F N B : & FNBPA Public Disclosure 2017- October 16, 2017

F.N.B. Corporation & First National Bank of Pennsylvania

Capital Stress Test Results Disclosure

Capital Stress Testing Results covering January 1, 2017 through March 31,

2019 for F.N.B. Corporation and First National Bank of Pennsylvania under a

Hypothetical Severely Adverse Economic Scenario.

Released October 16, 2017

When we refer to "FNB," "we," "our," and "us" in this report, we meanF.N.B. Corporation (including First National Bank of Pennsylvania). When we refer to "FNBPA" or "Bank" in this report, we mean our only bank subsidiary,First National Bank of Pennsylvania, and its subsidiaries.

F.N.B. Corporation (FNB), headquartered in Pittsburgh, Pennsylvania, is a diversified financial services company operating in eight states. We hold a significant retail deposit market share in attractive markets including: Pittsburgh, Pennsylvania; Baltimore, Maryland; Cleveland, Ohio; and Charlotte, Raleigh, Durham and the Piedmont Triad (Winston-Salem, Greensboro and High Point) in North Carolina. As of June 30, 2017, we had 423 banking offices throughout Pennsylvania, Ohio, Maryland, West Virginia, North Carolina and South Carolina. We provide a full range of commercial banking, consumer banking and wealth management solutions through our subsidiary network which is led by our largest affiliate, First National Bank of Pennsylvania (FNBPA). Commercial banking solutions include corporate banking, small business banking, investment real estate financing, international banking, business credit, capital markets and lease financing. Consumer banking provides a full line of consumer banking products and services including deposit products, mortgage lending, consumer lending and a complete suite of mobile and online banking services. Wealth management services include fiduciary and brokerage services, asset management, private banking and insurance. We also operate Regency Finance Company (Regency), which had 76 consumer finance offices in Pennsylvania, Ohio, Kentucky and Tennessee as of June 30, 2017.

As of June 30, 2017, FNB had total assets of $30.8 billion and FNBPA had total assets of $30.6 billion. As such, FNBPA accounts for approximately 99 percent of FNB's assets and a majority of the variance in the stress tests. Therefore, separate explanations will not be provided.

Background

Section 165(i)(2) of the Dodd-Frank Wall Street Reform and Consumer Protection Act (DFA) requires national banks and federal savings associations with total consolidated assets of $10 billion - $50 billion to conduct the annual Dodd-Frank Act Stress Test (DFAST). This disclosure specifically addresses provisions of DFA requiring that company‐run stress test results be made publicly available.

The results of the company-run stress tests provide the Federal Reserve Bank (Fed) and the Office of the Comptroller of the Currency (OCC) with forward-looking information that will be used in bank supervision and will assist the agencies in assessing the companies' risk profile and capital adequacy. The objective of the annual company-run stress test is to ensure that banking institutions have robust, forward-looking stress testing processes that account for their unique risks, and to help ensure that institutions have sufficient capital to continue operations throughout times of economic and financial stress. The Fed and OCC intend to use the data to assess the reasonableness of the stress test results and determine whether additional analytical techniques are needed to identify, measure and monitor risk. These stress test results are also expected to support ongoing improvement in a covered institution's stress testing practices with respect to its internal assessments of capital adequacy and overall capital planning.

Considerations

DFA sets forth specific parameters and assumptions for all institutions to use regarding capital actions. For this and other reasons noted below, results contained herein may differ materially from other publications made by us or by regulatory agencies. To better understand the context of these results, the following should be considered:

Risks included in the Stress Test

FNB has established a robust risk management framework that supports ongoing enterprise-wide risk management, as well as the risk surrounding stress testing. The objective of risk management is not to eliminate risk, but to identify risk, and subsequently manage this risk effectively to preserve capital and optimize shareholder value.

Through an analysis of FNB's business units and business activities, FNB's enterprise-wide risk management (ERM) process works to identify risks inherent in our businesses. The risks identified are catalogued in a series of business risk assessments, which are stored in a database managed by ERM. FNB used this information to decide which risks should be considered material and are therefore integral to stress testing.

Through this process, FNB has identified five major categories of risk: credit risk, market risk, liquidity risk, operational risk, and compliance risk.

