# Pagaya Technologies Ltd. (PGY) Informational only - not investment advice. CIK: 0001883085 SIC: 6199 Finance Services SIC breadcrumb: [Finance, Insurance, And Real Estate](/division/H/) > [SIC Major Group 61](/major-group/61/) > [SIC 6199 Finance Services](/industry/6199/) Latest 10-K filed: 2026-03-02 SEC page: https://www.sec.gov/edgar/browse/?CIK=1883085 Filing source: https://www.sec.gov/Archives/edgar/data/1883085/000188308526000018/pgy-20251231.htm ## At a glance FY2025 · period end 2025-12-31 · filed 2026-06-01 · accession 0001883085-26-000036 · source: https://data.sec.gov/api/xbrl/companyfacts/CIK0001883085.json | Metric | Value | FY | Provenance | | --- | ---: | ---: | --- | | Revenue | 1,301,360,000 USD | 2025 | verified | | Net income | 81,389,000 USD | 2025 | verified | | Assets | 1,545,914,000 USD | 2025 | verified | | Free cash flow | 224,718,000 USD | 2025 | computed | | Net margin | 6.25% | 2025 | computed | | Operating margin | 20.27% | 2025 | computed | | Revenue YoY | +26.07% | 2025 | computed | | ROE | 16.96% | 2025 | computed | Computed values are grepcent-computed from the verified facts above and may differ from ratios the company itself reports. Free cash flow = operating cash flow − capital expenditures. Net margin = net income ÷ revenue. Operating margin = operating income ÷ revenue. Revenue YoY = FY2025 revenue ÷ FY2024 revenue − 1 (consecutive fiscal years only). ROE = net income ÷ period-end stockholders' equity. No market price, no rating, no forecast on this site. Not investment advice. ### Peer percentile fingerprint | Ratio | PGY | Peer median | Percentile | N | | --- | ---: | ---: | ---: | ---: | | Net margin | 6.3% | 4.4% | 62 | 33 | | Operating margin | 20.3% | -3.5% | 80 | 21 | | Revenue growth | 26.1% | 15.2% | 64 | 34 | | FCF margin | 17.3% | -27.0% | 76 | 30 | | ROE | 17.0% | -2.1% | 88 | 33 | | ROA | 5.3% | -0.1% | 94 | 35 | | Liabilities / equity | 2.00 | 2.00 | 50 | 33 | | Current ratio | 1.80 | 2.19 | 35 | 21 | Percentile = share of the N covered peers reporting that ratio whose value is lower (ties counted half); computed among grepcent-covered companies in SIC industry 6199 Finance Services, not the whole market. A higher percentile means a higher value of the ratio, not a better company. Ratios with fewer than 8 reporting peers are omitted. Latest reported values per company; fiscal periods may differ. Descriptive arithmetic - not a score, rating, or ranking. ## Selected Fundamentals | Metric | Value | Unit | FY | Filed | | --- | ---: | --- | ---: | --- | | Revenue | 1301360000 | USD | 2025 | 2026-06-01 | | Net income | 81389000 | USD | 2025 | 2026-06-01 | | Assets | 1545914000 | USD | 2025 | 2026-06-01 | ## Financials Annual standardized facts from SEC companyfacts as of latest extracted filing date 2026-06-01. Source: https://data.sec.gov/api/xbrl/companyfacts/CIK0001883085.json. Derived margins, ratios, and free cash flow are computed from the extracted annual SEC facts. | Metric | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | | --- | ---: | ---: | ---: | ---: | ---: | ---: | | Revenue | 99,010,000 | 474,588,000 | 748,928,000 | 812,051,000 | 1,032,248,000 | 1,301,360,000 | | Net income | 14,470,000 | -91,151,000 | -302,321,000 | -128,438,000 | -401,406,000 | 81,389,000 | | Operating income | 21,253,000 | -5,809,000 | -251,505,000 | -24,400,000 | 66,840,000 | 263,827,000 | | Diluted EPS | 0.02 | -8.25 | -8.22 | -2.14 | -5.66 | 0.93 | | Operating cash flow | 4,257,000 | 49,811,000 | -40,000,000 | -21,659,000 | 47,751,000 | 238,620,000 | | Capital expenditures | 1,097,000 | 6,624,000 | 22,406,000 | 20,189,000 | 17,737,000 | 13,902,000 | | Assets | | 590,258,000 | 1,045,079,000 | 1,208,376,000 | 1,291,072,000 | 1,545,914,000 | | Liabilities | | 105,859,000 | 279,656,000 | 468,377,000 | 775,276,000 | 960,460,000 | | Stockholders' equity | | 1,292,000 | 553,520,000 | 559,721,000 | 326,491,000 | 480,017,000 | | Cash and cash equivalents | 5,066,000 | 190,778,000 | 309,793,000 | 186,478,000 | 187,921,000 | 235,329,000 | | Free cash flow | 3,160,000 | 43,187,000 | -62,406,000 | -41,848,000 | 30,014,000 | 224,718,000 | ### Ratios ROE and ROA use period-end equity/assets. Liabilities / equity uses total liabilities divided by stockholders' equity. Current ratio uses current assets divided by current liabilities when both are reported. | Metric | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | | --- | ---: | ---: | ---: | ---: | ---: | ---: | | Net margin | 14.61% | -19.21% | -40.37% | -15.82% | -38.89% | 6.25% | | Operating margin | 21.47% | -1.22% | -33.58% | -3.00% | 6.48% | 20.27% | | Return on equity | | | -54.62% | -22.95% | -122.95% | 16.96% | | Return on assets | | -15.44% | -28.93% | -10.63% | -31.09% | 5.26% | | Liabilities / equity | | 81.93 | 0.51 | 