in the Official Journal of the EU and came into force on Aug. 1, 2024. The AI Act will apply extraterritorially, impacting both EU and non-EU entities providing or deploying artificial intelligence systems in the EU or placing General-Purpose artificial intelligence models on the EU Market, and will impact BNY. The AI Act creates pan-EU regulation to manage the risks associated with the use of artificial intelligence, including with respect to financial services. The AI Act requires categorization of artificial intelligence systems into four risk levels depending on their potential to harm individuals or society (unacceptable risk, high risk, limited risk, and minimal risk) and imposes obligations depending on the risk categorization, which may include data governance, documentation and recordkeeping, human oversight, testing, cybersecurity, disclosure, regulatory notification or reporting, or training. In addition, the AI Act prohibits artificial intelligence that pose unacceptable risks that are abusive or contradict EU values, including artificial intelligence that may be manipulative, exploitive, or discriminatory. The individual provisions of the AI Act apply on a rolling basis from Feb. 2, 2025 to Aug. 2, 2027. BNY has evaluated the impact of the AI Act and has established an implementation program designed to operationalize the regulatory requirements.

The NYSDFS requires financial institutions regulated by NYSDFS, including The Bank of New York Mellon, to establish a cybersecurity program, adopt a written cybersecurity policy, designate a chief information security officer, address artificial intelligence risks related to cybersecurity, and have policies and procedures in place to ensure the security of information systems and non-public information accessible to, or held by, third parties. The NYSDFS rule also includes a variety of other requirements to protect the confidentiality, integrity and availability of information systems, including the annual delivery of a certificate of compliance.

•The development and use of artificial intelligence.

We are required to accurately process large numbers of transactions each day on a timely basis. The transactions we process or execute are operationally complex and can involve numerous parties, jurisdictions, regulations and systems, and, therefore, are subject to execution and processing errors and failures. In addition, we utilize certain manual processes, which are subject to increased risks of human and other processing error, malfeasance, fraud and other misconduct than automated processes. When errors or delays do occur, they may be difficult to detect and remediate in a timely manner. The use of automation, artificial intelligence and other emerging technologies in connection with automated processes may amplify the impact of any such error or delay, as the failure to timely discover and respond to an operational error can have dramatic consequences. These risks are heightened in connection with automated processes and from the implementation of new products, systems or processes, which may present new risks that may not be adequately identified, or for which we may not have adequate controls. Furthermore, the risks resulting from an operational error may be heightened with respect to certain asset classes, such as some digital assets, with respect to which it may be impossible to retrieve wrongfully or erroneously transferred digital assets.

software and networks could result in greater susceptibility to cyberattacks, particularly in light of the greater frequency and severity of cyberattacks in recent years, as well as the growing prevalence of cyberattacks affecting third-party software and information service providers. Additionally, emerging technologies such as artificial intelligence and cloud computing are becoming increasingly critical to the operation of our systems and platforms, and, as our reliance on these technologies continues to grow, we will continue to be increasingly subject to evolving risks associated with their use. Our new product initiatives, including in connection with digital asset services, may further expose us to new and evolving technology risks and may lead to dependencies on, and compatibility issues with, decentralized or third-party blockchains and their protocols, which we do not control. Although we have programs and processes to identify such risks, there can be no assurance that any such disruptions, failures or delays will not occur or, if they do occur, that actions taken to mitigate their impact will be timely or adequate. Although we maintain insurance covering certain technology infrastructure losses and intend to maintain such insurance coverage if it is available to us on commercially reasonable terms, there can be no assurance that liabilities or losses we may incur, including as a result of a cybersecurity incident, will be covered under such policies or that the amount of insurance will be adequate. In addition, although we evaluate and seek opportunities to strengthen our business continuity and operational resiliency capabilities, there can be no guarantee that a technology outage will not occur, including as a result of failures related to upgrades and maintenance, that our incident response processes will be effective to efficiently identify and respond to an adverse event, or that our business continuity and operational resiliency capabilities will enable us to maintain our operations and appropriately respond to events.

transactions and communicate with customers and counterparties, which could, in turn, increase our counterparty credit and other exposures. This risk may be intensified to the extent there is a limited number of third parties offering a unique product or service, if there is concentration in third parties from a single geographic area or due to the nature of the third party’s industry and operations (e.g., firms that may have less robust scale, financial and operational resiliency standards with which to defend against a cyberattack), as well as to the extent third parties (including their downstream service providers) with which we do business have adopted artificial intelligence and other emerging technologies. As financial entities and technology systems globally become more complex and interconnected, a technology disruption or other operational event that significantly degrades, deletes or compromises the systems or data at one institution or vendor could disrupt the functioning of the overall financial system. Such a disruptive event has in the past impaired, and could in the future impair, our ability to settle transactions. Further, we may not be able to effectively monitor or mitigate operational risks impacting our vendors or relating to the use of common and other vendors by third-party service providers, which could result in potential liability to clients and customers, regulatory fines, penalties or other sanctions, increased operational costs or harm to our reputation.

