Q3 2025 Intercontinental Exchange Inc Earnings Call
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I'll now hand, joy that cochlear Gonzales manager of Investor Relations to begin. Please go ahead.
Good morning, Ice's third quarter 2025 earnings release and presentation can be found in the investors section of our dot com.
Is that also will be archived and our call will be available for replay.
Today's call May contain forward looking statements. These statements, which we undertake no obligation to update represent our current judgment and are subject to risks assumptions and uncertainties.
For a description of the risks that could cause our results to differ materially from those described in forward looking statements. Please refer to our 2024 Form 10-K, 2025 third quarter Form 10-Q, and other filings with the SEC.
Speaker #1: Journey .
Speaker #2: By building and implementing tools to drive efficiency and deliver enhanced analytical insights for Ice and our customers . We are now taking the next step by combining our pursuit of workflow automation across our business processes with the solutions we provide to our clients through generative and energetic AI .
In our earnings supplement we refer to certain non-GAAP measures. We believe our non-GAAP measures are more reflective of our cash operations and core business performance, you'll find a reconciliation to the equivalent GAAP terms into earnings materials. When used on this call net revenue refers to revenue net of transaction based expenses and adjusted earnings refers.
Speaker #2: Under the name of Ice Aurora . As we continue to expand our AI capabilities , we're leveraging three core strengths deep , operational , and complex workflow expertise .
Adjusted diluted earnings per share.
Throughout this presentation unless otherwise indicated references to revenue growth are on a constant currency basis.
Please see the explanatory notes on the second page of the earnings supplement for additional details regarding the definition of certain items.
Speaker #2: Highly differentiated proprietary data which we believe will only grow in value , and the powerful network effects of our platform . We started with a deep understanding of our data workflows , task and document management , as well as the rules and compliance frameworks of our businesses .
With us on the call today are Jeff Sprecher Chair and CEO.
Warren Gardiner Chief Financial Officer, Ben Jackson, President Lynn Martin President of NYSE, and Chris Edmonds President of fixed income and data services I will now turn the call over to Warren. Thanks.
Speaker #2: We then conducted a risk assessment of how much automation can be applied to executing these workflows . Based on the impact , technical maturity , accuracy , and model explainability in the AI tools available .
Thanks Scott.
Good morning, everyone and thank you for joining us today I'll begin on slide four with some of the key highlights from our record third quarter results.
Third quarter adjusted earnings per share were $1 71.
Speaker #2: Balanced against the risks of automation . Similar to benchmarks used across industries to measure the scale of automation , we rank our automation within processes on a scale of 0 to 5 .
Up 10% year over year, and the best third quarter in our company's history.
Net revenues totaled $2 4 billion.
Were underpinned by a 5% increase in recurring revenue.
Speaker #2: At zero . The process is entirely manual . At five , the process is fully automated , including exception handling , without requiring human input .
This recurring revenue growth was fueled by a 9% rise in exchange data and a 7% uplift in fixed income and data services, both reflecting sustained demand for our high value proprietary data offerings.
Speaker #2: We are applying this model to every workflow across ice , bottom up , measuring exactly where we are today in terms of the maturity of AI models , automating workflows with or without human intervention , and where we can get to based on the current state of the technology .
Third quarter, adjusted operating expenses totaled $981 million.
Our disciplined cost management was further supported by approximately $15 million in one time benefits.
Evenly distributed across compensation expense and depreciation and amortization.
Speaker #2: Currently , most generative or agentic AI models at their core are best at pattern recognition , and this recognition continues to evolve . This means there is a stochastic and probabilistic accuracy to them .
After adjusting for these benefits we would have been towards the low end of our guidance range.
I also want to provide some color on the third quarter adjusted tax rate of 21%, which benefited from recent prior year tax audit settlements.
<unk> this benefit the adjusted tax rate would have been within the prior 24% to 26% guidance range and as a result, we expect the fourth quarter tax rate will normalize to between 24% and 26%.
Speaker #2: Measuring the reliability and predictability of the outcomes . AI models produce for the highly regulated businesses that we and our customers operate . There has to be an acknowledgement of how much accuracy a probabilistic outcome must have in order to be considered acceptable for full automation , versus when some level of human interaction remains necessary , especially in exception handling .
Moving to capital allocation, we returned $674 million to our shareholders during the quarter, including approximately $400 million of share repurchases. In addition, we reduced debt outstanding by roughly $175 million.
Speaker #2: Today , we have clear visibility of where we can go and are executing on this in many areas , balanced by the risk .
Reducing gross leverage to just over two nine times EBITDA.
Next I will touch on a few fourth quarter guidance items.
Speaker #2: I just outlined . That is our strategy and what our ice aurora platform is all about . And we're already seeing results across ice .
Fourth quarter adjusted operating expenses to be in the range of $1 $5 million to $1 billion $15 million sequential increase is largely driven.
By the aforementioned onetime expenses items not repeating in the fourth quarter.
Speaker #2: AI is streamlining and automating workflows across systems , accelerating product development , and dramatically accelerating the speed with which we can deliver the modernization of multiple tech stacks within ice .
Fourth quarter adjusted Nonoperating expense is expected to be between $180 million and $185 million driven by a sequential uptick in interest expense related to our October investment in poly market.
Speaker #2: Importantly , we aim to do this without compromising our adherence to information security , data management and privacy in our energy markets . The macro AI and data center expansion trend is expected to drive significant energy demand over the next decade .
As a note we funded $1 billion of that investment with CPE issuance in early October and expect to fund up to an additional $1 billion in future also utilizing existing capacity on our commercial paper program.
Now, let's move to slide five where I'll provide an overview of the performance of our exchange segment.
Speaker #2: We believe our trading and clearing platform , which offers deep liquidity and price transparency across the full energy spectrum , is uniquely positioned to support customers despite lower overall market volatility .
Third quarter net revenues totaled $1 3 billion.
Building on strong double digit growth in the prior two years.
Transaction revenues totaled $876 million importantly towards the end of October open interest across our futures and options complex surged, 16% year over year with energy futures up 14% in interest rate futures declining 37% underscoring the growing demand for our risk management tools amid shifting macroeconomic.
Speaker #2: The third quarter of this year was the second strongest third quarter in our history . Following the record quarter of a year ago .
Speaker #2: LED by continued strength in our global gas and power markets , with third quarter volumes up 8% and 18% year over year , respectively .
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Shifting to recurring revenues, which include our exchange data services and our NYSE listings business revenue sold a record $389 million up 7% year over year.
Speaker #2: As we've consistently said , open interest is a leading indicator of future growth , and we're pleased to see it continued trending higher with record futures , energy in October up 14% year over year , including 25% and 30% growth in our Brent and Tbtf benchmarks , respectively .
Underpinning growth and a record recurring revenues with 9% growth in our broader exchange data and connectivity services, which was once again led by our futures data. While also benefiting from approximately $6 million of auto related revenue that we don't anticipate will repeat in the fourth quarter.
Speaker #2: This reflects the value of our diversified energy platform . The depth of our liquidity , and the confidence customers place in our benchmarks , which serve as global price reference points across thousands of related contracts , providing trusted price transparency across geographies across our global gas portfolio , which spans North America , Europe and Asia .
In our listings business the NYSE helped to raise a market leading $20 billion in new IPO proceeds through the first three quarters of 2025.
It is worth noting that only roughly half of new Ipos have met the NYSE listing standards and these high standards remain a critical component of our 99% retention rate.
As a result of this strong performance within our exchange data business. We now expect full year growth to be towards the high end of our 4% to 5% guidance range.
Speaker #2: Volumes have increased 20% year to date . Importantly , this strong year to date performance has been underpinned by broad based strength , including a 16% increase in our North American complex .
Turning now to slide six I'll discuss our fixed income and data services segment.
Speaker #2: A 26% increase in our European portfolio , and a 27% increase in our Asian Jkm market in parallel , our power markets have seen continued growth with volumes up 21% year to date and 18% in the quarter .
Third quarter revenues totaled a record $618 million, including transaction revenues of $123 million on.
On a year over year basis ice bonds revenues increased 15% driven by 41% growth in our Muni business, which was in part driven by growing institutional adoption.
Speaker #2: This reinforces the synergy between our gas and power markets and the need for comprehensive risk management tools that offer transparency , flexibility and choice in fixed income and data services driven by multiyear investments .
Within our CDN business results were largely driven by lower member interest a direct result of the lower fed funds rate when compared to the year ago period.
Recurring revenues totaled a record $495 million and grew by 7% year over year.
Speaker #2: Our comprehensive platform delivered another quarter of record revenues , which grew 5% year over year , including 7% growth in recurring revenue and 10% growth in our data and network technology business .
In our fixed income data and analytics business record third quarter revenues of $311 million increased 5% year over year, driven by growth in pricing and reference data and our index business, which reached a record $754 billion in ETF AUM is at the end of the third quarter.