0.84 | 2.37 | 2.00 | | Current ratio | | 8.60 | 3.28 | 4.05 | 1.80 | | ## As-reported value updates 2 tracked differences above grepcent's stated thresholds were found between the earliest XBRL-filed value and the value currently on file for the same fiscal period. Ledger: /company/PGY/revisions/ ## Quarterly Quarterly standardized facts from SEC companyfacts as of latest extracted filing date 2026-07-30. Source: https://data.sec.gov/api/xbrl/companyfacts/CIK0001883085.json. Flow metrics use discrete quarter-length periods from 10-Q/10-Q/A filings. Q4 revenue and net income are derived only when annual FY and nine-month YTD facts exist for the same fiscal year; derived Q4 values are labeled. EPS Q4 is not derived. | Quarter | End date | Revenue | Net income | Diluted EPS | Method | | --- | --- | ---: | ---: | ---: | --- | | 2024-Q1 | 2024-03-31 | 245,276,000 | -21,223,000 | -0.33 | reported discrete quarter | | 2024-Q2 | 2024-06-30 | 250,344,000 | -74,785,000 | -1.04 | reported discrete quarter | | 2024-Q3 | 2024-09-30 | 257,234,000 | -67,476,000 | -0.93 | reported discrete quarter | | 2024-Q4 | 2024-12-31 | 279,394,000 | -237,922,000 | | derived Q4 = FY annual - nine-month YTD | | 2025-Q1 | 2025-03-31 | 289,989,000 | 7,893,000 | 0.10 | reported discrete quarter | | 2025-Q2 | 2025-06-30 | 326,398,000 | 16,655,000 | 0.20 | reported discrete quarter | | 2025-Q3 | 2025-09-30 | 350,165,000 | 22,545,000 | 0.23 | reported discrete quarter | | 2025-Q4 | 2025-12-31 | 334,808,000 | 34,296,000 | | derived Q4 = FY annual - nine-month YTD | | 2026-Q1 | 2026-03-31 | 317,944,000 | 24,694,000 | 0.28 | reported discrete quarter | | 2026-Q2 | 2026-06-30 | 387,042,000 | 45,273,000 | 0.49 | reported discrete quarter | ## Filed narrative (10-K & 10-Q) ## Business Verbatim Item 1 Business section from PGY's latest 10-K: [/company/PGY/business/](/company/PGY/business/). ## Risk Factors Verbatim Item 1A Risk Factors from PGY's latest 10-K: [/company/PGY/risk-factors/](/company/PGY/risk-factors/). ## Latest quarter (10-Q) Latest 10-Q source: https://www.sec.gov/Archives/edgar/data/1883085/000188308526000058/pgy-20260630.htm Extracted structurally from real Item 2 body heading to real Item 3/4 boundary. Published MD&A gate trimmed front/tail over-capture. Confidence: high Filing date: 2026-07-30 Report date: 2026-06-30 Item 2. Management’s Discussion and Analysis of Financial Condition and Results of Operations You should read the following discussion and analysis of our financial condition and results of operations together with the unaudited condensed consolidated interim financial statements included in this Quarterly Report on Form 10-Q (this “Form 10-Q”) and our audited annual consolidated financial statements as of and for the year ended December 31, 2025, and the related notes included in our Annual Report on Form 10-K filed on March 2, 2026, and as amended on April 30, 2026 and June 1, 2026 (collectively, the “2025 Annual Report on Form 10-K”). Some of the information contained in this discussion and analysis, including information with respect to our plans and strategy for our business and related financing, includes forward-looking statements that involve risks and uncertainties. As a result of many factors, including those factors set forth in the “Risk Factors” section of the 2025 Annual Report on Form 10-K, our actual results could differ materially from the results described in or implied by the forward-looking statements contained in the following discussion and analysis. In this section “we,” “us,” “our” and “Pagaya” refer to Pagaya Technologies Ltd. Company Overview Pagaya’s mission is to deliver more financial opportunity to more people, more often. We believe our mission will be accomplished by becoming the trusted lending technology partner for the consumer finance ecosystem, with an expansive product suite (the fee-generating side of our business) fueled by effective and efficient capital and risk management (the capital efficiency side of our business). Both sides of our business working harmoniously to meet the complex needs of the leading financial institutions. We are a product-focused technology company that deploys sophisticated data science and proprietary, AI-powered technology to enable better outcomes for financial institutions, their existing and potential customers, and institutional or sophisticated investors. We have built, and we are continuing to scale, a leading AI and data network for the benefit of financial services and other service providers, their customers, and investors. Services providers integrated in our network, which we refer to as our ‘‘Partners,’’ range from high-growth financial technology companies to incumbent banks and financial institutions. We believe Partners benefit from our network