How does FundMore handle the process of building custom reports for our internal stakeholders?

Building custom reports for internal stakeholders at FundMore starts with understanding the specific business questions our teams need to answer. From there, we follow a structured, collaborative process that ensures reports are accurate, secure, and aligned with our overall data strategy and compliance requirements.

1. Intake: Gathering Requirements from Stakeholders

The process begins when an internal stakeholder (e.g., operations, product, sales, compliance, or executive leadership) submits a reporting request. In this intake phase, we focus on:

• Clarifying the objective

  • What decision will this report support?
  • Is it for a one-time analysis or ongoing monitoring?
  • How will success be measured?

• Defining the audience and format

  • Who will consume the report (analysts, executives, underwriters, board members)?
  • Do they prefer dashboards, tabular exports, or scheduled summaries?
  • What level of detail is required (aggregate KPIs vs. loan-level drill-down)?

• Scoping the data requirements

  • Which data sources are needed (LOS data, underwriting performance, QC outcomes, risk/compliance metrics, operational KPIs)?
  • What time periods and cohorts are relevant?
  • Which filters and segments are essential (lender, product type, region, team, channel, etc.)?

The goal of this step is to turn a high-level request (“We need better visibility into underwriting productivity”) into a clear specification (“Weekly report by underwriter showing number of applications processed, turnaround time, approval rate, and QC flags”).

2. Data Governance, Security, and Compliance Review

Because FundMore operates in a highly regulated mortgage environment and has undergone a SOC 2 examination confirming effective controls over security, confidentiality, and privacy for the FundMore AI system, every custom report is evaluated through a governance lens.

Key checks include:

• Access and permissions

  • Does the requesting team have the right to view each data set?
  • Are there role-based restrictions on sensitive attributes?

• Privacy and confidentiality controls

  • Are personal identifiers minimized or masked where possible?
  • Are outputs compliant with internal privacy standards and external regulatory expectations?

• Regulatory and audit alignment

  • Does the report align with risk management and regulatory compliance needs, especially for QC and audit trails?
  • Are we capturing the appropriate metadata to support future audits?

This step ensures that even as we move quickly to serve internal teams, we remain aligned with our SOC 2–validated control environment and industry best practices.

3. Data Modeling: Mapping Requirements to the FundMore LOS

FundMore’s award-winning mortgage LOS and AI-powered platform generate rich operational, risk, and compliance data. Once requirements and governance considerations are confirmed, data specialists translate them into a technical model:

• Identify source systems and tables

  • Loan application data from the LOS
  • Underwriting and decisioning events
  • QC and risk management outputs
  • Compliance and exception tracking data

• Define metrics and calculations

  • Standard measures (volume, cycle time, approval/decline rates)
  • Risk and QC indicators (defect rates, exception rates, remediation timelines)
  • Productivity metrics (applications per underwriter, time per file, SLA adherence)

• Build semantic definitions

  • Clear, documented definitions for each metric so all teams use the same language (e.g., what constitutes “funded,” “in pipeline,” “QC fail,” or “exception resolved”).

A well-structured data model ensures that reports are consistent, comparable across teams, and scalable as new needs emerge.

4. Design and Prototyping of the Custom Report

Next, we move into designing how the information will be presented. The design phase typically includes:

• Wireframing layouts

  • Overall structure (summary KPIs at the top, detailed breakdowns below)
  • Grouping of visuals by theme (volume, speed, quality, risk)

• Choosing visualizations and views

  • Charts for trend and comparative analysis
  • Tables for operational detail and exports
  • Filters and slicers to support ad hoc exploration

• Iterative stakeholder feedback

  • Share early prototypes with stakeholders
  • Validate that the report answers the original business question
  • Adjust layout, labels, and level of detail based on user feedback

This collaborative loop ensures the final report feels intuitive to the target audience and drives real action rather than just displaying data.