Additionally, we face risks from cyberattacks targeted at third-party service providers and their downstream service providers, which could impact our operations. Our reliance on third-party service providers, as well as our increasing adoption of artificial intelligence solutions, employees’ usage of mobile and cloud technologies and our remote access systems, leave our networks susceptible to greater access points for attackers to exploit. This further increases the risk of unauthorized access to our networks and results in greater amounts of information being available for access, all of which heightens risks relating to the frequency and severity of cyberattacks against us and our third-party service providers and their downstream service providers.

providers, clients, financial market utilities and other financial institutions). Malicious actors, who are becoming increasingly sophisticated and may see their effectiveness enhanced by the use of artificial intelligence, quantum computing and other novel methods, may also attempt to place individuals within BNY or fraudulently induce employees, vendors, clients or other users of our systems through social engineering, such as phishing or deepfake-enabled attacks, to disclose sensitive information in order to gain access to our data or that of our clients, or to send funds or authorize the sending of funds.

The development and use of artificial intelligence present risks and challenges that may materially adversely impact our business.

The deployment of artificial intelligence, including generative artificial intelligence and other advanced machine learning technologies, by us, our third-party vendors, clients, counterparties and other market participants, combined with rapid advances in this emerging technology, present risks and challenges that may fundamentally alter the competitive landscape and the markets in which we operate. Artificial intelligence has the potential to transform economic and societal structures in ways that are difficult to predict or control, potentially threatening the viability of our company and the broader financial system. These risks may occur as a result of enhanced governmental or regulatory scrutiny, litigation, ethical concerns, confidentiality or other security risks, intellectual property concerns over data rights and protection, increased exposure to copyright infringement or intellectual property misappropriation claims, heightened susceptibility to cyberattacks, increased frequency and severity of cyberattacks, inaccurate or biased algorithms or underlying datasets, misuse or misappropriation as well as other factors that could adversely affect our business, reputation and financial results. In addition, poor implementation of artificial intelligence by us or our third-party service providers could subject us to additional risks that we may not adequately predict or mitigate.

The failure to strategically embrace the potential of artificial intelligence or to achieve the expected effectiveness, productivity or cost-reduction from our adoption of artificial intelligence may result in a competitive disadvantage for us. If we cannot offer new artificial intelligence-facilitated technologies as quickly as our competitors, if our competitors develop more cost-effective solutions or other product offerings, if our employees do not adopt such

technologies expediently or if we are not able to source components we may require, such as artificial intelligence chips due to a supply chain shortage amid rising geopolitical uncertainty, we could experience a material adverse effect on our operating results, customer relationships and growth opportunities. Our use and deployment of artificial intelligence, for example digital engineers and other digital employees, has introduced operational and control risks, including the risk of potential errors in automated decision-making, challenges in oversight and accountability, increased vulnerability to system failures or cyber incidents, and the risk that these digital employees may not perform as intended under complex or unforeseen circumstances, which could materially disrupt our business operations and adversely affect our financial condition and reputation.

The evolving legal, regulatory and compliance framework for artificial intelligence both in the U.S. and internationally may impact our ability to protect our own data and intellectual property against infringing use and could require changes in our implementation of artificial intelligence technology and increase our compliance costs and the risk of non-compliance. Further, our efforts to evolve our governance, risk management and control frameworks to manage the novel and amplified risks from our use of artificial intelligence may be insufficient or ineffective, which could expose us to operational disruptions, legal and regulatory sanctions, reputational harm and adverse financial impacts. Additionally, we may not be able to control how third-party artificial intelligence that we choose to use is developed or maintained including the source and quality of the data on which such models are trained or the frequency and nature of model updates. We may also be unable to govern or protect the integrity of the data we input into such tools, with respect to how such data is retained, reused, co-mingled with other data or disclosed, even where we have sought protections with respect to these matters.

In addition, our businesses, technology and the markets in which we operate are continuously evolving. We may fail to fully understand the implications of changes in our businesses, technology, including the impacts of artificial intelligence, our industry or the financial markets or fail to adequately or timely enhance our risk framework to address those changes. Further, if our risk framework is ineffective because it fails to keep pace with changes in the industry, technology, financial markets, regulatory requirements, our businesses, our counterparties, clients or service providers or for other reasons, we could incur losses, suffer reputational damage, face significant

Weaknesses in model design, implementation or governance, issues with data quality, and the failure of our models to fully capture interdependencies among risk factors may result in incomplete, misleading or flawed outputs. To the extent that our models utilize data provided by third parties, deficiencies in the accuracy, timeliness or completeness of third-party data or the effectiveness in our controls and validation processes could further amplify these risks. Models utilizing artificial intelligence, machine learning or other emerging technologies present additional challenges, including biases in algorithms or datasets and limitations in the transparency into the generation of outputs, potentially leading to ineffective decision-making, reporting errors or other unintended consequences.

Due to shifting political priorities and novel focus areas of regulators and other governmental authorities, we could become subject to additional laws, rules, regulations and scrutiny relating to cybersecurity and data protection, digital assets, artificial intelligence and other emerging technologies, and financial market access.

We rely on certain employees with subject matter expertise to assist in the implementation of important initiatives and to support the development of new products and services, including in connection with our deployment of artificial intelligence and other technology initiatives. As focus on technology and

risk management increases in the financial industry, competition for technologists, artificial intelligence engineers and risk personnel has intensified, which could constrain our ability to execute on certain of our strategic initiatives.