to extend financial products to their customers, in turn helping those customers fulfill their financial needs. These assets originated by Partners with the assistance of Pagaya’s AI technology are eligible to be acquired by (i) investment funds managed or advised by Pagaya or one of its affiliates, (ii) asset backed securitization (“ABS”) vehicles sponsored or administered by Pagaya or one of its affiliates, (iii) special purpose vehicles established by third-party investors to facilitate the purchase of assets under forward flow agreements and (iv) other similar vehicles (“Financing Vehicles”). In recent years, investments in digitization have improved the front-end delivery of financial products, upgrading customer experience and convenience. Notwithstanding these advances, we believe underlying approaches to the determination of creditworthiness for financial products are often outdated and overly manual. In our experience, providers of financial services tend to utilize a limited number of factors to make decisions, operate with siloed technology infrastructure and have data limited to their own experience. As a result, we believe financial services providers approve a smaller proportion of their application volume than is possible with the benefit of modern technology, such as our AI technology and data network. At our core, we are a technology company that deploys data science and technology to drive better results across the financial ecosystem. We believe our solution drives a “win-win-win” for Partners, their customers and potential customers, and investors. First, by utilizing our network, Partners are able to approve more customer applications, which we believe drives superior revenue growth, enhanced brand affinity, opportunities to promote other financial products and decreased unit-level customer acquisition costs. Partners realize these benefits with limited incremental risk or funding requirements. Second, Partners’ customers benefit from enhanced and more convenient access to financial products. Third, investors benefit through gaining exposure to these assets originated by Partners with the assistance of our AI technology and acquired by the Financing Vehicles through our network. Our Economic Model Pagaya’s revenues are primarily derived from Network Volume. We define Network Volume as the gross dollar value of assets originated by our Partners with the assistance of our artificial intelligence (“AI”) technology1. We generate revenue from network AI fees, contract fees, interest income and investment income. Revenue from fees is comprised of network AI fees and contract fees. Network AI fees can be further broken down into two fee streams, including AI integration fees and capital markets 1 Our proprietary technology uses machine learning models as a subset of artificial intelligence that go through extensive testing, validation, and governance processes before they can be used or modified. The machine learning models are static and do not have the ability to self-correct, self-improve, and/or learn over time. Any change to the models requires human intervention, testing, validation, and governance approvals before a change can be made. 28 Table of Contents execution fees. We primarily earn AI integration fees for the creation and delivery of the assets that comprise our Network Volume. Capital markets execution and contract fees are primarily earned from investors. Multiple funding channels are utilized to enable the purchase of network assets from our Partners, such as asset backed securitizations and forward flow arrangements. Capital markets execution fees are primarily earned from the market pricing of ABS transactions, as well as upon the execution of forward flow transactions, while contract fees are management, performance and similar fees. Additionally, we earn interest income from our investments in loans and securities, including risk retention holdings and additional investments we may make in our sponsored asset backed securitizations, and from our corporate cash balances. We earn investment income associated with our ownership interests in certain investment fund where Pagaya is the Registered Investment Advisor (“RIA”) and other proprietary investments. We incur costs when Network Volume is acquired by the Financing Vehicles. These costs, which we refer to as ‘‘Production Costs,’’ compensate our Partners for acquiring and originating assets. Accordingly, the amount and growth of our Production Costs are highly correlated to Network Volume. An important operating metric to evaluate the success of our economic model, therefore, is FRLPC, or Fee Revenue Less Production Costs. FRLPC is a not calculated in accordance with generally accepted accounting principles in the U.S. (“GAAP”). See