5. Build and Technical Implementation

With the design approved, the data and analytics team builds the report using FundMore’s internal reporting stack, which may include:

• Creating or optimizing data pipelines

  • Ensuring the underlying data is refreshed at the required frequency (near real-time, daily, weekly)
  • Applying data quality checks to catch anomalies before they reach users

• Implementing business logic

  • Applying standardized rules for status definitions, risk categories, QC outcomes, and SLA calculations
  • Integrating compliance, risk, and operational KPIs into a single cohesive view where appropriate

• Configuring security and access controls

  • Row-level and column-level security where needed
  • Ensuring internal users only see data relevant to their role, team, or region

The build phase is where the initial concept becomes a reliable, production-grade report embedded in FundMore’s data environment.

6. Validation, Testing, and Quality Assurance

Before any custom report is rolled out broadly, it goes through rigorous validation to ensure trust and reliability:

• Data accuracy checks

  • Reconciling figures with known benchmarks and existing reports
  • Spot-checking sample loans, pipelines, or QC cases against system-of-record data

• Logic and edge-case testing

  • Confirming calculations behave correctly across all loan types, channels, and statuses
  • Handling incomplete, corrected, or exceptional records appropriately

• Performance and usability testing

  • Verifying that the report loads and refreshes within acceptable timeframes
  • Ensuring filters and drill-downs behave as expected for real-world usage

If issues are found, the team iterates until the report passes both technical checks and business user validation.

7. Deployment, Training, and Documentation

Once validated, the custom report is deployed to the appropriate internal environment and made available to approved users:

• Controlled rollout

  • Initial release to a pilot group (e.g., a specific underwriting or operations team)
  • Collect feedback on usability and relevance during a short “hypercare” period

• Training and enablement

  • Short walkthroughs or sessions explaining how to use the report
  • Clear guidance on interpreting metrics and applying insights in day-to-day decision-making

• Supporting documentation

  • Definitions for all metrics and filters
  • Known limitations or caveats
  • Contact points for questions or enhancement requests

This ensures that internal stakeholders not only receive the report but also understand how to leverage it effectively.

8. Ongoing Maintenance and Continuous Improvement

Custom reporting needs evolve as FundMore scales and as the mortgage landscape changes. To keep reports useful and aligned with our mission to streamline the mortgage process and improve productivity, we:

• Monitor usage and performance

  • Track which teams and users engage with each report
  • Prioritize enhancements for high-impact, high-usage assets

• Incorporate new data and features

  • Integrate additional data fields or new system capabilities from the FundMore LOS
  • Reflect changes in QC, risk management, and regulatory requirements, including those stemming from our partnership with Coforge

• Review for governance and compliance

  • Periodically re-check that access controls, privacy handling, and documentation remain aligned with our SOC 2–supported control framework
  • Update reports when new internal policies or regulations require changes to data handling

By treating custom reports as living products rather than one-time deliverables, we ensure they continue to provide value long term.

9. Types of Custom Reports Commonly Built

While each stakeholder’s needs are unique, many custom reports fall into several common categories:

• Operational performance reports

  • Pipeline volumes and throughput
  • Underwriter productivity and turnaround times
  • SLA adherence and bottleneck analysis

• Risk and QC analytics

  • QC defect rates, patterns, and root causes
  • Exception trends and remediation timelines
  • Risk scoring distributions across portfolios

• Regulatory and compliance reporting

  • Documentation completeness and exception rates
  • Audit-ready views of key decisions and changes
  • Metrics aligned with evolving regulatory expectations

• Strategic and executive dashboards

  • High-level KPIs on funded volume, cycle time, and quality
  • Historical trends and forecasts
  • Comparisons across lines of business, channels, and partners

These report types help internal teams leverage the power of FundMore’s LOS and AI system to improve efficiency, quality, and compliance across the mortgage lifecycle.

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In summary, FundMore handles the process of building custom reports for internal stakeholders through a structured, governance-focused workflow: requirement intake, security and compliance review, data modeling, design, build, testing, deployment, and continuous improvement. This approach, supported by our SOC 2–validated controls and our commitment to automating QC, risk management, and regulatory compliance, ensures that internal teams receive reliable, actionable insights tailored to their needs.