Advances in technology, such as artificial intelligence driven automation, may lead to changes in the composition of our workforce. This could require us to invest in reskilling programs and to manage impacts on morale and retention as well as employment-related litigation. Relatedly, the loss of critical employees’ skills, market knowledge and industry experience, and the cost of finding replacements, particularly in competitive labor markets, have led, and may continue to lead, to an increase in labor costs, which may hurt our business. In addition, our current or future approach to in-office and remote-work arrangements may not meet the needs or expectations of our current or prospective employees, may not be perceived as favorable as compared to the arrangements offered by competitors and may not be conducive to a collaborative working environment, which could adversely affect our ability to attract, retain, develop and motivate employees. If

we are unable to continue to attract, retain, develop and motivate highly qualified employees, or manage the workforce implications of our deployment of artificial intelligence, our performance, including our competitive position, could be adversely affected.

From time to time, we have launched new lines of business, offered new products and services within existing lines of business or undertaken transformational or strategic projects. There are substantial risks and uncertainties associated with these efforts, including with respect to projects that involve the adoption of new and evolving technologies such as artificial intelligence. For example, we have devoted significant resources to building and integrating artificial intelligence solutions into our daily operations, as well as developing new technology solutions for our clients, including our initiatives related to real-time electronic payments and global collateral management, as well as Wove, our integrative wealth management advisory platform. If these technology solutions do not operate or perform as expected, are not successful, or do not produce the anticipated efficiencies, it could adversely impact our reputation, business and results of operations. Developing and providing new products and services, including those relating to digital assets, increases our operational risk exposures. These risks are often heightened for projects that rely on third-party service providers, or in connection with new technologies and asset classes, such as digital assets, that are not only new for BNY but also relatively new to the financial markets more broadly. Compared with our activities involving traditional assets, digital asset-related products or services may introduce incremental or unique risks, particularly those associated with cybersecurity exposures and third-party dependencies, as well as reputational, technology, legal and regulatory risks.

Moreover, new or disruptive technologies, such as blockchain and other distributed ledgers, as well as the introduction of new financial products such as stablecoins or advances in artificial intelligence, automation and quantum computing, may quickly impact markets and the manner in which our clients interact and transact within markets. Increased competition in any of these areas may require us to make additional capital investments in our businesses in order to remain competitive. Our failure to either anticipate, or participate in, the transformational change within a given market or adapt these technologies as successfully as our peers could make us less competitive and result in potential negative financial impact.

Reputational harm may arise from numerous sources such as: events occurring at BNY, other financial institutions or in the financial markets; the perceived failure to comply with legal and regulatory requirements or deliver appropriate standards of service and quality; the failure to appropriately describe our products and services; the way we address sustainability concerns in our business activities or in our relationships with clients; public commentary or scrutiny against us; the purported inappropriate or unlawful actions of our employees or the use of social media by our employees; the consequences of using emerging technologies, such as blockchain technology or generative artificial intelligence; alleged financial reporting irregularities involving ourselves or other large and well-known companies; perceived or actual conflicts of interest; any cybersecurity event impacting us or our customers’ data and our cybersecurity defenses and business continuity and resiliency capabilities; our association with third-party service providers that attract heightened public attention; and the failure of an affiliate, joint venture, vendor or other third party with which we do business or that facilitates our business activities to comply with laws or regulations.

4 • Record sales performance for the year • Growing number of multi-product client relationships • Successful new client acquisition • Continued investments in our new commercial model including senior talent across target countries and client segments, training and tooling Strong Execution on Strategic Priorities in 2025 Execution momentum reinforced by positive feedback loop of continuous actions driving tangible results • Launched Eliza 2.0, BNY’s AI platform; 99% of employees on Eliza • 160 enterprise AI solutions in production and 134 digital employees live • Formed several partnerships with AI industry and academia • >60 AI-related patent applications • Scaling governance for responsible use of AI • >70% of employees working in the new platforms operating model as of year-end 2025 – Transitioned ~50% of employees in 2025 • Generated ~$550mm of efficiency savings • ~$500mm of incremental investments in new client solutions, technology and our people • Hired the company’s first Chief Product and Innovation Officer and created a new product and innovation organization • Delivered several new client solutions and numerous micro-innovations • Solidified leadership in Digital Assets through multiple product launches and client mandates – E.g., stablecoin reserve custody, BNY Dreyfus Stablecoin Reserves Fund, tokenized money market funds etc. Serving our clients as One BNY Embracing AI Unlocking scale and growth across our platforms Innovating new products and solutions

5 • Implemented rigorous strategic, operational and financial reviews • Established strategic pillars and principles, created platforms operating model and new commercial organization and model • Increased investments in our culture and people, and technology • Transformed executive leadership team and established next generation of leaders • Reduced NII interest rate sensitivity • Executed “Project Catalyst” efficiency program and instilled an owner mentality • Completed several small divestitures and the acquisition of Archer • Created product and innovation organization, launched AI Hub and Eliza AI platform • Refreshed the BNY brand • Set and exceeded medium-term financial targets for phase 1 PHASE 1: Setting our Foundation Over the Past 3 Years We Set the Foundation of Our Transformation Strategic execution with attention to detail and a long-term mindset (a) 2023-2025 Medium-term Long-term

6 Debt Instrument Issuance Traditional Fund Services NAV Alternatives Fund Services NAV Custody Trade Settlement 2022 2023 2024 2025 0% 0% 2% 3% 2022 2023 2024 2025 24 30 40 160 134 2022 2023 2024 2025 Operations Productivity Enterprise AI Solutions and Digital Employees Full-time Employees Execution Enables Enhanced Business and Operating Performance... Business and operating performance metrics demonstrate the effectiveness of BNY’s strategic transformation agenda NII Sensitivity to Changes in Interest Rates(b)Organic Fee Growth(a) Deeper Client Relationships Up 100 bps rate shock vs. baseline Down 100 bps rate shock vs. baseline 51,700 53,400 51,800 48,100 2022 2023 2024 2025 2023 2024 2025 64% Number of clients who bought from ≥3 businesses Change in average unit cost (2025 vs. 2024) for select operations processes (15)% (24)% 6% (8)% 6% (8)% 3% (4)% 1% (3)% AI Solutions Digital Employees 28% 28% CAGR = (2)% (6)% (19)% Note: See page 28 in the Appendix for corresponding footnotes.