the section below entitled “Reconciliation of Non-GAAP Financial Measures” for a description and reconciliation of this measure to the most directly comparable GAAP measure. Additionally, we have built what we believe to be a leading data science and AI organization that has enabled us to assist our Partners as they make decisions to extend credit to consumers. Excluding Production Costs, headcount, technology overhead and research and development expenses represent the most significant portion of our expenses. Key Factors Affecting Our Performance Expanded Usage of Our Network by Our Existing Partners Our AI technology typically enables Partners to convert a larger proportion of their application volume into originated loans, enabling them to expand their ecosystem and generate incremental revenues. Our Partners have historically seen rapid scaling of origination volume on our network shortly after onboarding and the contribution of Pagaya’s network to Partners’ total origination volume tends to increase over time. Additionally, we continue to introduce and develop new asset types, products and services, enabling Partners to expand their relationship with Pagaya and further increase origination volumes. Adoption of Our Network by New Partners We devote significant time to, and have a team that focuses on, onboarding and managing Partners to our network. We believe that our success in adding new Partners to our network is driven by our distinctive value proposition: driving significant revenue uplift to our Partners at limited incremental cost or credit risk to the Partner. Our success adding new Partners has contributed to our overall Network Volume growth and driven our ability to rapidly scale new asset classes and products. Continued Improvements to Our AI Technology We believe our historical growth has been significantly influenced by improvements to our AI technology, which are in turn driven both by the deepening of our proprietary data network and the strengthening of our AI technology. As our existing Partners grow their usage of our network, new Partners join our network, and as we expand our network into new asset classes and products, the value of our data asset increases. Our technology improvements thus benefit from a flywheel effect that is characteristic of AI technology, in that improvements are derived from a continually increasing base of training data for our technology. We have found, and we expect to continue to experience, that more data leads to more efficient pricing and greater Network Volume. Since inception, we have evaluated more than $4.2 trillion in application volume. In addition to the accumulation of data, we make improvements to our technology by leveraging the experience of our research and development specialists. Our research team is central to accelerating the sophistication of our AI technology and expanding into new markets and use cases. We are reliant on these experts’ success in making these improvements to our technology over time. Availability and Pricing of Funding from Investors 29 Table of Contents Regardless of market conditions, the availability and pricing of funding from investors is critical to our growth. We have diversified our investor network and will continue to seek to further diversify our investor base. For the six months ended June 30, 2026 and 2025, our top 5 investors collectively accounted for approximately 44% and 52%, respectively, of our total funding. Performance of Assets Originated with the Assistance of Our Proprietary Technology The availability of funding from investors is a function of demand for consumer credit, as well as the performance of such assets originated with the assistance of our AI technology and purchased by Financing Vehicles. Our AI technology and data-driven insights are designed to enable relative outperformance versus the broader market. We believe that investors in Financing Vehicles view our AI technology as an important component in delivering assets that meet their investment criteria. Impact of Macroeconomic Cycles and Global and Regional Conditions We expect economic cycles to affect our financial performance and related metrics. Macroeconomic conditions, including persistent inflation, elevated interest rates, supply chain constraints, geopolitical tensions, climate-related disruptions, and evolving global conflicts, may affect consumer demand for financial products, our Partners’ ability to generate and convert customer application volume, and the availability and cost of funding from investors through our Financing Vehicles. Geopolitical instability persists in the Middle East and Eastern Europe. T [Excerpt truncated for page length; source filing is linked above.] ## Latest 10-K MD&A (excerpt) Latest 10-K Item 