Summary of Stress Test Methodologies

To support the assessments and create the DFAST projections, FNB utilized multiple forms of quantitative and qualitative analysis to forecast balance sheets, income statements and capital. Business analyses, statistical modeling, and expert judgment, subject to review and challenge by the appropriate internal governing committees, were used to develop these projections as required by the regulatory bodies.

FNB subscribes to the macroeconomic data services of a leading analytics firm which supplements the national macroeconomic and market variables provided by the regulators with estimations of variables at the state level. In addition, FNB estimates certain interest rates that are not provided by the regulators and are important to the modeling of its net interest income. FNB developed several statistical models which, given the regulatory scenario variables, predict future behavior based on historical relationships between business activity and the scenario variables. In other cases, driver-based equations were used to express certain income statement items in relation to a related financial statement item based on historical proportions. Additionally, certain noninterest income and expense items were forecasted using management judgment and not deemed to vary between the regulatory scenarios. Model development included the consideration of multiple models, a review and challenge by subject matter experts, and an independent model validation process.

Description of the Severely Adverse Economic Scenario

The Severely Adverse scenario is characterized by a substantial weakening in economic activity in 2017 (-5.1 percent to -7.5 percent growth rates), followed by a recovery in mid-2018 to 2019 (+3.0 percent to +3.9 percent growth rates). The unemployment rate reverses its 2009-2016 trend and begins to sharply increase to a peak of 10.0 percent in Q3 2018, before slowly improving for the remainder of the forecast period. Global growth, inflation and interest rates follow a similar path as the U.S. with notable economic weakness experienced in Japan, but notable relative strength in the "Developing Asia" region.

Equity prices decline sharply in 2017 (-50 percent) before recovering throughout the remaining forecast period. The equity market volatility index spikes up in early 2017 to near levels seen in 2008, before moderating to near pre-forecast levels by the end of 2019. Residential housing and commercial real estate prices exhibit annual declines of -13 percent and -18 percent, respectively, in both 2017 and 2018 and then recover modestly in 2019.

Short-term interest rates decrease to near zero and remain there throughout the remaining forecast period, but do not enter negative territory. Long-term interest rates decline dramatically in early 2017 and very slowly begin to increase throughout the remaining forecast period, which causes the yield curve to steepen from 2Q 2017 forward. Corporate and mortgage spreads widen materially in 2017 before slowly narrowing throughout 2018-2019 to near pre-forecast levels.

These and other economic variables were transformed into usable inputs for our revenue, expense, and lossmodels, and into estimates that underlie our capital projections. A full list of economic variables and their values, along with a more detailed descriptionof theSeverelyAdverse economic scenario, can be found on the Fed's website.

Results for the Severely Adverse Scenario for January 1, 2017 - March 31, 2019

Capital Ratios

Consistent with assumed capital actions describedearlier in this disclosure, Table1 depicts beginning (December 31, 2016) and ending (March 31, 2019) capital ratios observed through the nine‐quarter horizon of theSeverely Adverse economic scenario compared to regulatory minimum and well-capitalized requirements. Key drivers of changes to capital levels are illustrated below.

Table 1. Capital Ratios: Beginning, Ending, and Minimum Values

Revenue, Loss, and Net Income

Table 2 depicts cumulative results forJanuary 1, 2017throughMarch 31, 2019, for theSeverely Adverse economic scenario.

Table 2. Net Income after Taxes

Loan and Lease Losses

Table 3 depicts cumulative nine‐quarter losses for loan and lease categories for theSeverely Adverse economic scenario.

Table 3. Cumulative Credit Losses for Loan and Lease Portfolios

(3) Other loans and leases primarily consists of equipment leases, overdraft losses and credit cards.

Additional Capital Ratio Components

Table 4 discloses the change in risk-weighted assets from the beginning (December 31, 2016) to the ending (March 31, 2019) of the nine‐quarter stress test horizon of the Severely Adverse economic scenario.

Table4. Risk-Weighted Assets to Assets,Beginning (December 31, 2016) andEnding (March 31, 2019) Values

FNBPA

Explanation of the Most Significant Causes for Changes in Regulatory Capital Ratios

Table 5 above reconciles the primary drivers of the change in the common equity tier 1 risk-based capital ratio from December 31, 2016 to March 31, 2019. The following factors account for much of the projected change in the regulatory capital ratios.