9 • Complete company-wide transition into the platforms operating model and mature in the model • Reach maturity in the new commercial model • Scale integrated, multi-platform client solutions • Advance global financial markets and infrastructure with distributed ledger and other technologies • AI for everyone, everything, everywhere – scaling organizational intelligence with enterprise and partner agents and unlocking capacity at scale with digital employees • Further improve efficiency and profitability through continued commitment to positive operating leverage We are Embarking on Our Next Phase with Strong Momentum Foundational work continues while we increasingly scale our platforms and growth ambitions to drive competitive advantages 2023-202520 3-20 5 Medium-term Long-term PHASE 2: Scaling our Platforms and Growth Ambitions

Our two core transformation programs are showing results. The new commercial model is enabling greater sales momentum and multi-product solutioning, and as we continue to transition additional parts of the company into our platforms operating model, we see the benefits of this new way of working starting to materialize. In addition, we are embracing the power of AI, which, we believe, is for everyone, everywhere and for everything. Last month we launched for all our people the next version of BNY’s AI platform, Eliza – smarter, faster and easier to use.

3 0% (1)% 6% 5% Enterprise AI Solutions and Digital Employees Eliza AI Platform Adoption 0% 0% 36% 96% FY22 FY23 FY24 1H25 5% 3% 1% 3% FY22 FY23 FY24 1H25 Expense Growth (excluding notable items) Fee Revenue Growth 3% 7% 5% 8% Total Revenue Growth Pre-tax Margin 21% 24% 31% 34% FY22 FY23 FY24 1H25 • New commercial model starting to show increasing effectiveness – Two consecutive quarters of record sales performance – Increasing number of multi-product relationships – Higher organic growth • Pace of continuous product innovation accelerating Mid-year Business Update Multi-year transformation is gaining momentum with tangible results starting to demonstrate BNY’s medium- to long-term potential BE MORE FOR OUR CLIENTS RUN OUR COMPANY BETTER POWER OUR CULTURE • Transition into platforms operating model progressing, with >50% of employees transitioned into the model as of the end of 1H25 – First platforms activated in early 2024 starting to show maturity in the model, including faster delivery times, enhanced service quality, increased innovation, along with greater efficiency • On track for ~$0.5bn of incremental investments and ~$0.5bn of efficiency savings in 2025 • Rounded out the executive leadership team • Welcoming ~3,000 interns and analysts to BNY this summer • Further expanded learning pathways • Enabling culture by embracing development and adoption of AI = Organic (a) FY23 FY24 1H25FY22 FY23 FY24 1H25FY22 24 30 40 67 0 0 0 66 FY22 FY23 FY24 1H25 = All other = AI Solutions = Digital Employees N/A N/A (a) Represents a non-GAAP measure. See pages 14 and 15 in the Appendix for the corresponding reconciliation of the non-GAAP measure of noninterest expense growth excluding notable items. Noninterest expense – GAAP year-over-year growth was 3% for the six months ended June 30, 2025, (4)% for the year ended December 31, 2024, 2% for the year ended December 31, 2023 and 13% for the year ended December 31, 2022. N/A – not applicable.

We also consider data risks in the execution of our business objectives and processes, including the development of new products and services, including AI applications. We remain committed to increasing the effectiveness of our data management practices which are designed to enable us to deliver products and services to our clients across the investment lifecycle.

EU Artificial Intelligence Act

On July 12, 2024, the EU’s Regulation on Artificial Intelligence (“AI Act”) was published in the Official Journal of the EU and came into force on Aug. 1, 2024. The AI Act will apply extraterritorially, impacting both EU and non-EU entities, and will impact BNY. The AI Act creates a pan-EU regulatory framework to manage the risks associated with the use of artificial intelligence, including with respect to financial services. The AI Act requires categorization of AI systems into four risk levels depending on their potential to harm individuals or society (unacceptable risk, high risk, limited risk, and minimal risk) and imposes obligations depending on the risk categorization, which may include data governance, documentation and recordkeeping, human oversight, testing, cybersecurity, disclosure, regulatory notification or reporting, or training. In addition, the AI Act prohibits AI that pose unacceptable risks that are abusive or contradict EU values, including AI that may be manipulative, exploitive, or discriminatory. The individual provisions of the AI Act apply on a rolling basis from Feb. 2, 2025 to Aug. 2, 2027. BNY has evaluated the impact of the AI Act and has established an implementation program designed to operationalize the regulatory requirements applicable to BNY within required time frames.