Speaker #2: Our proprietary data is the cornerstone of our business and a key differentiator in the evolving AI landscape . With over 50 years of experience , our high quality pricing and reference data serves as the foundation for what is today one of the largest providers of fixed income indices globally .
Data network technology revenues were a record increased and increased by 10% in the quarter and acceleration from 7% growth in the first half and 5% growth in 2024, driven by heightened demand for our ice global network.
Speaker #2: From benchmark indices and analytics to custom solutions , we support the full ETF ecosystem as AI becomes embedded in trading strategies across all areas of investing .
Our strategic strategic investments in data center infrastructure are paying off driven by increasing demand for data and increased capacity as well as clients for parent integrate AI into trading workflows.
Speaker #2: We expect our proprietary data to grow in strategic importance with our data sets providing a competitive edge to users of AI models that depend on precision , depth , and large quantities of historical data .
<unk> also continued to drive high single digit growth across our consolidated feeds business and our desktop solutions as we continue to realize the benefits of investments to enhance our platform.
Speaker #2: Our data is securely managed within ICE's infrastructure , protected by firewalls and entitlements . Our commercial agreements tightly control access and only permits specific use cases through authorized delivery channels .
It's worth noting that the third quarter included a few million dollars of one time revenue that we don't expect will repeat that said, we still anticipate fourth quarter revenue growth in data and network technology to be in the high single digit range and for total segment recurring revenue to be between 5% and 6% growth the fourth quarter and the full year.
Speaker #2: This approach helps ensure our data remains exclusive and strategically deployed , especially as models increasingly rely on high quality inputs to drive performance .
Please flip to slide seven where I'll discuss our mortgage technology results.
Third quarter revenues totaled $528 million up 4% year over year.
Speaker #2: In our reference data business , we're leveraging AI to process and validate documents from hundreds of sources using AI models that we thoroughly test for fit for purpose , and high probabilistic outcomes from Google , meta , Amazon , and several other AI models achieving over 95% accuracy in extracting reference data from fixed income perspectives .
Recurring revenue sold $391 million in increased on a year over year basis.
The year over year improvement was largely driven by our data and analytics business and MSP within our servicing business.
Turning to the fourth quarter, we expect revenues to remain at these levels, primarily driven by Mr. Cooper's acquisition of Flagstar and customers resetting their minimums on encompass which I'll note. This paired with the benefit of higher transaction fees. We expect these items to largely be offset by revenue from new customers coming online.
Speaker #2: This capability is a critical part of the collection process , improving both efficiency and speed of delivery , enabling us to do more with the same resources .
Transaction revenues totaled $137 million.
Speaker #2: Today , within our reference data business alone , we . Are processing roughly 40,000 documents on average per month using AI documents assessed by AI that meet predefined confidence thresholds .
Up 12% year over year, driven by double digit revenue growth related to encompass closed loans and high single digit growth for Mers registrations.
We look to the fourth quarter, it's important to remember typical seasonal impact on purchase volumes, which tend to be lighter in the fourth quarter relative to the second and third quarters.
Speaker #2: Go straight into our database for clients to consume , while those falling below the threshold are flagged for manual review and intervention . This capability is a critical part of the collection process , improving both efficiency and speed of delivery , enabling us to do more with the same resources .
In summary, the third quarter was once we once again grew revenues adjusted operating income and adjusted earnings per share building upon our record first half results and representing the best year to date performance in our company's history.
Speaker #2: We're also leveraging machine learning to power key components of our evaluated pricing . Our continuous evaluated pricing blends , trade and quote data to predict bond pricing , complementing our deep market expertise and data quality workflows .
And as we continue to strategically invest in our future. We have also returned over $1 7 billion to shareholders year to date.
As we look to the end of the year and into 2026, we remain focused on extending our track record of growth and on creating value for our shareholders I'll be happy to take your questions during Q&A, but for now hand, it over to Ben.
Speaker #2: Additional models use historical data to determine bid ask spreads across the bond universe . With machine learning capabilities significantly improving evaluation quality when measured against actual trades .
Thank you Lauren and thank you all for joining US. This morning, please turn to slide eight.
Speaker #2: In the market . Meanwhile , our Ice global network continues to set the standard for resiliency , latency , and security , connecting participants to over 750 data sources and more than 150 trading venues , including Ice in the NYSE , the ice cloud comprises state of the art data centers owned and operated by Ice and facilitates seamless integration with key third party cloud providers .
Technology and innovation have been foundational to ice since our inception.
Our approach to AI is a natural extension of that legacy.
We are using it to accelerate our existing 25 year automation journey by building and implementing tools to drive efficiency and deliver enhanced analytical insights for ice and our customers.
We are now taking the next step by combining our pursuit of workflow automation across our business processes with the solutions, we provide to our clients through generative at Gentex AI under the name of ice Aurora.
Speaker #2: All under ISIS . Cybersecurity and operational Resilience Framework . This provides our clients flexibility to access AI workloads where it makes the most sense without compromising cyber and operational controls .
Speaker #2: We continue to invest in our data centers to support business growth needs and to meet growing customer demand , including to support increased adoption of AI strategies .
As we continue to expand our AI capabilities, we're leveraging three core strengths deep.
Deep operational and complex workflow expertise highly differentiated proprietary data, which we believe will only grow in value and.
Speaker #2: This is to ensure we are accessing the most cost effective , secure and reliable infrastructure for ISIS needs and our customers needs both now and in the future across product development .
And the powerful network effects of our platform.
We started with a deep understanding of our data workflows task and document management.
Speaker #2: AI is automating data analysis , pattern recognition and repetitive processes using tools such as GitHub , Copilot , freeing product managers to focus on validation and enhancement .
As well as the rules and compliance frameworks of our businesses.
We then conducted a risk assessment of how much automation can be applied to executing these workflows based on the impact technical maturity accuracy and model explain ability in the AI tools available balanced against the risks of automation.
Speaker #2: This is already accelerated speed to market for certain products . For example , we've reduced the time to convert code for index qualification , calculation and reporting by roughly 60% , demonstrating the new innovation underway across Ice .
Similar to benchmarks used across industries to measure the scale of automation.
Speaker #2: We're utilizing utilizing AI with our new sentiment indicator data sets , including Reddit , Dow Jones and Polymarket . With Google and Meta AI models helping to process these data sets and identify patterns .
We rank our automation within processes on a scale of zero to five at.
At zero the processes entirely manual.
At five the process is fully automated including exception handling without requiring human input.
Speaker #2: While still in the development phase . These data sets are particularly attractive to market participants seeking an edge through differentiated data inputs . This illustrates how our proprietary data set is set to become increasingly vital to a trading community reliant on models to support trading decisions in our mortgage business , the use of AI is helping our efforts to streamline the home ownership experience , enhancing productivity of lending and servicing operations , improving the borrower experience with self-service workflows , reducing risk by automating compliance and quality checks across the mortgage life cycle .
We are applying this model to every workflow across ice bottom up.
Measuring exactly where we are today in terms of the maturity of AI models, automating workflows with or without human intervention.
And where we can get to based on the current state of the technology.
Currently most generative or <unk> AI models at their core are best at pattern recognition.
And this recognition continues to evolve.
This means there is a stochastic and probabilistic accuracy to them measuring the reliability and predictability of the outcomes AI models produce.
Speaker #2: All while improving recapture rates for our customers. All of this contributes to lowering the cost to originate and service the loan for our customers.
For the highly regulated businesses that we and our customers operate.
Speaker #2: A foundational part of our mortgage strategy , for example , customers using our industry standard loan servicing system , MSP save roughly 20 to 30% on the cost to service a loan based on a recently conducted customer study .
There has to be an acknowledgment of how much accuracy, a probabilistic outcome must have in order to be considered acceptable for full automation.
Versus when some level of human interaction remains necessary, especially in exception handling.
Speaker #2: And we expect this number will increase with new innovations that we have come to market or are coming to market , such as our enhanced customer service loan boarding , ice , business intelligence for servicing and our loss mitigation suite .
Today, we have clear visibility of where we can go and are executing on this in many areas balanced by the risk I just outlined.
That is our strategy and what our ice Aurora platform is all about.
Speaker #2: This execution reinforces our clients trust in us to enhance and streamline their business workflows through our workflow automation capabilities . In the third quarter , despite a tough macro backdrop , revenues increased 4% year over year , while transaction revenue grew 12% .
And we're already seeing results across ice.
AI is streamlining and automating workflows across systems accelerating product development and dramatically accelerating the speed with which we can deliver the modernization of multiple tech stacks within ice.
Importantly, we aim to do this without compromising our adherence to information security data management and privacy.
Speaker #2: We also continued to win new clients , signing on two new clients to MSP , both already on encompass and building on the two we signed in the second quarter , including .
In our energy markets, the macro AI and data center expansion trend is expected to drive significant energy demand over the next decade.