7 source: https://www.sec.gov/Archives/edgar/data/1883085/000188308526000018/pgy-20251231.htm Complete FY 2025 MD&A: /company/PGY/mda/fy2025/ Extracted structurally from real Item 7 body heading to real Item 7A/8 boundary. Confidence: high Filing date: 2026-03-02 Report date: 2025-12-31 Item 7. Management's Discussion and Analysis of Financial Condition and Results of Operations The following discussion and analysis should be read in conjunction with this Annual Report and our consolidated financial statements and the related notes contained elsewhere in this Annual Report. This discussion and analysis may contain forward-looking statements based upon current expectations that involve risks and uncertainties. Our actual results may differ materially from those anticipated in these forward-looking statements as a result of various factors, including those set forth in “Item 1A.—Risk Factors” of this Annual Report. Pursuant to the FAST Act Modernization and Simplification of Regulation S-K, discussions related to the results of operations for the year ended December 31, 2024 in comparison to the year ended December 31, 2023 have been omitted. For such omitted discussions, refer to Pagaya’s Operating Results included in the Annual Report on Form 10-K filed with the SEC on March 12, 2025. Company Overview 64 Table of Contents Pagaya’s mission is to deliver more financial opportunity to more people, more often. We believe our mission will be accomplished by becoming the trusted lending technology partner for the consumer finance ecosystem, with an expansive product suite (the fee-generating side of our business) fueled by effective and efficient capital and risk management (the capital efficiency side of our business). Both sides of our business working harmoniously to meet the complex needs of the leading financial institutions. We are a product-focused technology company that deploys sophisticated data science and proprietary, AI-powered technology to enable better outcomes for financial institutions, their existing and potential customers, and institutional or sophisticated investors. We have built, and we are continuing to scale, a leading AI and data network for the benefit of financial services and other service providers, their customers, and investors. Services providers integrated in our network, which we refer to as our ‘‘Partners,’’ range from high-growth financial technology companies to incumbent banks and financial institutions. We believe Partners benefit from our network to extend financial products to their customers, in turn helping those customers fulfill their financial needs. These assets originated by Partners with the assistance of Pagaya’s AI technology are eligible to be acquired by Financing Vehicles: (i) funds managed or advised by Pagaya or one of its affiliates, (ii) securitization vehicles sponsored or administered by Pagaya or one of its affiliates and (iii) other similar vehicles (“Financing Vehicles”). In recent years, investments in digitization have improved the front-end delivery of financial products, upgrading customer experience and convenience. Notwithstanding these advances, we believe underlying approaches to the determination of creditworthiness for financial products are often outdated and overly manual. In our experience, providers of financial services tend to utilize a limited number of factors to make decisions, operate with siloed technology infrastructure and have data limited to their own experience. As a result, we believe financial services providers approve a smaller proportion of their application volume than is possible with the benefit of modern technology, such as our AI technology and data network. At our core, we are a technology company that deploys data science and technology to drive better results across the financial ecosystem. We believe our solution drives a “win-win-win” for Partners, their customers and potential customers, and investors. First, by utilizing our network, Partners are able to approve more customer applications, which we believe drives superior revenue growth, enhanced brand affinity, opportunities to promote other financial products and decreased unit-level customer acquisition costs. Partners realize these benefits with limited incremental risk or funding requirements. Second, Partners’ customers benefit from enhanced and more convenient access to financial products. Third, investors benefit through gaining exposure to these assets originated by Partners with the assistance of our AI technology and acquired by the Financing Vehicles through our network. Emerging Growth Company Status On the last business day of the second quarter in 2025, the aggregate market value of the Company’s ordinary Class A shares held by non-affiliate shareholders