SEC Conflicts of Interest Rule for Use of Artificial Intelligence by Broker-Dealers and Investment Advisers

On July 26, 2023, the SEC proposed new rules intended to address certain conflicts of interest associated with the use of “Covered Technology” by broker-dealers and investment advisers (“Firms”) in investor interactions (“Proposed AI Rules”). Covered Technology is generally described as applying to “artificial intelligence” or “AI” and is broadly defined under the Proposed AI Rules to include the use of analytical, technological, or computational functions, algorithms, models, correlation matrices, or similar methods or processes that optimize for, predict, guide, forecast, or direct investment-related behaviors or outcomes of an investor. If adopted, the Proposed AI Rules would: (i) generally apply when a Firm uses a Covered Technology in engaging or communicating with an investor, including by exercising discretion

The NYSDFS requires financial institutions regulated by NYSDFS, including The Bank of New York Mellon, to establish a cybersecurity program, adopt a written cybersecurity policy, designate a chief information security officer, address artificial intelligence risks related to cybersecurity, and have policies and procedures in place to ensure the security of information systems and non-public information accessible to, or held by, third parties. The NYSDFS rule also includes a variety of other requirements to protect the confidentiality, integrity and availability of information systems, including the annual delivery of a certificate of compliance.

•The development and use of artificial intelligence.

We are required to accurately process large numbers of transactions each day on a timely basis. The transactions we process or execute are operationally complex and can involve numerous parties, jurisdictions, regulations and systems, and, therefore, are subject to execution and processing errors and failures. In situations reliant upon manual processes, the risk of execution and processing errors and failures is heightened. Manual processes are inherently more prone to human and other processing error, malfeasance, fraud and other misconduct than automated processes. With more complex and voluminous transactions at ever increasing speeds, which present an increased risk of error or significant operational delay, we must continuously evolve and automate our processes, controls, technology, systems and workforce in a manner designed to achieve accurate and timely execution of these transactions. When errors or delays do occur, they may be difficult to detect and remediate in a timely manner. The use of automation, artificial intelligence and other emerging technologies in connection with automated processes, may amplify the impact of any such error or delay, as the failure to timely discover and respond to an operational error can have dramatic consequences, especially in connection with automated processes in light of the speed and volume of transactions involved. These risks are heightened in connection with the implementation of new products, systems or processes, which may present new risks that may not be adequately identified, or for which we may not have adequate controls. Furthermore, the risks resulting from an operational error may be heightened with respect to certain asset classes, such as some digital assets, with respect to which it may be impossible to retrieve wrongfully or erroneously transferred digital assets.

Affiliates or third parties (including their downstream service providers) with which we do business or that facilitate our business activities, including by providing data, information, technology, security or infrastructure services, have been, and could in the future continue to be, sources of execution and processing errors, breaches or loss, failures or significant operational delays. These risks may be amplified to the extent third parties (including their downstream service providers, such as those that provide data, cloud computing or other security or technology services) with which we do business have adopted the use of automation, artificial intelligence and other emerging technologies. These risks are further heightened to the extent that we rely on a limited, or otherwise concentrated, set of third parties with respect to certain processes or business activities.

Weaknesses in model design, implementation or governance may result in flawed outputs, increasing risks. Inaccuracies in input data or issues with data quality or effectiveness can further amplify these risks. To the extent that our models utilize data provided by third parties, deficiencies in the accuracy, timeliness or completeness of third-party data or the effectiveness in our controls and validation processes, could further amplify these risks. Models utilizing artificial intelligence, machine learning or other emerging technologies present additional challenges, including biases in algorithms or datasets, potentially leading to ineffective decision-making, reporting errors or other unintended consequences.

Cybersecurity incidents may occur through or as a result of system errors, lack of adequate policies and procedures, human error, software vulnerabilities (which may be unknown), potential lapses in information security practices or other irregularities, and intentional or unintentional acts by individuals or groups (including employees, vendors, customers and state actors, as well as others with malicious intent) having authorized or unauthorized access to our systems, data-bearing devices or facilities as well as the systems, devices or facilities of our clients, counterparties or third-party service providers. Malicious actors, who may see their effectiveness enhanced by the use of artificial intelligence, such as through the use of “deep-fake” technology or quantum computing, may also attempt to place individuals within BNY or fraudulently induce employees, vendors, customers or other users of our systems through social engineering, such as phishing, to disclose sensitive information in order to gain access to our data or that of our clients, or to send funds or authorize the sending of funds. A cybersecurity incident that results in the theft, loss, disclosure, use or alteration of information (which may include confidential or proprietary information), system or network failures, or unauthorized access or loss of access to information, may require us to reconstruct lost data (which may not be possible) or reimburse clients for data and credit monitoring services, or result in loss of customer business or damage to our computers or systems and those of our customers and counterparties. Further, although the application of distributed ledger technology is growing, such technology is nascent and may be vulnerable to cyberattacks or have other weaknesses, which could result in the loss of customer assets, including customer funds or custodied digital assets. Losses of certain types of assets, such as digital assets, may be distinctly difficult to recover and could subject us to customer disputes, claims for reimbursement, losses, negative publicity, reputational damage and governmental and regulatory scrutiny, investigations and enforcement actions.

Cyberattacks are expected to accelerate on a global basis in both frequency and magnitude as threat actors are becoming increasingly sophisticated in using novel techniques and tools, including artificial intelligence and other emerging technologies, that have the potential to circumvent controls, evade detection and even remove forensic evidence. Thus, the risk of an occurrence of a cybersecurity incident is inherent to a decision to invest in our company and

The development and use of artificial intelligence present risks and challenges that may adversely impact our business.

