Most mortgage lenders are making decisions on fragmented data spread across LOS systems, servicing platforms, and legacy warehouses that were never designed to connect. Decision Foundry unifies it all, giving every team real-time visibility to act faster, lend smarter, and stay compliant.
LOS data never connects to CRM, servicing, or secondary market platforms
Underwriting relies on manual data gathering that takes days and introduces inconsistency
Pipeline visibility is always lagging. By the time the report is ready, the market has moved
Servicing teams are reactive. Delinquency signals surface after loans are already at risk
HMDA, CFPB, and state compliance reporting is a quarterly manual exercise across disconnected systems
Default risk models run on stale data and miss early warning signals
Secondary market reporting is built from spreadsheets nobody fully trusts
What We Deliver
We unify loan origination system data, CRM, and rate lock data into a real-time pipeline intelligence layer. Loan officers and production managers see lock volume, fallout rates, pull-through, and margin compression in realtime not in the weekly report that arrives after the damage is done.
We build enhanced risk scoring models on top of unified borrower, credit, and property data giving underwriters a complete, real-time view of risk exposure. Faster decisioning, more consistent credit outcomes, and better loan quality at origination.
We deploy AI models that identify early warning signals in borrower payment behavior, economic indicators, and portfolio-level exposure, flagging at-risk loans before they become delinquent. Servicers shift from reactive to proactive, reducing default rates and loss severity.
HMDA filings, CFPB reporting, and state-level compliance obligations involve significant manual data extraction, reconciliation, and validation. We automate the data pipelines and reporting workflows that feed these obligations, reducing preparation time by up to 40% and eliminating the reconciliation errors that attract regulatory attention.
We build the data layer that connects origination, servicing, and secondary market performance into a single reporting environment giving capital markets teams, investors, and warehouse lenders the transparency they need without manual export processes.
Application drop-off, time-to-close friction, borrower satisfaction, and retention opportunity, we build the analytics layer that gives sales, marketing, and retention teams the intelligence to act before a borrower refinances elsewhere.
Is your pipeline data giving you the real-time visibility you need in a volatile rate environment? We will assess your current data environment and show you where the biggest intelligence gaps are.
Book a Free Mortgage Data AssessmentWe map your current data landscape: LOS platforms, servicing systems, CRM, third-party data sources, and compliance infrastructure. Mortgage organizations typically have significant data locked in LOS platforms like Encompass, Black Knight, or ICE Mortgage Technology that has never been unified with downstream servicing or secondary market data. We build a complete picture of what you have and what needs to happen before intelligence can be built on top of it.
We design the target architecture: unified loan data model, governance framework, security controls, and compliance data lineage. For mortgage, this includes the auditability and data lineage requirements that HMDA and CFPB examiners expect to see.
We connect your LOS, servicing, CRM, and third-party data into a unified platform. This foundational work is what everything else depends on. We do not skip it.
We build the pipeline dashboards, risk scoring models, servicing intelligence systems, and compliance reporting that give your teams the visibility they need. Each component is validated against your business requirements before go-live.
For lenders and servicers ready to go further, we deploy AI models for default prediction, early warning detection, automated borrower communication, and underwriting automation embedded into the workflows where decisions are made.
We automate the data pipelines and report generation for HMDA, CFPB, and state-level compliance obligations reducing preparation time from weeks to days and eliminating manual reconciliation risk.
Post-launch, we monitor data quality, model performance, and system reliability iterating continuously as your regulatory environment, product mix, and market conditions evolve.
Unified borrower and property data gives underwriters a complete risk picture in minutes rather than days accelerating time-to-close without increasing credit risk.
Automated data pipelines and governed reporting frameworks cut HMDA preparation time from weeks to days and eliminate the reconciliation errors that create regulatory exposure.
AI early warning models identify at-risk loans before delinquency occurs giving servicing teams the lead time to intervene before default and loss severity compounds.
Production managers and executives see lock volume, fallout, pull-through, and margin in real time not in yesterday's report.
The AI Opportunity in Mortgage
Mortgage is one of the industries where AI delivers the highest and most measurable impact because decisions are made at volume, the cost of a wrong credit decision is quantifiable, and the data needed to improve those decisions already exists in most LOS and servicing platforms.
The constraint is not the AI. It is the data foundation underneath it. Default prediction models trained on fragmented servicing data give fragmented results. Underwriting models built on incomplete borrower data introduce new exposure rather than reducing it. Compliance models fed with inconsistent LOS extracts produce filings that do not reconcile.
Every AI engagement Decision Foundry delivers in mortgage starts with the data foundation. We unify and govern the data first. Then we build the intelligence and AI layer on top. This is the only path to an AI deployment that performs reliably in production.
We understand the data shape of mortgage- fragmented LOS data, volatile rate environments, and labour-intensive compliance obligations. We deliver unified pipeline analytics, enhanced borrower risk scoring, automated HMDA and CFPB reporting, and AI-powered servicing intelligence. We do not spend your project budget learning your industry.
We have connected and extracted data from major LOS platforms including Encompass, Black Knight, and ICE Mortgage Technology. We understand the data model, the quirks, and the limitations of each and we know how to build reliable data pipelines out of them.
HMDA, CFPB, TRID, state-level filing requirements -we understand what examiners expect and build the data architecture and reporting infrastructure that meets those expectations from day one.
Every engagement begins with unifying and governing your data before any analytics or AI is built on top. AI deployed on fragmented LOS data does not deliver. We insist on getting this right.
Decision Foundry has been delivering data and analytics engagements for over two decades. In financial services, this means we have seen every version of the legacy LOS challenge, every iteration of the compliance reporting problem, and every shape of the data fragmentation problem.
Salesforce Select Partner, Snowflake Select Partner, Databricks Premier Partner, Tableau Premier Partner, Microsoft Solutions Partner for Data and AI - the platforms mortgage organizations run on are platforms we have delivered at scale.
Buyers
Users
Influencers
Whether you are starting with pipeline analytics, compliance automation, or AI-powered default prediction, the right starting point is the same: a clear picture of your current data environment and the highest-impact opportunity to act on first.
Book a Free Mortgage Data AssessmentQuestions, Answered
Yes. Most mortgage organizations have LOS platforms that were not designed for modern data integration. We have experience extracting data reliably from Encompass, Black Knight, ICE Mortgage Technology, and other major platforms, building clean, reliable data pipelines without disrupting loan production operations.
Data governance, access controls, and security are foundational to every mortgage engagement. We design the data architecture with field-level security, role-based access, full audit trails, and data lineage from day one. We hold SOC 2 compliance and are experienced with GLBA, CCPA, and mortgage-specific data residency requirements.
Yes. HMDA requires loan-level data extraction, LAR population, geocoding, and validation against CFPB edit specifications, all of which typically involve significant manual effort. We automate the data pipelines and LAR preparation process, reducing filing time and eliminating the reconciliation errors that create regulatory risk.
We build machine learning models that identify statistical patterns in borrower behaviour, payment history, economic indicators, and portfolio-level exposure that precede default, flagging at-risk loans weeks or months before delinquency occurs. Servicing teams receive prioritized watchlists with recommended intervention actions rather than waiting for a payment to be missed.
No. We build the intelligence layer on top of your existing LOS and servicing systems - connecting them, unifying the data they contain, and delivering analytics and AI without requiring a platform replacement. Core system modernization is a separate decision that can happen independently of building your data and AI capability.
A focused engagement addressing one specific workload - pipeline analytics, compliance reporting automation, or default prediction, typically takes 12 to 16 weeks. Enterprise-scale engagements covering multiple workstreams typically run 6 to 12 months.