Speaker #2: We also signed 16 new encompass clients , five of them already on MSP or MSP sub servicer . We've also made significant progress in Replatforming MSP from the mainframe to ICE's modern tech stack to give us increased agility , cost efficiency and scale .
We believe our trading and clearing platform, which offers deep liquidity and price transparency across the full energy spectrum is uniquely positioned to support customers.
Despite lower overall market volatility the third quarter of this year was the second strongest third quarter in our history following the record quarter of a year ago.
Speaker #2: Here , tools such as GitHub , Copilot have helped us achieve a significant improvement in productivity , helping us rewrite the entire user interface .
Speaker #2: By the end of this year and migrate 30 million lines of code with roughly one third complete and the remaining targeted to complete within two years .
Led by continued strength in our global gas and power markets with third quarter volumes up, 8% and 18% year over year, respectively.
Speaker #2: The original estimate to complete this project was baseline to take up to seven years , similar to the move off the mainframe following our acquisition of Interactive Data Corporation with the assistance of GitHub , Copilot and other AI based code conversion tools , we have reduced the projected window to around half the time .
As we've consistently said open interest is a leading indicator of future growth.
We're pleased to see a continued trending higher with record futures energy Oi in October up 14% year over year, including 25% and 30% growth in our branch in TTS benchmarks, respectively.
Speaker #2: Originally anticipated . A significant improvement to the speed with which we can now convert old technology processes to ISIS . Modern tech stack .
This reflects the value of our diversified energy platform the depth of our liquidity and the confidence customers place in our benchmarks, which serve as global price reference points across thousands of related contracts, providing trusted price transparency across geographies.
Speaker #2: Another interesting area where we're applying our AI adoption model is in customer service . Here we have evolved our capabilities to a level of conditional automation , one where there is significant automation , but still requires human intervention for exception handling .
Across our global gas portfolio, which spans North America, Europe, and Asia volumes have increased 20% year to date.
Speaker #2: We are using generative AI to provide predictions for a customer service representative on call intent , and then call summarization . We are next applying a AI to automate department handoff for issue handling .
Shortly the strong year to date performance has been underpinned by broad based strength, including a 16% increase in our North American complex, a 26% increase in our European portfolio, and a 27% increase in our Asian JM market.
Speaker #2: Then we plan to take this to the next level by adding a chatbot designed to go beyond search capabilities . One that also executes real action , such as payment scheduling for borrower self-service within our mortgage technology , servicing digital application .
In parallel our power markets have seen continued growth with volumes up 21% year to date and 18% in the quarter.
This reinforces the synergy between our gas and power markets and the need for comprehensive risk management tools that offer transparency flexibility and choice.
Speaker #2: And we will work to expand even further with an intelligent virtual agent for certain issue resolution , where the maturity of the solutions and the quality of the probabilistic outcome is balanced against risk .
In fixed income and data services, driven by multiyear investments our comprehensive platform delivered another quarter of record revenues, which grew 5% year over year, including 7% growth in recurring revenue and 10% growth in our data and network technology business.
Speaker #2: In summary , as Ice continues to enhance our leading technology , we do so with both the client and end consumer in mind , as well .
Speaker #2: As always , considering what will make us more operationally efficient and deliver solutions that help automate workflows . With that , I'll hand it over to Jeff .
Our proprietary data is the cornerstone of our business and a key differentiator.
In the evolving AI landscape with over 50 years of experience our high quality pricing and reference data serves as the foundation for what is today one of the largest providers of fixed income indices globally.
Speaker #3: Thank you . Ben , please turn to slide nine . Given ICE's recently announced investment and business relationship with Polymarket , I thought it might be helpful to explain our thinking on the evolution of markets .
From benchmark indices and analytics to custom solutions, we support the full ETF ecosystem.
Speaker #3: Ice was an early investor in the crypto space , having been an early stage funder of Bakkt and Coinbase . We made these investments in order to stay close to the evolution of the market's use of blockchain .
As AI becomes embedded in trading strategies across all areas of investing we expect our proprietary data to grow in strategic importance with.
Speaker #3: In the case of Bakkt , we thought that there could be an acceptance of a system of tokens that adhered to a high level of then existing securities and commodities regulation .
With our datasets, providing a competitive edge to users of AI models that depend on precision depth in large quantities of historical data.
Speaker #3: We found , however , that traditional regulated financial firms were slow or unwilling to adopt tokens during a period of regulatory uncertainty , particularly where events of default would move unwanted tokens onto a financial guarantors balance sheet .
Our data is securely manage within Ics infrastructure protected by firewalls and entitlements.
Our commercial agreements tightly control access and only permits specific use cases through authorized delivery channels.
This approach helps ensure our data remains exclusive and strategically deployed especially as models increasingly rely on high quality inputs to drive performance.
Speaker #3: Current US administration and Congress have been attempting to address these uncertainties , which has caused Ice to more actively lean into the knowledge that we've accumulated over the past decade .
And our reference data business, we're leveraging AI to process and validate documents from hundreds of sources using AI models that we thoroughly test for fit for purpose and high probabilistic outcomes from Google meta Amazon and several other AI models, achieving over 95% accuracy and extracting reference.
Speaker #3: One of the significant macro trends of the past decade of blockchain investment is a rewiring of the rails of the banking system . For example , operates six clearinghouses around the world , all of which are highly regulated and which are required to operate within the limitations of local banking hours , customs and preferences on chain banking now operates globally with 24 by seven availability , allowing for instantaneous margin calls and trade liquidations .
Data from fixed income prospectus.
This capability is a critical part of the collection process, improving both efficiency and speed of delivery, enabling us to do more with the same resources.
Today within our reference data business alone we are processing roughly 40000 documents on average per month using AI.
Speaker #3: This facilitates increasing margining and lending against assets , which some cohorts of asset holders are clearly taking advantage of . With increased risk management tolerances and which places excess trade financing collateral into an omnibus stablecoin , collateral pool .
Documents assessed by AI that meet predefined confidence thresholds go straight into our database for clients to consume while those falling below the threshold are flagged for manual review in intervention.
Speaker #3: This excess collateral pool is funded by traders via the forfeiture of earnings on their collateral features that were previously unavailable to regulated clearinghouses .
This capability is a critical part of the collection process, improving both efficiency and speed of delivery, enabling us to do more with the same resources.
We're also leveraging machine learning to power a key components of our evaluated pricing.
Speaker #3: Ice decided to invest in Polymarket as we're impressed with the design of its underlying architecture of smart contracts that take advantage of this new banking infrastructure alongside our investment , we've also announced a strategic data agreement , under which Ice will become a global distributor of Polymarket highly differentiated , event driven data .
Our continuous evaluated pricing blends trading quote data to predict bond pricing.
<unk>, our deep market expertise and data quality workflows.
Additional models use historical data to determine bid ask spreads across the bond universe with machine learning capabilities significantly improving evaluation quality when measured against actual trades in the market.
Speaker #3: As the leader in non-sports prediction markets , Polymarket provides real time probabilities on events like elections , economic indicators and cultural trends , offering a powerful new layer of insight , supporting more informed decision making .
Meanwhile, our ice global network continues to set the standard for resiliency latency and security connecting participants to over 750 data sources and more than 150 trading venues, including ice and NYSE.
Speaker #3: We believe that we can polymarket acceptance into the traditional financial system by virtue of our distribution , understanding and long time customer relationships .
The ice cloud comprises state of the art Datacenters owned and operated by ice and facilitate seamless integration with key third party cloud providers, all under Ice's cyber security and operational resilience framework.
Speaker #3: And we believe Polymarket engineering team can help ICE's engineers better understand our own adoption of evolving banking technology . A relationship that is already paying dividends to both of us .
This provides our clients flexibility to access AI workloads, where it makes the most sense without compromising cyber and operational controls.
Speaker #3: Ice is in the process of rolling out an advanced clearing model for our global clearinghouses , one that we've very elegantly named ice Risk Model two , our new clearing system was built on the existing local banking and regulatory infrastructure for funds , movement and collateral management .
We continue to invest in our data centers to support business growth needs and to meet growing customer demand, including to support increased adoption of AI strategies.
This is to ensure we are accessing the most cost effective secure and reliable infrastructure for ices needs and our customers' needs both now and in the future.
Speaker #3: However , the current regulatory environment is being confronted by collateral management using tokens , which I believe will help evolve regulatory oversight to take advantage of 24 by seven capital movement , an Ice intends to be at the forefront of driving this evolution .
Cross product development AI is automating data analysis pattern recognition and repetitive processes using tools, such as Github copilot, freeing product managers to focus on validation and enhancement.
Speaker #3: Given our own use case of operating six global clearinghouses with differing collateral and regulatory environments . Such an evolution can make global clearing and trade settlement more efficient .