The use and development of artificial intelligence by us, our third-party vendors, clients, counterparties and other market participants in certain business processes, models, including generative artificial intelligence models, services or products may expose us to risks and potential liabilities. These risks may

occur as a result of enhanced governmental or regulatory scrutiny, litigation, ethical concerns, confidentiality or other security risks, intellectual property concerns over data rights and protection, heightened susceptibility to cyberattacks, increased frequency and severity of cyberattacks, inaccurate or biased algorithms or underlying datasets, misuse or misappropriation as well as other factors that could adversely affect our business, reputation and financial results. In addition, poor implementation of artificial intelligence, by us or our third-party providers, could subject us to additional risks that we cannot adequately predict or mitigate.

The failure to strategically embrace the potential of artificial intelligence may result in a competitive disadvantage for us. Although we are incorporating artificial intelligence technologies into some of our products, services and processes, if we cannot offer new artificial intelligence-facilitated technologies as quickly as our competitors, if our competitors develop more cost-effective solutions or other product offerings, or if we are not able to source components, such as artificial intelligence chips due to a supply chain shortage amid rising geopolitical uncertainty, we could experience a material adverse effect on our operating results, customer relationships and growth opportunities.

Furthermore, the use or adoption of artificial intelligence into our products or services may result in exposure to claims by third parties of copyright infringement or other intellectual property misappropriation, which may require us to pay compensation or license fees to third parties. The evolving legal, regulatory and compliance framework for artificial intelligence both in the U.S. and internationally may also impact our ability to protect our own data and intellectual property against infringing use and could require changes in our implementation of artificial intelligence technology and increase our compliance costs and the risk of non-compliance. Additionally, we may not be able to control how third-party artificial intelligence that we choose to use are developed or maintained, or how data we input into such tools are used or disclosed, even where we have sought protections with respect to these matters.

In the future, we could become subject to additional laws, rules and regulations, including related to the safekeeping of client assets, cybersecurity and data protection, digital assets, artificial intelligence and other emerging technologies, climate risk management and sustainability-related governance and reporting, including additional disclosure requirements with respect to sustainability-related goals, investment strategies, risk management and emissions. In addition, certain regulatory initiatives within and outside of the U.S. may overlap and/or conflict with each other, which could subject us to additional compliance costs and regulatory risk. This reflects the nature of developments relating to cybersecurity, digital assets, artificial intelligence and climate regulation, including the increased and ever shifting focus globally by regulators and other governmental authorities on these topics and the relatively uncertain, distinct and novel nature of the associated principles.

From time to time, we have launched new lines of business, offered new products and services within existing lines of business or undertaken transformational or strategic projects. There are substantial risks and uncertainties associated with these efforts, including with respect to projects that involve the adoption of new and evolving technologies such as artificial intelligence. We invest significant time and resources in developing and marketing new lines of business, products and services and executing on our transformational and strategic initiatives. For example, we have devoted significant resources to developing new technology solutions for our clients, including our initiatives related to real-time electronic payments and global collateral management, as well as Wove, our integrative wealth management advisory platform. If these technology solutions do not operate or perform as expected, are not successful, or do not produce the anticipated efficiencies, it could adversely impact our reputation, business and results of operations. Developing and providing new products and services, including those relating to digital assets, increases our operational risk exposures. These risks are often heightened for projects that rely on third-party service providers, or in connection with new technologies and asset classes, such as digital assets, that are not only new for BNY but also relatively new to the financial markets more broadly. Compared with our activities involving traditional assets, digital asset-related products or services may introduce incremental or unique risks, particularly those associated with cybersecurity exposures and third-party dependencies, as well as reputational, technology, legal and regulatory risks.

We are subject to reputational, legal, compliance and regulatory risk in the ordinary course of our business. Harm to our reputation can result from numerous sources, including adverse publicity or negative information, whether or not true, arising from events occurring at BNY, other financial institutions or in the financial markets, perceived failure to comply with legal and regulatory requirements or deliver appropriate standards of service and quality, or a failure to appropriately describe our products and services, how we address environmental, social and sustainability concerns in our business activities or in our relationships with clients, the purported inappropriate or unlawful actions of our employees or the use of social media by our employees, the consequences of using emerging technologies, such as generative artificial intelligence or blockchain technology, alleged financial reporting irregularities involving ourselves or other large and well-known companies and perceived or actual conflicts of interest. For example, a cybersecurity event impacting us or our customers’ data could have a negative impact on our reputation and customer confidence in BNY and our cybersecurity defenses and business continuity and resiliency capabilities. Our reputation could also be harmed by the failure of an affiliate, joint venture or a vendor or other third party with which we do business to comply with laws or regulations. Our reputation may be significantly damaged by adverse publicity or negative information regarding BNY, whether or not true, that may be published or broadcast by the media or posted on social media, non-mainstream news services or other internet forums. The speed and pervasiveness with which information, misinformation or rumors can be disseminated through these channels, in particular social media, may magnify risks relating to negative