exceeded $700 million. As a result, we are considered a “large accelerated filer” as defined in Rule 12b-2 under the Exchange Act and ceased to be an “emerging growth company” as of December 31, 2025. Due to the loss of emerging growth company status, the Company is no longer exempt from the auditor attestation requirements of Section 404(b) of the Sarbanes-Oxley Act, and our independent registered public accounting firm evaluated and reported on the effectiveness of our internal controls over financial reporting in this Annual Report. The transition to large accelerated filer status subjects the Company to accelerated filing deadlines and additional disclosure requirements, which further aligns our reporting with other large US companies for even greater transparency. Foreign Private Issuer Status The Company was previously classified as a “foreign private issuer” (“FPI”) under SEC rules; however, as of June 30, 2025, the Company determined that it no longer satisfied the criteria to be an FPI. Consequently, we will be required to comply with all of the provisions applicable to a U.S. domestic issuer under the Exchange Act. There are no material adjustments required as a result of this adjustment since we have decided to voluntarily file on U.S. domestic issuer forms with the SEC beginning in 2024. Since then, the Company has been filing its quarterly reports on Form 10-Q, current reports on Form 8-K, and its annual reports on Form 10-K. In addition, the Company has been complying with Regulation FD and the SEC’s proxy rules, with the exception of the “short-swing” profit recovery provisions of Section 16 of the Exchange Act. Beginning on January 1, 2026, our officers, directors, and principal shareholders are subject to the “short-swing” profit recovery provisions of Section 16 of the Exchange Act with respect to their purchases and sales of the Ordinary Shares. Our Economic Model 65 Table of Contents Pagaya’s revenues are primarily derived from Network Volume. We define Network Volume as the gross dollar value of assets originated by our Partners with the assistance of our artificial intelligence (“AI”) technology1 and, with respect to single-family rental operations, the gross dollar value of services, which may include the value of newly onboarded properties onto our Darwin platform. We generate revenue from network AI fees, contract fees, interest income and investment income. Revenue from fees is comprised of network AI fees and contract fees. Network AI fees can be further broken down into two fee streams: AI integration fees and capital markets execution fees. We primarily earn AI integration fees for the creation and delivery of the assets that comprise our Network Volume. Capital markets execution and contract fees are primarily earned from investors. Multiple funding channels are utilized to enable the purchase of network assets from our Partners, such as asset backed securitizations and forward flow arrangements. Capital markets execution fees are primarily earned from the market pricing of ABS transactions, as well as upon the execution of forward flow transactions, while contract fees are management, performance and similar fees. Additionally, we earn interest income from our risk retention holdings and our corporate cash balances and investment income associated with our ownership interests in certain Financing Vehicles and other proprietary investments. We incur costs when Network Volume is acquired by the Financing Vehicles. These costs, which we refer to as ‘‘Production Costs,’’ compensate our Partners for acquiring and originating assets. Accordingly, the amount and growth of our Production Costs are highly correlated to Network Volume. An important operating metric to evaluate the success of our economic model, therefore, is FRLPC, or fee revenue less Production Costs. Additionally, we have built what we believe to be a leading data science and AI organization that has enabled us to assist our Partners as they make decisions to extend credit to consumers or for the identification and purchase, or property management, of single-family rental properties. Excluding Production Costs, headcount, technology overhead and research and development expenses represent the significant portion of our expenses. Key Factors Affecting Our Performance Expanded Usage of Our Network by Our Existing Partners Our AI technology typically enables Partners to convert a larger proportion of their application volume into originated loans, enabling them to expand their ecosystem and generate incremental revenues. Our Partners have historically seen rapid scaling of origination volume on our network shortly after onboarding and the contribution of Pagaya’s network to Partners’ total origination volume tends to increase