This is already accelerated speed to market for certain products. For example, we've reduced the time to convert code for index qualification calculation and reporting by roughly 60%.
Speaker #3: And we've seen that the efficient use of collateral typically results in increased trading volumes and transaction revenues . One does not have to look too far to see that trading volumes in the US equities markets have dramatically increased since the industry freed up collateral by moving from T+ two day to T+ one day settlement times beyond the rewiring of funds , movement , Polymarket has pioneered the rapid listing of new markets driven by real time consumer demand , traditional exchanges have been subject to government approvals of our new product launches , which at best take 30 days , and in many countries , substantially longer .
Demonstrating the new innovation underway across ice were utilized utilizing AI with our new sentiment indicators datasets, including Red at Dow Jones in soup, Polymarker with Google and meta AI models, helping to process. These datasets and identify patterns, while still in the development phase These datasets.
Are particularly attractive to market participants seeking an edge through differentiated data inputs.
This illustrates how our proprietary dataset.
Set to become increasingly vital to a trading community reliant on models to support trading decisions.
Speaker #3: Polymarket is forcing a dialogue in the U.S. on how to minimize government regulatory burdens so as not to impede innovators. We think this dialogue will ultimately benefit new product innovation for all markets, and certainly for ICE.
In our mortgage business the use of AI is helping our efforts to streamline the homeownership experience enhancing productivity of lending and servicing operations, improving the borrower experience with self service workflows, reducing risk by automated compliance and quality checks across the mortgage lifecycle, all while improving recapture rates for.
Speaker #3: Now , augmenting on Ben's comments on the adoption of artificial intelligence , we see the jagged , intelligence phenomena at play for both our own AI adoption and for that of our customers internally .
Our customers.
All of this contributes to lowering the cost to originate and service alone for our customers a foundational part of our mortgage strategy.
Speaker #3: At ICE, we have our engineers using Copilots to help them write code more effectively, particularly where the projects involve modernizing our legacy code.
For example, customers using our industry standard loan servicing system MSP save roughly 20% to 30% on the cost to service alone.
Speaker #3: However , to fully deploy production code at scale and at the latency , precision which Ice operates , we still require unique skill sets that are not now available in AI .
On a recently conducted customer study and we expect this number will increase with new innovations that we have come to market or are coming to market such as our enhanced customer service loan boarding ice business intelligence for servicing and our loss mitigation suite.
Speaker #3: So our current experience is that AI has become a good assistant for our but not a replacement . Then also highlighted our use of AI in improving our customer service .
Speaker #3: Artificial intelligence has made our help desk more efficient at diagnosing real time issues , as well as cataloging and summarizing customer inputs to create more efficient feedback loops .
This execution reinforces our clients trust us to enhance and streamline their business workflows through our workflow automation capabilities.
Speaker #3: The third area where we've deployed AI is in our data gathering and data organization , such as cataloging , bond and equity prospectuses , cleansing our data sets , and organizing unstructured data for our vast financial data offerings .
In the third quarter, despite a tough macro backdrop revenues increased 4% year over year, while transaction revenue grew 12%.
We also continued to win new clients signing on to new clients to MSP, both already on encompass and building on the two we signed in the second quarter, including the UWS.
Speaker #3: And lastly , much of the regulation that Ice is required to oversee is surveillance in the form of pattern recognition . Here again , AI tools are making our colleagues more efficient at our oversight .
We also signed 16, new encompass clients five of them already on MSP or an MSP sub servicer.
Speaker #3: So in summary , our internal use cases for AI have made our colleagues better at what they do in terms of our customer adoption of AI .
We've also made significant progress in re platforming MSP from the mainframe to Ics modern tech stack to give us increased agility cost efficiency and scale.
Speaker #3: We see that same jagged intelligence where AI is very helpful in some areas . Yet unreliable in others , where our customers interface with ice products for pattern recognition or language organization .
<unk> tools, such as Github co pilot has helped us achieve a significant improvement in productivity, helping us rewrite the entire user interface by the end of this year.
Speaker #3: We're seeing positive uptake . For example , we've seen healthy uptake of our structured and unstructured financial data offerings . Similarly , the AI tools that we've built into our mortgage network , such as our data and document automation and our customer engagement suite , have strong interests with customers adopting these tools to more efficiently target new business and minimize the cost of mortgage onboarding .
And migrate 30 million lines of code.
With roughly one third complete and the remaining targeted to complete within two years.
The original estimates to complete this project was baseline to take up to seven years similar to the move off the mainframe following our acquisition of interactive data Corporation.
With the assistance of Github Copilot and other AI base code conversion tools, we have reduced the projected window to around half. The time originally anticipated a significant improvement to the speed with which we can now convert old technology processes to Ics modern tech stack.
Speaker #3: But not to replace underwriting decisions that are subject to regulatory oversight or to replicate the vast Ice mortgage network that links the industry together , including the US Federal housing regulators , supervisory efforts and validating GSE and Federal Home Loan Bank mortgage Holdings and providing it with monthly mortgage service information .
Another interesting area, where we're applying our AI adoption model is in customer service.
Speaker #3: Finally , a number of people have speculated to me that the overall volumes of trading must have increased due to AI adoption . Well , that's possible .
Here, we have evolved our capabilities to a level of conditional automation.
One where there is significant automation, but still requires human intervention for exception handling.
Speaker #3: I believe that a significantly larger volume impact has come from capital being freed up when moving equity settlement times . One day forward , and with the expansion of retail trading leverage , that's inherent in popular one day options .
We are using generative AI to provide predictions for a customer service representative on call intern and then call summarization.
Next supplying a gentex AI to automate department handoff for issue handling.
Speaker #3: So all in all , we think the current state of AI is helping to control costs and control new hiring in and is for us at the margin , driving sales and transaction growth .
Then we plan to take this to the next level by adding a chatbot designed to go beyond search capabilities.
One that also execute real action such as payment scheduling for borrowers self service within our ice mortgage technology servicing digital application.
And we will work to expand even further with an intelligent virtual agent for certain issue resolution or the maturity of the solutions and the quality of the probabilistic outcome is balanced against risk.
In summary, as ice continues to enhance our leading technology, we do so with both the client and end consumer in mind as well as always considering what will make us more operationally efficient and deliver solutions that help automate workflows.
With that I'll hand, it over to Jack.
Thank you Ben please turn to slide nine.
Given ices recently announced investment and business relationship with poly market I thought it might be helpful to explain our thinking on the evolution of markets.
Ice was an early investor in the crypto space, having been an early stage Thunder of back and coin base. We made these investments in order to stay close to the evolution of the market's use of blockchain.
In the case of back we thought that there could be an acceptance of our system of tokens that adhere to our high level of than existing securities and commodities regulation.
We found however that traditional regulated financial firms were slow or unwilling to adopt tokens during a period of regulatory uncertainty, particularly where events of default would move unwanted tokens onto our financial guarantors balance sheet.
Current U S administration and Congress have been attempting to address these uncertainties, which has caused ice to more actively lean into the knowledge that we've accumulated over the past decade.
One of the significant macro trends of the past decade of blockchain investment is a rewiring of the rails of the banking system.
Vice for example operate six clearing houses around the world all of which are highly regulated and which are required to operate within the limitations of local banking hours customs and preferences.
On chain banking now operates globally with 24 by seven availability, allowing for instantaneous margin calls and trade liquidations.
This facilitates increasing margining and lending against assets, which some cohorts of asset holders are clearly taking advantage of with increased risk management tolerances.
And which places excess trade financing collateral into an omnibus stable coin collateral pool.
This excess collateral pool is funded by traders via the forfeiture of earnings on their collateral features that were previously unavailable to regulated clearinghouses.
Ice decided to invest in poly market as we are impressed with the design of its underlying architecture of smart contracts that take advantage of this new banking infrastructure.
Alongside our investments, we've also announced a strategic data agreement under which <unk> will become a global distributor of poly market is highly differentiated event driven data.
As the leader in non sports prediction markets Poly market provides real time probabilities on events like elections, economic indicators and cultural trends offering a powerful new layer of insight supporting more informed decision making.
We believe that we can accelerate falling market's acceptance into the traditional financial system by virtue of our distribution understanding and longtime customer relationships and we believe poly markets engineering team can help ice's engineers better understand our own adoption of evolving banking technology a relationship there.
It is already paying dividends to both of us.
Ics in the process of rolling out an advanced clearing model for our global clearing houses one that we've very elegantly named ice risk model too.
Our new clearing system was built on the existing local banking and regulatory infrastructure for funds movement and collateral management.
However, the current regulatory environment is being confronted by collateral management, using tokens, which I believe will help evolve regulatory oversight to take advantage of 24 by seven capital movement.
And ice intends to be at the forefront of driving this evolution given our own use case of operating six global clearinghouses with differing collateral and regulatory environments.
Such an evolution can make global clearing and trade settlement more efficient and we've seen that the efficient use of collateral typically results in increased trading volumes and transaction revenues.