5 Commercial Model Effective Cross-selling and Delivering Integrated Solutions • >20% increase in the number of strategic multi-line of business enterprise clients over the past 2 years • ~20% increase in cross-line of business referrals YoY; >30% increase in sales YoY from clients who bought from 3+ businesses Growth Investments Scaling Growth Investments including Wove, Archer, ETFs, Alternatives, Global Clearing etc. • Wove momentum accelerating with $29mm revenue booked in 2024, and an exit rate of ~$75mm at year-end • Pick-up in Archer new client wins following acquisition announcement in September • Global Clearing volumes up >10% YoY reflecting active issuance and trading as well as more clients and markets on our platform Platforms Operating Model Aligning Ourselves to our Role as a Financial Services Platform Company • ~25% of employees transitioned into the model by year-end 2024 • >80% of employees anticipated to be working in the model by year-end 2025 Digitization and AI Further Advancing Digitization and Scaling AI Hub • Driving down unit cost e.g., ~5% lower cost per custody trade, ~15% lower cost per NAV in traditional fund services over 2024 • Promoting AI tools among our workforce; ~35% of employees enabled for Eliza, BNY's AI platform, at year-end 2024 Capital Markets Issuance Activity, Trading Volumes and Volatility U.S. Wealth Market Secular Growth and Rising Complexity Alternatives Shift from Public to Private Markets and Democratization of Access Digital Assets Evolving Technology and Asset Class Outsourcing and Vendor Consolidation Trend to Leverage Scaled Platforms and Providers with Breadth of Capabilities COMPELLING MARKET TRENDS Unlocking Opportunity in 2025 Improving position to capitalize on market beta and trends while continuing to drive alpha through consistent execution of strategic priorities α CLEAR STRATEGIC PRIORITIES β

6 • Deliver Enhanced Commercial Model and Integrated Solutions • Scale Growth Investments and Continued Product Innovation • Platforms Operating Model Transition • Continued Digitization of Workflows • Leveraging New Technologies, including AI • Continue Attracting Top Talent • Further Enhance Learning & Development • Elevate Experiences & Sense of Belonging A Strong Value Proposition for our Clients, Shareholders and People Progress toward existing medium-term financial targets in 2024 reinforces our goal to meet or exceed targets through-the-cycle BE MORE FOR OUR CLIENTS RUN OUR COMPANY BETTER POWER OUR CULTURE MEDIUM-TERM FINANCIAL TARGETS ≥33% Pre-tax Margin 5.5 - 6% Tier 1 Leverage Ratio ≥23% ROTCE ~11% CET1 Ratio (a) (a) Represents a forward-looking non-GAAP financial measure. See "Cautionary Statement" on page 27 for information regarding forward-looking non-GAAP financial measures.

EU Artificial Intelligence Act

On July 12, 2024, the EU’s Regulation on Artificial Intelligence (“AI Act”) was published in the Official Journal of the EU and came into force on Aug. 1, 2024. The AI Act will apply extraterritorially, impacting both EU and non-EU entities, and will impact BNY. The AI Act creates a pan-EU regulatory framework to manage the risks associated with the use of artificial intelligence, including with respect to financial services. Under the AI Act, AI systems are categorized into four risk levels depending on their potential to harm individuals or society: unacceptable risk, high risk, limited risk, and

minimal risk, and imposes obligations depending on the risk categorization, which may include data governance, documentation and recordkeeping, human oversight, testing, cybersecurity, disclosure, regulatory notification or reporting, or training. In addition, the AI Act prohibits AI that pose unacceptable risk that are abusive or contradict EU values, including AI that may be manipulative, exploitive, or discriminatory. The individual provisions of the AI Act apply on a rolling basis from Feb. 2, 2025 to Aug. 2, 2027. BNY has evaluated the impact of the AI Act and has established an implementation program designed to operationalize the regulatory requirements applicable to BNY within required time frames.

We also consider data risks in the execution of our business objectives and processes, including the development of new products and services, including AI applications. We remain committed to increasing the effectiveness of our data management practices which are designed to enable us to deliver products and services to our clients across the investment lifecycle.

On July 26, 2023, the SEC proposed new rules intended to address certain conflicts of interest associated with the use of “Covered Technology” by broker-dealers and investment advisers (“Firms”) in investor interactions (“Proposed AI Rules”). Covered Technology is generally described as applying to “artificial intelligence” or “AI” and is broadly defined under the Proposed AI Rules to include the use of analytical, technological, or computational functions, algorithms, models, correlation matrices, or similar methods or processes that optimize for, predict, guide, forecast, or direct investment-related behaviors or outcomes of an investor. If adopted, the Proposed AI Rules would: (i) generally apply when a Firm uses a Covered Technology in engaging or communicating with an investor, including by exercising discretion with respect to an investor’s account, providing an investor with information, or soliciting an investor and (ii) require Firms to (among other things) identify conflicts of interests when using Covered Technology in interactions with investors, and adopt policies and procedures to eliminate or neutralize those conflicts of interest. We are evaluating the potential impact of the proposed rules.

We are required to accurately process large numbers of transactions each day on a timely basis. The transactions we process or execute are operationally complex and can involve numerous parties, jurisdictions, regulations and systems, and, therefore, are subject to execution and processing errors and failures. In situations reliant upon manual processes, the risk of execution and processing errors and failures is heightened. Manual processes are inherently more prone to human and other processing error, malfeasance, fraud and other misconduct than automated processes. With more complex and voluminous transactions at ever increasing speeds, which present an increased risk of error or significant operational delay, we must continuously evolve our processes, controls, systems and workforce in a manner designed to achieve accurate and timely execution of these transactions. When errors or delays do occur, they may be difficult to detect and remediate in a timely manner. The use of automation, artificial intelligence and other emerging technologies in connection with automated processes may amplify the impact of any such error or delay, as the failure to timely discover and respond to an operational error relating to an automated process can have dramatic consequences in light of the speed and volume of transactions involved. Furthermore, the risks resulting from an operational error may be heightened with respect to certain asset classes, such as some digital assets, with respect to which it may be impossible to retrieve wrongfully or erroneously transferred digital assets.

