NTRSNorthern Trust

We use various systems and models, including AI-powered solutions, in analyzing and monitoring several risk categories, as well as for other business purposes. While we assess and improve these systems and models on an ongoing basis, there can be no assurance that they, along with other related controls, will effectively mitigate risk under all circumstances, or that they will adequately mitigate any risk or loss to us. As with any systems and models, there are inherent limitations because they involve techniques and judgments that cannot anticipate every economic and financial outcome in the markets in which we operate, nor can they anticipate the specifics and timing of such outcomes. Further, these systems and models may fail to quantify accurately the magnitude of the risks we face or they may not be effective against all types of risk, including risks that are unidentified or unanticipated. Our measurement methodologies rely on many assumptions and historical analyses and correlations. These assumptions may be incorrect, and the historical correlations on which we rely may not continue to be relevant. Models based on historical data sets might not be accurate predicators predictors of future outcomes and their ability to appropriately predict future outcomes may degrade over time due to limited historical patterns, extreme or unanticipated market movements or customer behavior and liquidity, especially during severe market downturns or stress events (e.g., geopolitical events or pandemics). Consequently, the measurements that we make may not adequately capture or express the true risk profiles of our businesses or provide accurate data for other business purposes, each of which ultimately could have a negative impact on our business, financial condition and results of operations. Errors in the underlying model or model assumptions, or inadequate model assumptions, could result in unanticipated and adverse consequences, including material loss or noncompliance with regulatory requirements or expectations. In addition, the use of generative AI, a relatively new and emerging technology in the early stages of commercial use, exposes us to additional risks, such as damage to our reputation, competitive position, and business, legal and regulatory risks and additional costs. For example, generative AI has been known to produce false or “hallucinatory” inferences or output, and certain generative AI uses machine learning and predictive analytics, which can create inaccurate, incomplete, or misleading content, unintended biases, and other discriminatory or unexpected results, errors or inadequacies, any of which may not be easily detectable. Additionally, to the extent that we do not have sufficient rights to use the data or other material or content used in or produced by the AI tools used in our business, or if we experience cybersecurity incidents in connection with our use of AI, it could adversely affect our reputation and expose us to legal liability or regulatory risk, including with respect to third-party intellectual property, privacy, data protection and cybersecurity, publicity, contractual or other rights. Despite internal policies in place with respect to the usage of AI, if any of our employees or service providers were to use any third-party AI-powered software in connection with our business or the services they provide to us, it may lead to the inadvertent disclosure or incorporation of our confidential information into publicly available training set, which may impact our ability to realize the benefit of, or adequately maintain, protect and enforce our intellectual property or confidential information, harming our competitive position and business. We may not be able to sufficiently mitigate or detect any of the foregoing limitations or risks given our and other market participant’s lack of experience with using AI, the pace of technological change, and rapid adoption of AI by our business partners and competitors. As the utilization of AI becomes more prevalent, we anticipate that it will continue to present new or unanticipated ethical, reputational, technical, operational, legal, competitive, and regulatory issues, among others. As a result, the challenges presented with our use of AI could adversely affect our business, financial condition, and results of operations.