One does not have to look too far to see the trading volumes in the U S. Equities markets have dramatically increased since the industry freed up collateral by moving from T. Plus two day to T plus one day settlement times.
Beyond the rewiring of funds movement Poly market has pioneered the rapid listing of new markets driven by real time consumer demand traditional exchange.
Exchanges have been subject to government approvals of our new product launches, which at best take 30 days and in many countries substantially longer.
Poly market is forcing a dialogue in the U S on how to minimize government regulatory burdens so as to not impede innovators. We think this dialogue will ultimately benefit new product innovation for all markets and certainly for ice.
Now augmenting on Ben's comments on the adoption of artificial intelligence, we see the jagged intelligence phenomenon at play for both our own AI adoption and for that of our customers.
Internally at ice we have our engineers using co pilots to help them write code more effectively, particularly where the projects involve modernizing our legacy code.
However to fully deploy production code at scale and at the latency precision, which ice operates we still require a unique skill sets that are not now available in AI. So our current experiences at AI has become a good assistant for our teams, but not a replacement.
Then also highlighted our use of AI and improving our customer service artificial.
Intelligence has made our help desk more efficient at diagnosing real time issues as well as cataloging and summarizing customer inputs to create more efficient feedback loops.
<unk> third area, where we deployed AI is in our data gathering and data organizations, such as cataloging bond and equity prospectuses cleansing, our datasets and organizing unstructured data for our best financial data offerings.
And lastly, much of the regulation that is required to oversee as surveillance in the form of pattern recognition.
Again, AI tools are making our colleagues more efficient at our oversight. So in summary, our internal use cases for AI have made our colleagues better at what they do.
In terms of our customer adoption of AI, we see that same jagged intelligence, where AI is very helpful. In some areas, yet unreliable and others.
Where our customers interface with ice products for pattern recognition or language organization. We're seeing positive uptake for example, we've seen healthy uptake of our structured and unstructured financial data offerings Sim.
Really the AI tools that we've built into our mortgage networks, such as our data and document automation and our customer engagement suite have strong interest with customers adopting these tools to more efficiently target new business and minimize the cost of mortgage onboarding, but.
But not to replace underwriting decisions that are subject to regulatory oversight order replicate the vast ice mortgage network that links the industry together, including the U S. Federal housing regulators supervisory efforts and validating GSE and federal home loan Bank mortgage holdings and providing it with monthly mortgage.
Service information.
Finally, a number of people have speculated to me that the overall volumes of trading must have increased due to AI adoption.
While that's possible I believe that a significantly larger volume impact has come from capital being freed up when moving equity settlement times, one day forward and with the expansion of retail trading leverage that's inherent in popular one day options.
So all in all we think the current state of AI is helping to control cost and control new hiring in.
And as for us at the margin driving sales and transaction growth.
Our record third quarter results on top of our extraordinary third quarter results of last year are another example of strong execution across our all weather platform.
We very intentionally positioned the company to provide customer solutions in numerous geographies and economic conditions to facilitate these all weather results.
I'd like to end, our prepared remarks by thanking our customers for their continued business and thank you for your trust and I would also like to thank my colleagues at ice for their contribution to the very best third quarter in our company's history. Following on our unsurpassed first half results and yielding the best year to date performance and the Companys history.
Three.
I'll now turn the call back to our moderator linear and will conduct a question and answer session until 930 eastern time.
Thank you.
Please press star followed by the number one if you'd like to ask a question and answer all your devices.
Anyone else Youll tend to speak.
Reminder, to please limit yourself to one question and jump back in queue. If you have any follow up.
Our first question today comes from Ken Worthington with Jpmorgan. Please go ahead. Your line is open.
Hi, good morning, Thanks for taking the question.
Believe it or not my question is on the impact of AI in the mortgage origination and servicing business then really following up in your prepared remarks. So maybe first how easy is it to incorporate the benefits of it.
AI and MSP and encompassed given their tech stacks look like today. So you gave some examples but can you get AI into all of the areas you need to maximize your competitiveness and then maybe secondly, do you think AI can make it easier for perspective ice mortgage technology class.
To pursue efficiency on their own.
And does the hope of new technology extend the time, it's taking for ice to sign up new encompass and MSP customers, particularly when thinking about large customers.
Thanks, Ken It's Ben I'll take this.
My.
In my mind, the best way to summarize the impact of AI.
Our mortgage origination and servicing platforms is that it's enabled us to transition these platforms.
What has historically been seen as systems of record.
To a system of intelligence.
And what do I mean, so when you think about these these core platforms.
Our orchestrating incredibly complex and highly regulated business processes and workflows.
And we alluded to it in the comments.
Multiple times, both Jeff and I did that we also have an incredible network attached to us got thousands of customers hundreds of network service providers 35000 settlement agents tens of thousands of notary as an example.
And we are orchestrating communication not only of those clients connecting to us, but as important if not more important connectivity between our clients.
And we have the proprietary information on how to orchestrate that workflow and how to make it more robust we also own and maintain the most robust compliance and underwriting guideline databases in the industry and that's the reference data that's required to really automate underwriting workflows, which we're doing through our DDA platform.
We also own and maintain the most comprehensive set of closing guidelines and rules for every county.
In the country, which enables our electronic closing in the reporting of loan transactions in the business that we acquired with simple file.
And we've also have significant proprietary data derived data offer.
Our platforms that help to inform our business intelligence models and.
Enable our clients to find more operational efficiencies and business efficiencies that our clients can can benefit from.
So you take all of this together and how we're applying AI throughout each business process from a bottom up perspective, using that Aurora process that I that I had mentioned.
Going through business process by business process understanding what the probabilistic accuracy of pattern recognition model that AI is providing and what's the business tolerance around the regulatory rules the compliance associated to how much automation can be applied versus when human intervention.
It needs to take place so we are extraordinarily well positioned.
To take advantage of this and.
It shows up in our results, we had our highest quarter of the year in terms of sales in the third quarter across our ice mortgage technology segment, we had two MSP clients both of which.
Our already on encompass signed in the last quarter and that's on top of the two that we had last quarter, including one of the largest lenders in the U S with United wholesale mortgage.
And then we had 16 encompass wins five of which are on MSP MSP sub servicers that are that are really buying into our vision of the benefits of a front to back workflow.
So we feel very well positioned and looking at the funnel behind that we feel like we're in a very strong position.
Thanks.
Thank you. Our next question comes from Dan Fannon with Jefferies.
Please go ahead.
Thanks, Another question here on mortgage or and you gave some near term comments around the fourth quarter, given flagstar, but could you elaborate a bit more on the shorter term dynamics and also pennymac, which announced in the quarter that they would also be leaving your platform over time, what that contribution is today.
Sure. Thanks for the question Dan So in terms of the third quarter, which I think is what youre referring to.
Yes, we were a little bit lower by a few million dollars. There are three real reasons for that so first and we mentioned this a little bit last quarter was there was the roll off of the typical roll off of inactive loans on MSP that came in a little bit higher than we anticipated, but that said active loans on MSP ticked higher for the first time in a few quarters to so there was a positive there on that front.
Um you know, going through business process by business process, understanding what, the probabilistic accuracy of a pattern recognition model. That AI is providing. And what's the business tolerance around the regulatory rules the compliance Associated to how much automation can be applied versus when human intervention needs to take place. So we're extraordinarily well, positioned, uh, to take advantage of this. And it shows up in our results, we had our highest order of the year. In terms of sales, in the third quarter across our ice mortgage technology segment. We had 2, uh, MSP clients, both of which, uh, are already on Encompass signed in the last quarter and that's on top of the 2 that we had last quarter, including 1 of the largest lenders in the US with the United Wholesale Mortgage. And then we had 16, Encompass wins 5 of which are on MSP or MSP subservice services.
That are that are really buying into, you know, our vision of the, the benefits of a front-to-back workflow.
In the second component of that too is and you've heard us talk a little bit. This last couple of quarters. We did have some customers renew at slightly lower minimums in than we had expected.
So we fail very well positioned and we, you know, looking at the funnel behind that we feel like we're in a very strong position.
Thank you. Our next question comes from Dan Fannon with Jefferies.
Please go ahead.
But overall, we do continue to see the discount to prior minimums narrowing versus last year and in the percent of loans above the minimums are improving which is helping our transaction fees and then third we did have some implementation with fourth and the first quarter of next year. It was really all based on customer needs, but as Ben noted we.
Thanks. Uh, another question here on mortgage. Warren, you gave some near-term comments around the fourth quarter given flag star. But could you elaborate a bit more on the shorter term Dynamics, and also Penny Mac, which announced in the quarter that they would also be leaving your platform over time. What that contribution is today.
We just noted we had the best quarter of the year for sales across the platform not all of those of course hit in the current quarter and the fourth quarter, but but certainly a good forward looking indicator for the for the business as you think about next year, so all of that together.