As our business areas evolve, whether due to the introduction of technology, new service offering requirements for our clients, interactions with third-party service providers, or changes in regulation relative to these service offerings, unforeseen risks materially impacting our business operations could arise. For example, we have begun to incorporate artificial intelligence technologies, including generative artificial intelligence, into some of our products, services and processes, and we may in the future expand such offerings. The use of artificial intelligence may expose us to new risks and greater potential liabilities including as a result of enhanced governmental or regulatory scrutiny, litigation, ethical concerns, confidentiality or other security risks, intellectual property concerns and data rights and protection concerns, as well as other factors that could adversely affect our business, reputation and financial results. Additionally, the technology used has become increasingly complex and relies on the continued effectiveness of the programming code and integrity of the inputted data. Rapid technological changes and competitive pressures require us to make

information, including copyrights, trademarks, patents and controls on access and distribution. These measures may not prevent misappropriation or infringement of our intellectual property or proprietary information and a resulting loss of competitive advantage. Furthermore, if a third party were to assert a claim of infringement or misappropriation of its proprietary rights, obtained through patents or otherwise, against us, we could be required to spend a significant amount of resources to defend such claims, develop alternative methods of operations, pay substantial money damages, obtain a license from the third party or possibly stop providing one or more products or services. Furthermore, given intellectual property ownership and license rights surrounding artificial intelligence, such as generative artificial intelligence, are currently not fully addressed by courts or regulators, the use or adoption of artificial intelligence into our products or services may result in exposure to claims by third parties of copyright infringement or other intellectual property misappropriation, which may require us to pay compensation or license fees to third parties. The evolving legal, regulatory and compliance framework for artificial intelligence may also impact our ability to protect our own data and intellectual property against infringing use. In addition, we conduct business in various jurisdictions that may not have comparable levels of protection for intellectual property and proprietary information as the U.S. The protection afforded in those jurisdictions may be less established and/or predictable. As a result, there may also be heightened risks associated with the potential theft of data, proprietary information, technology and intellectual property in those jurisdictions by domestic or foreign actors, including private parties and those affiliated with or controlled by state actors. Any theft of data, proprietary information, technology or intellectual property may negatively impact our operations and reputation, including disrupting our business activities in those jurisdictions.

In the future, we could become subject to additional laws, rules and regulations, including related to the safekeeping of client assets, cybersecurity and data protection, digital assets, artificial intelligence and other emerging technologies, climate risk management and ESG governance and reporting, including additional disclosure requirements with respect to sustainability-related goals, investment strategies, risk management and emissions. In addition, certain regulatory initiatives within and outside of the U.S. may overlap and/or conflict with each other, which could subject us to additional compliance costs and regulatory risk. This reflects the pace of developments relating to cybersecurity, digital assets, artificial intelligence and climate regulation, including the increased focus globally by regulators and other governmental authorities on these topics and the relatively uncertain, distinct and novel nature of the associated principles.

We are subject to reputational, legal, compliance and regulatory risk in the ordinary course of our business. Harm to our reputation can result from numerous sources, including adverse publicity or negative information, whether or not true, arising from events occurring at BNY Mellon, other financial institutions or in the financial markets, perceived failure to comply with legal and regulatory requirements or deliver appropriate standards of service and quality, or a failure to appropriately describe our products and services, how we address environmental, social and sustainability concerns in our business activities or in our relationships with clients, the purported inappropriate or unlawful actions of our employees or the use of social media by our employees, the consequences of using emerging technologies, such as generative artificial intelligence or blockchain technology, alleged financial reporting irregularities involving ourselves or other large and well-known companies and perceived conflicts of interest. For example, a cybersecurity event impacting us or our customers’ data could have a negative impact on our reputation and customer confidence in BNY Mellon and our cybersecurity defenses and business continuity and resiliency capabilities. Our reputation could also be harmed by the failure of an affiliate, joint venture or a vendor or other third party with which we do business to comply with laws or regulations. Our reputation may be significantly damaged by adverse publicity or negative information regarding BNY Mellon, whether or not true, that may be published or broadcast by the media or posted on social media, non-mainstream news services or other internet forums. The speed and pervasiveness with which information, misinformation or rumors can be disseminated through these channels, in particular social media, may magnify risks relating to negative publicity or media scrutiny. Damage to our reputation could affect the confidence of clients,

We are required to accurately process large numbers of transactions each day on a timely basis. The transactions we process or execute are operationally complex and can involve numerous parties, jurisdictions, regulations and systems, and, therefore, are subject to execution and processing errors and failures. In situations reliant upon manual processes, the risk of execution and processing errors and failures is heightened. Manual processes are inherently more prone to human and other processing error, malfeasance, fraud and other misconduct than automated processes. With more complex and voluminous transactions at ever increasing speeds, which present an increased risk of error or significant operational delay, we must continuously evolve our processes, controls, systems and workforce in a manner designed to achieve accurate and timely execution of these transactions. When errors or delays do occur, they may be difficult to detect and remediate in a timely manner. The use of automation, artificial intelligence and other emerging technologies in connection with automated processes may amplify the impact of any such error or delay, as the failure to