Nonaccrual Loans and Recognition of Income. Interest income on loans is recorded on an accrual basis unless, in the opinion of management, there is a question as to the ability of the debtor to meet the terms of the loan agreement, or interest or principal is 90 days or more contractually past due and the loan is not well-secured and in the process of collection. Loans meeting such criteria are classified as nonaccrual, and interest income is recorded on a cash basis. Past due status is based on how long since the contractual due date a principal or interest payment has been past due. For disclosure purposes, loans that are 29 days past due or less are reported as current. At the time a loan is determined to be nonaccrual, interest accrued but not collected is reversed against interest income in the current period. Interest collected on nonaccrual loans is applied to principal unless, in the opinion of management, collectability of principal is not in doubt. Management’s assessment of indicators of loan collectability, and its policies relative to the recognition of interest income, including the suspension and subsequent resumption of income recognition, do not meaningfully vary between the different loan classes. Nonaccrual loans are returned to performing status when factors indicating doubtful collectability no longer exist. Factors considered in returning a loan to performing status are consistent across all classes of loans and, in accordance with regulatory guidance, relate primarily to expected payment performance. A loan is eligible to be returned to performing status when: (i) no principal or interest that is due is unpaid and repayment of the remaining contractual principal and interest is expected or (ii) the loan has otherwise become well-secured (possessing realizable value sufficient to discharge the debt, including accrued interest, in full) and is in the process of collection (through action reasonably expected to result in debt repayment or restoration to a current status in the near future). A loan that has not been brought fully current may be restored to performing status provided there has been a sustained period of repayment performance (generally a minimum of six payment periods) by the borrower in accordance with the contractual terms, and Northern Trust is reasonably assured of repayment within a reasonable period of time. Additionally, a loan that has been formally restructured so as to be reasonably assured of repayment and performance according to its modified terms may be returned to accrual status, provided there was a well-documented credit evaluation of the borrower’s financial condition and prospects of repayment under the revised terms, and there has been a sustained period of repayment performance (generally a minimum of six payment periods) under the revised terms.

In 2015, Northern Trust Fiduciary Services (Guernsey) Limited (NTFS), an indirect subsidiary of the Corporation, was charged by a French investigating magistrate judge with complicity in estate tax fraud in connection with the administration of two trusts for which it serves as trustee. Charges also were brought against a number of other persons and entities related to this matter. NTFS provided no tax advice and was not involved in the preparation or filing of the challenged estate tax filings in this case. In 2017, a French court found no estate tax fraud had occurred and NTFS and all other persons and entities charged were acquitted. The Public Prosecutor’s Office of France appealed the court decision and in June 2018 a French appellate court issued its opinion on the matter, acquitting all persons and entities charged, including NTFS. In January 2021, the Cour de Cassation, the highest court in France, reversed the June 2018 appellate court ruling, requiring a re-trial at the appellate court level. This re-trial concluded in October 2023. On March 5, 2024 2024, the appellate court rendered a judgment against all defendants, including NTFS. NTFS was ordered to pay a fine of €187,500 in conjunction with the judgment. In addition, the court ordered that certain of those convicted in relation to tax fraud or aiding and abetting tax fraud, including NTFS, are jointly and severally liable for any allegedly unpaid estate taxes owing, plus penalties and interest. NTFS provided no tax advice and was not involved in the preparation or filing of the challenged estate tax filings in this case. Further, NTFS believes it acted in accordance with all applicable laws and fully complied with its fiduciary duties. Accordingly, NTFS filed an appeal of the judgment on March 5, 2024. Under applicable law, upon On February 4, 2026, the filing by NTFS Cour de Cassation affirmed the appellate court’s judgment against all of its appeal, the judgment, as well as its effects (including defendants, including NTFS. The determination of the fine and parties’ joint and several liability) will be stayed liability for the unpaid estate taxes owing, plus penalties and interest, is dependent on a final decision in a separate proceeding still pending before the outcome of the appeal. tax courts.

There was a negative Provision for Credit Losses of $7.5 million in 2025, as compared to a negative Provision for Credit Losses of $3.0 million in 2024, as compared to a Provision for Credit Losses of $24.5 million in 2023. 2024. The negative provision during 2024 2025 resulted primarily from decreases in both individual and collective reserves. The decrease in individual reserves was driven by one Commercial loan charge-off. The a decrease in collective reserves was for the Commercial Real Estate (CRE) portfolio driven by an improved industry outlook, partially offset by an increase in specific reserves related to a small number of non-performing loans. The prior-year negative provision primarily reflected a decrease in held to maturity securities collective reserves driven by methodology changes and improvements in the held to maturity securities portfolio quality quality; partially offset by an increase in the Commercial Real Estate (CRE) CRE portfolio, driven by deterioration in portfolio quality. The prior-year provision primarily reflected an increase in the reserve evaluated on a collective basis within the CRE portfolio, driven by an increase in the size and duration of the portfolio, weaker economic projections for the industry, methodology updates, and credit quality deterioration on a small number of loans.