Nothing terribly significant on a standalone basis, but did up to a couple of revenues come in a bit lighter than and that sort of impacts the fourth quarter from a run rate standpoint, and also some of the implementations to that I noted to have an impact on the fourth quarter as well.
And then of course as you mentioned flagstar.
That will roll off in the fourth quarter, which has an impact, but we had mentioned that before.
In terms of Pennymac.
I think the way to think about that is it's probably about a half point of growth, but that won't be an impact for us until 2028 and to be clear, it's a half point on recurring revenue.
Sure. Uh thanks for the question, Dan. So in terms of the the third quarter, which is, I think is what you're referring to, um, yeah, we were a little bit lower by a few million dollars. There were 3 real reasons for that. So, first, and we mentioned this, a little bit last quarter was there was the roll off of the typical roll off of inactive loans on MSP that came in a little bit higher than we anticipated. But that said, um, active loans on MSP tick tire for the first time in a few quarters too. So there was a positive there, you know, on that front, um, in the second component of that too is and you heard us talk a little bit. This last couple quarters. We did have some customers Renew at slightly lower minimums than we than we had expected. Um, but overall we do continue to see the discount to Prior minimums narrowing versus last year. And and the percent of loans are approving which is is helping our transaction fees.
That would have an impact on but then again not until 2020 would we expect to see that.
Our next question comes from Ben.
With Barclays.
Please go ahead.
Hi, good morning, and thanks for taking the question.
Following up on Jeff's commentary on poly market I was wondering maybe first if you could give us any more details about the data licensing where redistribution arrangement, what sort of P&L impact might that look like and then maybe you bought it you took a big has taken the company can you talk a bit about your longer term plans do you have any plans to list event contracts, we've heard your competitor talking.
About that quite a bit or is this more about the partnership and maybe sorry to squeeze another one in there but to what degree is the blockchain technology itself part of the appeal rather than sort of a means to an end to access this type of trading type of.
Uh, in terms of PennyMac.
New market data points. Thank you.
Hi, This is Chris Edmonds I'll take the first part of that Jeff pick up on some of the other parts of your questions, but on the the sentiment analysis itself of the data is becoming interesting feedback loop for our clients. We've seen a tremendous demand from our clients based on our experience with the <unk> data the Dow Jones data that Ben referenced.
I think the way to think about that is it's it's probably about a half point of of growth, but that won't be an impact for us until uh 2028. And to be clear, it's a half point on recurring Revenue uh, that that would have an impact on. But and again, not till 2028, would we expect to see that?
Our next question comes from Ben Buddhist with B, please.
Please go ahead.
In his prepared comments, so now the ability to take those signals and actually create a market around that and then get the feedback loop from that activity is happening on a pilot market really gives us an opportunity for a complete ecosystem around that and thats driving the customer interest in that in and really what led us to the idea that.
We wanted to be a distributor of that data to make sure we had it in our ecosystem for our clients to use.
Yes.
I think.
As I tried to this is Jeff I think what I mentioned tried to convey in my prepared remarks was that we.
Hi, good morning, and thanks for taking the question. Um, maybe following up on Jeff's commentary on poly Market. Um, I was wondering, maybe first, if you could give us any more details about the data, uh, licensing or redistribution Arrangement, you know what, what sort of p&l impact, you know, might that look like and then maybe, you know, you bought you took a big stake in the company. Can you talk a bit about your longer term plans? Um, do you have any plans to list event contracts? We've heard your competitor talking about that quite a bit. Um, or is this more about, you know, the partnership and maybe sorry to squeeze another 1 in there, but to what degree is, you know, that the blockchain technology itself are part of the appeal rather than, you know, sort of a, a means to an end to, um, you know, access this, you know, type of trading type of, um, you know, new New Market data points. Thank you.
We really believe poly market has done something particularly innovative and special.
In the way they have historically settled.
<unk>.
Their contracts and and it's true block chain.
Non intermediate settlement between two parties sending tokens.
Hi. This is Chris Edmonds. I'll I'll take the first part of that and just pick up on some of the other parts of your questions. But on the, the sense of analysis itself of the data is becoming an interesting feedback loop for our clients. We've seen a tremendous demand from our clients based on our experience, with the Reddit data, the Dow Jones, uh, data that
<unk>.
Yeah.
A second layer that.
They've been adopting that gives them some performance capabilities and.
We wanted to learn more about that get our engineers more involved in it because because you can see the trends in traditional finance are that they are going to be more assets that are token is potentially.
In reference in his prepared comments. So now the ability to take that those signals and actually create a market around that and then get the feedback loop from that activity. That's happening on piling Market, really gives us an opportunity for a complete ecosystem around that and that's driving the customer interest in that. And, and really what led us to the to the idea that we wanted to be a distributor of that data to make sure we had it in our ecosystems, for our clients to use.
Bank deposits.
And we think that that will ultimately make its way into the clearing infrastructure and allow us to better run 24 by 7%. The same for US is as I mentioned a couple of times in my prepared remarks. The fact that we have six clearing houses means that clients tend to keep excess collateral.
All six because of the banking hours that are required to move capital around win win those particular clearinghouses are open.
And we think by having 24 by seven collateral management will be able to minimize overall collateral requirements for our customers and that will feed its way into higher trading volumes, which as we have seen that correlation and so.
Yeah, and um, I think, you know, as I tried to this is Jeff. I think what I mentioned tried to convey, in my prepared, remarks was that we really believe poly Market has done something, particularly Innovative and special. Um, in the way they have, uh, historically settled, um, uh, their contracts and uh, and, and it's true blockchain, um, non- intermediated settlement between 2 parties, uh, sending tokens. Um, on on, you know, a second layer that, uh, that that they've been adopting that that gives them some performance capabilities. And, um,
In our interest sale make our customers' trading more efficient.
I'd just say separately.
We built ice.
Over 20 years by really.
Leaning into commercial users and the workflows that they have in the supply chains that exist around the globe and.
we wanted to learn more about that, get our Engineers more involved in it because because you can see the trends in traditional Finance are that they're going to be more assets that are tokenized potentially um Bank deposits. Uh and and we will think that that will ultimately make
In helping to manage our risk of commercials.
We've never been particularly.
Potent in the retail space or even the high frequency space others have.
Focused on that and we've been very very commercial.
It's good to have a relationship with poly market, because theyre really educating us about how they have gone to market with retail customers.
How they did essentially tremendous ground game marketing with without money assets at their disposal and really created a brand and brand awareness.
With a small balance sheet.
Make its way into the clearing infrastructure and allow us to better run 24 by 7. The thing for us is, as I mentioned a couple times in my prepare remarks, the fact that we have 6, clear houses means that clients tend to keep excess collateral at all 6, because of the banking hours that are required to move Capital around. When when those particular Clearing Houses are open. And we think by having 24, by 7, collateral management will be able to minimize overall collateral, uh, requirements for our customers. And that will feed its way into uh, higher trading volumes, which is we, we have seen that correlation and so it's it's in our interest to help make our customers trading more efficient.
I would just say separately.
And so again, we admire what they've done.
We built ice.
Trying to educate them on traditional finance, while they educate us on on consumer finance and hopefully that will pay dividends for both of us down the road.
But it just made sense that.
The teams.
<unk> worked together to really educate one another in the hope that one and one makes three.
Our next question comes from Patrick <unk> with Piper Sandler.
Your line is open.
Yes.
Yes. Good morning, Thanks for taking the question, maybe just double clicking on Ben's question on poly market and just.
You know, over 20 years, by really leaning into commercial users and the workflows that they have and the supply chains that exist around the globe, uh, and helping to manage, uh, risk of commercials. We've never been particularly um, potent in the retail space or even the The High Frequency space others have uh focused on that. And we've been very, very commercial. So it's good to have a relationship with poly Market because they're really educating us about how they have gone to Market uh with retail customers um, how they did essentially.
The contract level in.
In prediction markets a lot of the volume we've seen so far has been in sports contracts, there's been a lot of lawsuits and questions about whether regulators are going to allow that to proliferate, but it seems like you know in.
You know, tremendous ground game marketing with without money assets and at their disposal. And really, you know, created a brand and brand awareness, um, with a with a small balance sheet.
In the next few years, if they do allow it to continue you can see a lot of sports book volumes move on exchange. So just wondering if what you think how do you see that playing out and what opportunity can present for poly market and ice and maybe just if you can talk about how you see sports contracts versus non sports contracts and their applicability.
Ability.
but it just made sense that uh, that the teams uh, work together to really educate 1, another, uh, and the hope that 1 in 1 makes 3
At the commercial level.
Progressing from here thanks.
Sure.
As Jeff again, I reached out to Shane.
Our next question comes from Patrick Miley with Piper Sandler, your Line's open.
<unk> poly market.