over time. Additionally, we continue to introduce and develop new asset types, products and services, enabling Partners to expand their relationship with Pagaya and further increase origination volumes. Adoption of Our Network by New Partners We devote significant time to, and have a team that focuses on, onboarding and managing Partners to our network. We believe that our success in adding new Partners to our network is driven by our distinctive value proposition: driving significant revenue uplift to our Partners at limited incremental cost or credit risk to the Partner. Our success adding new Partners has contributed to our overall Network Volume growth and driven our ability to rapidly scale new asset classes. Continued Improvements to Our AI Technology We believe our historical growth has been significantly influenced by improvements to our AI technology, which are in turn driven both by the deepening of our proprietary data network and the strengthening of our AI technology. As our existing Partners grow their usage of our network, new Partners join our network, and as we expand our network into new asset classes, the value of our data asset increases. Our technology improvements thus benefit from a flywheel effect that is characteristic of AI technology, in that improvements are derived from a continually increasing base of training data for our technology. We have found, and we expect to continue to experience, that more data leads to more efficient pricing and greater Network Volume. Since inception, we have evaluated more than $3.6 trillion in application volume. 1 Our proprietary technology uses machine learning models as a subset of artificial intelligence that go through extensive testing, validation, and governance processes before they can be used or modified. The machine learning models are static and do not have the ability to self-correct, self-improve, and/or learn over time. Any change to the models requires human intervention, testing, validation, and governance approvals before a change can be made. 66 Table of Contents In addition to the accumulation of data, we make improvements to our technology by leveraging the experience of our research and development specialists. Our research team is central to accelerating the sophistication of our AI technology and expanding into new markets and use cases. We are reliant on these experts’ success in making these improvements to our technology over time. Availability and Pricing of Funding from Investors Regardless of market conditions, the availability and pricing of funding from investors is critical to our growth. We have diver [Excerpt truncated for page length; the complete text is on the linked full-MD&A page.] Read the full FY 2025 MD&A: /company/PGY/mda/fy2025/ All MD&A years: /company/PGY/mda/ ## MD&A history Prior-year 10-K MD&A spans are extracted from SEC filings with the same bounded parser used for the latest filing. Each year's full verbatim text is on its own sub-page. - [FY 2024 MD&A](/company/PGY/mda/fy2024/): filed 2025-03-12; accession 0001883085-25-000050 (https://www.sec.gov/Archives/edgar/data/1883085/000188308525000050/pgy-20241231.htm) - [FY 2023 MD&A](/company/PGY/mda/fy2023/): filed 2024-04-25; accession 0001883085-24-000060 (https://www.sec.gov/Archives/edgar/data/1883085/000188308524000060/pgy-20231231.htm) ## Macro cross-references Indicators mapped to this company's SIC classification (industry 6199 Finance Services) by grepcent's deterministic macro-sector crosswalk. A navigational mapping, not a statistical or causal claim. - [M2SL](/indicator/M2SL/): M2 - [FEDFUNDS](/indicator/FEDFUNDS/): Federal Funds Effective Rate - [DFEDTARU](/indicator/DFEDTARU/): Federal Funds Target Range - Upper Limit - [DGS2](/indicator/DGS2/): Market Yield on U.S. Treasury Securities at 2-Year Constant Maturity - [DGS10](/indicator/DGS10/): Market Yield on U.S. Treasury Securities at 10-Year Constant Maturity - [T10Y2Y](/indicator/T10Y2Y/): 10-Year Treasury Constant Maturity Minus 2-Year Treasury Constant Maturity - [HOUST](/indicator/HOUST/): New Privately-Owned Housing Units Started: Total Units - [PERMIT](/indicator/PERMIT/): New Privately-Owned Housing Units Authorized in Permit-Issuing Places: Total Units Macro-to-micro threads including this sector: [Interest rates & the Fed](/thread/interest-rates-fed/), [Money & trade](/thread/money-trade/), [Consumer & credit](/thread/consumer-credit/), [Government finances](/thread/government-finances/), [Sector employment](/thread/sector-employment/). All macro indicators: /indicators/ ## For LLMs & downloads Markdown twin: /company/PGY.md · JSON record: /company/PGY.json · verified financials: /company/PGY/financials.json / /company/PGY/financials.csv · machine TOC for the whole site: /llms.txt