Yes, good morning.
Early in the summer after.
It became clear that debt.
The Trump administration in the U S.
Congress was going to validate much of what.
What's being done with stable coins and ultimately on the blockchain.
And it was in that environment that we began conversation and that was before the NFL football season.
We were attracted by their non sports.
Activities, where they really are a global leader.
And we really think that data and information supply chain data acts of God weather.
<unk>.
Corporate actions, we think that kind of information is going to be very very interesting to the traditional finance in fact, we know it is.
Double clicking on Ben's question on poly market and just at at kind of the contract level in prediction markets. A lot of the volume we've seen so far, has been in sports. Contracts. There's been a, you know, a lot of lawsuits and questions about whether Regulators are going to allow that to proliferate but it seems like you know, in the next few years, if they do allow it to continue, you could see a lot of sports book volumes move on Exchange. So just wondering if you you know what you think, how you see that playing out and what opportunity could present for poly market and ice and maybe just if you could talk about how you see Sports contracts versus non-sports contracts and their applicability um at the commercial level uh you know, progressing from here, thanks.
Anecdotally, Shane and I are very well aware of.
Sure. Um, this is Jeff again. Well, I reached out to Shane um the founder of poly Market.
Many institutional investors that are already scraping data, our finding data and making its way into informally into their their traditional.
Uh, early in the summer after. Um,
Decision, making.
And so.
Sports was not something that.
Uh, it became clear that uh, that the the Trump Administration and the US Congress was going to validate much of what um uh was being done.
<unk> really got our interest I think it's great for poly market.
If they can make a business around that and make earnings around that and certainly.
Longer term for our.
Our equity stake in the business that would be great, but we're not a venture firm. We don't you guys wont really reward us if we make.
A lot of money on that investment honestly I think we'll be rewarded if we can bring the underlying technologies into our workflow.
<unk> increased our sales revenue and manage our costs and so.
Long winded way of saying good for poly market if they can.
Obligate the sports complex.
Not high on our list in terms of what we're gonna contributes to them and what they will contribute to us.
Stable coins and and ultimately on the blockchain. Um, and it was in that environment that we began conversation and that was before the NFL football season, and we were attracted by their non-sports, uh, activities where they really are a global leader. And we really think that data and information supply chain data, acts of God, whether um, uh, you know, corporate actions, we think that kind of information is going to be very, very interesting to the traditional Finance. In fact, we know it is, um, anecdotally, Shane. And I are very well aware of of many institutional investors that are already, uh, scraping data or finding data and, and making its way into uh, informally into their their uh, traditional decision-making.
Next question comes from Brian <unk> with Deutsche Bank.
Please go ahead.
Okay great. Thanks. Thanks, Good morning, Thanks for taking my question.
So Sports was not something that, um, really got our interests. I think it's great for poly Market. If if, if they can, you know, make a business around that and and make
Just back to mortgage I, just want to clarify one on the <unk> outlook, but the guide of I think flat revenue <unk> <unk> was that for the whole segment.
earnings around that and certainly um you know, longer term for our Equity stake in the business that would be great but we're not a venture firm, we don't, you know, you guys won't really reward us if we make uh,
Or was that just for recurring so I know you did mentioned the seasonality in transaction fees. So if you could just verify that and then just longer term.
Outlook on that builds of the revenue synergy whats been actions so far in.
a lot of money on that investment, honestly, you know, I think we'll be rewarded if we can bring the underlying Technologies into our workflow and uh, increase our sales revenue and and and manage our
Are you sticking to the same timeline on the.
On the integration and then maybe just longer term just comments around competition in the mortgage space from.
And so, um, long-winded way of saying good for Poly Market if they can navigate the sports complex.
From the blockchain and from Buckingham providers I know, that's more futuristic, but just your thoughts on that.
Kind of not eye on our list in terms of the, what we're going to contribute, uh, to them. And what they'll contribute to us.
Alright, Brian ill try to hit the first two there and then hand it over to Ben So yes.
Next, uh, question comes from Brian Bell with joy Bank.
Thank you for clarifying some of the comments in the script, we're referring to recurring revenue being around the same level as the third quarter I did mention that of course, there is the typical seasonal impact.
Please go ahead.
From.
Just lower purchase volume that happens in sort of the winter months, you see that in the fourth and the first quarter.
Each year, so I don't I'm not trying to give a specific guidance on that I just think because we don't know where volumes are ultimately going to be in a particular period. So that's more just of a.
Uh, great thanks. Thanks. Good morning. Thanks for taking my question. Um, maybe just back to mortgage. I just wanted to clarify Warren on the, um, for Q Outlook, um, that the guide of I think flat Revenue 32 to 4 key was that for the whole segment, um, or was that just for recurring? Because I know you did mention the seasonality and transaction fees. So if you could just verify that and then
Just a helpful Guide for you guys to sort of think through that as you update your models.
I think your second question if I remember was around just maybe longer term guidance.
I think we'll give.
We will give guidance on the fourth quarter call.
But the MBA is forecasting loan growth kind of in the high single digit range right now.
Just a longer term, um, um, outlook on that build of the revenue, Synergy, you know what's been actioned so far. And, uh, are you sticking to the same timeline on the, um, you know, on on the integration and then maybe just longer term, just comments around competition, uh, in the mortgage space from, uh, from the blockchain and from blockchain providers. I know that's more futuristic but just just your thoughts on that.
Industry originations will be slightly below the $6 million.
Next year based on what they're seeing today, and I'm, not confirming or denying that but that's kind of the information that's out there. So based on that I would just point you back to.
The scenarios that we provided in the past where when.
When we closed the transaction that we would probably be more in the lower mid single digit range in that kind of an environment, but that obviously can change as interest rates move in mortgage.
Rates move the economics change pretty quickly. So we will have to see as we get closer to guidance next year in terms of where we what we provide there.
Hi, Brian I'll hit.
Competitive landscape question that you had towards the end.
We.
Customers and I've said this in prior calls customers continue to focus on having an independent well capitalized neutral technology provider.
To help develop and enhance this.
Critical market infrastructure for them and in particular, one that doesn't compete with them.
And that's why we continue to have the sales success that we highlighted obviously.
<unk> said it in this call that we had the highest quarter in sales in the third quarter.
We've had all year. So we're continuing to have a lot of success in there.
On the landscape itself. There was a question about <unk> about pennymac earlier, because the reality is with Pennymac, just a little bit of history on that that there was a longstanding dispute between Fannie Mac at Black Knight at arbiter found that.
Volumes are ultimately going to be in a particular period, so that's more just of a, um, you know, just a helpful guide for you guys to just sort of think through that as as you update your models. Um, I think your second question if I remember was around, just maybe longer term guidance. Um, I think we'll give, uh, we'll give guidance on the fourth quarter call, uh, of course. But, you know, the NBA is forecasting loan growth. Kind of in the high single digit range right now or industry. Originations will be slightly below the 6 million. Um, next year, based on what they're seeing today and I'm not confirming or denying that, but that's kind of the information that's out there. So I based on that, I would just point you back to, you know, the scenarios that we provided in the past where um, when we close the black Nate transaction that we would probably be more in the lower mid single digit range and that kind of an environment, but that obviously can change as interest rates move as mortgage, uh, rates move, you know, that can obviously, um, change pretty quickly. So we'll have to see as we get closer to to, to guidance next year. In terms of what we what we provide their
Adding back used or confidential information to build a servicing system. So it wasn't a surprise to us to be honest with you after buying black Knight that they took an ownership stake in our platform and they are.
Hi, Brian. I'll I'll hit the uh competitive landscape question that you had towards the end.
we, um,
Trying to build our loan origination system.
you know, customers, and I've said this in in Prior calls, customers continue to focus on having an independent. Well, capitalized neutral, technology provider.
To potentially move to over time, so it's not a surprise, but again there is a.
To help develop and enhance this.
In our mind, it's not a neutral independent platform.
Critical Market infrastructure for them and and in particular 1, that doesn't compete with them.
And then you have the rocket conversation that we have our understanding is that rockets moving.
They are loans to their to our legacy Cooper platform mainframe system called <unk>.
Not going to say Jim.
And yes, they've decided that they want to have their own proprietary custom system that is mainframe base to go to.
And that's why we continue to have the sales success that we highlighted. Um, obviously you know, we've we've set it in this call that we had the highest quarter in sales in the third quarter. Uh then we then we've had all year. So we're continuing to have a lot of success in their
And then you look at it platforms like we have with Mers were merged as a comprehensive platform handles first and second loans, it's got legal standing within the mortgage processes. It's got proven expertise in the bankruptcy foreclosure space.
It's an incredible business that's run with an independent board and board members that are part of the industry and it's a it's a great great business for us.
You take all of that and then our positioning of where were again, an independent well capitalized proven technology provider for many many different industries and that were neutral and don't compete with our customers. We think we're very well positioned.
Um, on the landscape itself. There's a question about a pain about Penny Mac earlier, you know, the reality is with Penny Mac, you know, just a little bit of history on that that there was a long-standing dispute between Penny Mack and black knight, an Arbiter found that um PennyMac used our confidential information to build a servicing system. So it wasn't a surprise to us to be honest with you. After buying Black Knight that they took an ownership stake in a platform and they are, you know, trying to build a loan origination system uh to to potentially move to overtime. So it's not a surprise. But again there's a in our mind, it's not a neutral independent platform.
And then you have the rocket conversation that we have, you know, our understanding is that Rockets moving.
Thank you.
Next question comes from Alex Blaustein with Goldman Sachs.
Uh, their loans to their to a legacy Cooper platform mainframe system called elsam. It's not going to staging.
Please go ahead.
Hey, good morning, everybody. Thank you for the question I was hoping to go back to one of the earlier points you made in prepared remarks around AI initiatives. When it comes to the workflow automation and you spend quite a bit of time talking through various processes.
and you know, they've decided that they want to have their own proprietary, you know, custom system, that is Mainframe based to go to
When you zoom out I guess, what's the goal here what in terms of actual savings do you guys think this can produce for the firm what's the timeframe on that and how are you thinking about either reinvesting some of these savings or letting them sort of dropdown to the bottom line and maybe sort of help us frame what that means for the firm's sort of profitability over time.
And then you look at platforms like we have with Ms. Where Ms is is a comprehensive platform handles first and second loans, it's got legal standing within the mortgage processes. It's got proven expertise in the bankruptcy. Foreclosure space. You know, it's an, it's an incredible business that's run with an independent board and board members that are part of the industry. And it's a, it's a great great business for us.
Thanks.
Yes.
Yeah.
Hi, Alex its Ben.
So we went through and I alluded to in my prepared remarks that we have.
So, you take all of that and then our positioning of where we're again, an independent, well, capitalized proven technology provider for many many different Industries and that we're neutral and don't compete with our customers. We think we're very well positioned.
Our strategy in a process that were applying across ice that Isa Laura.
Platform and for US it's really about.
Thank you. Uh, next question comes from Alex Blowin with Goldman Sachs
Literally breaking down business process by business process internally that we have within <unk> as well as the solutions that we're providing to customers.
Please go ahead.
And figuring out on our automation scale, how much automation can be applied where and when human intervention should be applied.
Along that because we and our customers operate extraordinarily high.
Highly compliant regulated businesses.
Hey, good morning everybody. Thank you for the question. Um, I was hoping to go back to uh 1 of the earlier points you made in prepared remarks around AI initiatives when it comes to the workflow Automation and you spend quite a bit of time talking through various processes. Uh when you zoom out, I guess, what's the goal here? What? In terms of actual savings? Do you guys think this can produce for the firm? What what's
In.
And all of the areas, where we operate.
At the end of the day. These AI models their pattern recognition software that have various levels of probabilistic outcomes.
The time frame on that. And how are you thinking about, um, either reinvesting? Some of these savings or letting them sort of drop down to the bottom line and maybe sort of help us frame what that means, for the firm's sort of profitability over time. Thanks.
Some are really some processes are really good and app to be.
hi Alex, it's been um,
To move towards almost full automation and theres, others, where you've got to have human intervention, especially in the exception handling process.
So, you know, we went through, and I alluded to, in my prepared remarks, that we have a...
Some areas like compliance checks for example in mortgage is going to be a very low level of tolerance accepted.
strategy and a process that we're applying across ice that ice Aurora platform and, you know, for us, it's really about
So what we're seeing.
Through this is are we seeing efficiency gains absolutely we're seeing efficiency gains.
Literally breaking down business processes, by business process, internally that we have within ICE, as well as the solutions that we're providing to customers.
We're right now our best guests from the way we've been applying is is that we're going to be able to do more with the same.
More with the same number of people, we're going to be able to speed to market as well.
Is the types of offerings that we want to provide the types of solutions that we want to provide to our customers. There is more and more demands for us to do more and we think we'll be able to do that with the same head count that we have.
Highly compliant, regulated businesses.
In all of the areas where we operate.
<unk> had historically.
Our next question comes from Ashish <unk> with RBC capital markets. Please go ahead.
Hey, Good morning, guys. This is though chi on for Ashish Mantra I. Appreciate you guys taking my question.
Just with the continued strength we've seen on your data services and solutions businesses across ice could you maybe give a little bit of a commentary on the drivers there maybe the apple.
And at the end of the day, these AI models, their pattern recognition software that have various levels of probabilistic outcomes. And you know, some are are really some processes are really good and and and apt to be uh, to move towards almost full Automation. And there's others where you've got to have human intervention, especially in the exception handling process. Because in some areas like compliance checks, for example, and mortgage is going to be a very low level of of Tolerance accepted.
So what we're seeing um through this is, are we see seeing efficiency gains absolutely receiving efficiency, gains?
Appetite is coming from.
From a customer perspective, either kind of quantity of data consumed versus pricing.
Also with the developments.
Were kind of high value datasets like the sentiment indicators is that kind of another leg up you would say kind of FERC driving growth in those segments.
Hi, its Chris I appreciate the question.
Where right now, you know our best guess from the way we've been applying is is that we're going to be able to do more with the same more with the same number of people we're going to be able to speed to Market as um as as as the types of offerings that we want to provide the type of solutions that we want to provide to our customers. There's more and more demands for us to do more and we think we'll be able to do that with the same headcount that we've had historically.
I would.
Suggest to you that it's more comprehensive than that.
Complete playbook youre getting to take advantage of on the client side and that is what is resonating that certainly the the high value assets that you've made reference tier one, but if you look at the mission critical data that we have across all of our exchange space going there. That's a foundation that people come to know and trust our ability to deliver that into their systems given that delivery.
Our next question comes from Ashish sabadra with RBC Capital markets, please go ahead.
Channel that they deem most appropriate at a given time and the ability to add additional content, whether it's the new pieces, we talked about or or where they can get additional pieces of.
Data from other sources as we said in prepared remarks with 750 different data sources that can come across those different delivery.
<unk> made investments says warrant and been both said in the prepared remarks and these capabilities. Those investments are paying off and you are seeing the clients ability to make those changes and incorporate these opportunities into their operational workflows.
Hey, good morning guys. This is Bill chi on first Chief sidhra. I appreciate you guys taking my question you know, just with the continued strength of seeing uh on your data service and solutions businesses across ice maybe give a little bit of a commentary on on the drivers there. You know where maybe the the and appetite is coming from uh from a customer perspective. Uh either kind of quantity of data consumed versus pricing. Um, and also, you know, with the developments of, of the new kind of high value data sets, like, these sentiment indicators, is that kind of another leg up you'd say, kind of, for driving growth in those segments, thanks.
Hi, it's Chris. I appreciate the question. I
I would.
Thank you we have nice I'll ask questions now I would like to turn the call back over to Jeff Sprecher, Chairman and CEO.
For any closing comments.
Well. Thank you Lydia I appreciate the way you manage the call today and thank you all for joining us this morning.
I'd like to again, thank all my colleagues for delivering the best third quarter in our company's history.
And again, thank our customers for their continued business and for the trust. They have in the way we manage our business will be back soon to continue to update you, but Meanwhile, we're going to be working to innovate for our customers and continue to build our all weather business model.
Suggest to you that it's it's more comprehensive than that. It it's a a complete Playbook that you're getting to take advantage of on the client side and that is what is resonating that certainly the the high value assets that you made reference to your 1. But if you look at the mission critical data that we have across all of our exchange space going there, that's a foundation that people come to know and trust our ability to deliver that into their systems. Given the delivery channel that they seem most appropriate at at a given time and the ability to add additional content. Whether it's the new pieces, we talked about
Thanks, and have a great day.
Thank you.
Okay cool. Thank you very much gentlemen, you may now disconnect your lines.
Or or where they can get additional pieces of a of data from other sources. As we said that the priority marks we have 750 different data sources that can come across. Those different delivery mechanisms we made Investments says uh Warren and been both said in the fair remarks. In these capabilities, those Investments are paying off and you're seeing the, the client's ability to make those changes and incorporate these opportunities, uh, into their operational workflows.
Thank you, we have no further questions, so I'd like to turn the call back over to Jeff and CEO for any closing comments.
Uh, well, thank you, Lydia. Uh, appreciate the way you manage the call today, and, and thank you all for joining us this morning. Um, I'd like to again thank all my colleagues for delivering the best third quarter in our company's history. And
And again, thank our customers for their continued business and for the trust they have in the way we manage our business, we'll be back soon to continue to update you, uh, but Meanwhile, we're going to be working to innovate for our customers and continue to build our all-weather business model.
Thanks and have a great day.
Thank you. This now concludes our call thank you very much for joining. You may now disconnect your line.