Your Loan Origination Data Template

The Activity Name describes a distinct task or milestone in the loan origination lifecycle. These events are recorded chronologically to build a sequence of actions for each loan application. The collection of these activities forms the basis of the process map.

In analysis, the Activity Name is used to visualize the process flow, identify bottlenecks between steps, and analyze the frequency and sequence of events. It is fundamental for understanding what happens during the process, measuring transition times, and detecting rework loops where activities are repeated.

This attribute defines the steps in the process, allowing for the visualization of the process map, analysis of process flow, and identification of bottlenecks or deviations.

Typically derived from event logs, status change records, or milestone data within the loan file in ICE Mortgage Technology.

The Event Timestamp marks the point in time that a process step occurred. It provides the chronological order necessary to reconstruct the process flow and is essential for all time-based analysis. For most activities, this represents the start time of the event.

This attribute is crucial for calculating durations and cycle times, such as the time between 'Underwriting Commenced' and 'Underwriting Completed'. It enables the analysis of process performance, the identification of delays and bottlenecks, and the monitoring of adherence to service level agreements (SLAs).

This timestamp provides the chronological sequencing for all activities and is the foundation for all duration, cycle time, and performance calculations.

Each milestone or event record in ICE Mortgage Technology should have an associated timestamp indicating when it was completed or logged.

The Loan Application ID uniquely identifies each individual loan request throughout its entire lifecycle. It serves as the central entity to group all associated activities and data, allowing for a complete trace of the origination journey for a specific loan.

In process mining analysis, this ID functions as the Case ID. It links all related events, such as 'Application Submitted', 'Underwriting Commenced', and 'Funds Disbursed', into a single coherent process instance. This enables the reconstruction and analysis of the end-to-end journey for every loan, which is essential for calculating cycle times, identifying variants, and understanding process flows.

This is the essential Case ID that connects all related activities into a single process instance, making it possible to analyze the end-to-end loan origination journey.

This is the primary loan identifier in ICE Mortgage Technology, often referred to as the Loan Number or Loan ID within the system.

This attribute indicates the origin of the loan application, for example, 'Online Portal', 'Broker', or 'In-Branch'. Different channels may have different data quality, completeness, and customer profiles, which can impact the downstream process.

Application Channel is a valuable dimension for comparing process performance. Analysis can reveal which channels are most efficient, have the lowest rework rates, or lead to the highest approval rates. These insights can help the business optimize its channel strategy and allocate resources effectively.

Helps compare the performance and efficiency of different submission channels to identify which ones are most effective or require process improvements.

Consult ICE Mortgage Technology documentation. This may be stored as a 'Source of Business' or similar field.

This attribute identifies the human resource involved in a process step. It can represent the person who completed the task, the current owner of the loan file, or the primary contact for the application.

Analyzing the process by Assigned Loan Officer helps in understanding workload distribution, comparing performance across individuals or teams, and identifying coaching opportunities. It is essential for dashboards related to resource performance, such as 'Loan Officer Activity Distribution' and 'Underwriting SLA Performance'.

This attribute is key to resource-based analysis, allowing you to measure performance, balance workloads, and compare efficiency across different loan officers and teams.

Consult ICE Mortgage Technology documentation. User information is typically associated with milestone completion records or loan ownership fields.

This attribute records the outcome of key decision points in the process, such as 'Approved', 'Denied', 'Withdrawn', or 'Approved with Conditions'. It represents the terminal state of a loan application or the result of an interim review.

Analyzing Decision Outcome is critical for understanding process effectiveness. It helps quantify approval and denial rates and is often analyzed alongside the 'Reason for Decision' to identify the primary drivers of negative outcomes. Understanding these outcomes is key to improving application quality and process efficiency.

This attribute is essential for measuring process effectiveness, such as approval rates, and for analyzing the reasons behind loan denials or withdrawals.

Consult ICE Mortgage Technology documentation. This information is typically tied to the underwriting decision milestone or the final loan status.

The Event End Time marks the completion of a specific task. For events that are considered instantaneous, the end time may be the same as the start time. For activities with a measurable duration, like 'Underwriting Review', this timestamp is distinct.

This attribute allows for a more precise analysis of process performance by differentiating between waiting time (time between activities) and processing time (duration of an activity). It is essential for calculating the 'ProcessingTime' metric and for resource utilization analysis.

Enables the calculation of true processing time for activities, helping to distinguish active work time from idle waiting time for more accurate bottleneck analysis.

Consult ICE Mortgage Technology documentation. This may be available for certain logged events or can be the same as the StartTime for milestone events.

The Loan Amount represents the principal amount of the loan application. This value can significantly influence the process, as larger or non-conforming loans may require additional scrutiny, different approval levels, or more extensive documentation, leading to longer cycle times.

This attribute is used as a key dimension for filtering and analysis. By creating value bands (e.g., <$250k, $250k-$500k, >$500k), analysts can compare process performance for different loan sizes. It is also a fundamental component for financial calculations, such as estimating the 'Cost per Loan Origination'.

Helps in segmenting the process to see if loan value impacts processing time, rework, or approval rates, providing valuable context for performance analysis.

This is a fundamental field in the loan application data within ICE Mortgage Technology.

This attribute categorizes each loan application based on the financial product offered. Different loan products often have distinct process requirements, complexities, and regulatory constraints, leading to variations in the origination process.

In analysis, Loan Product Type is a critical dimension for segmentation. It allows analysts to compare cycle times, rework rates, and process paths across different products to see if certain products are less efficient. This insight is crucial for tailoring process improvement efforts and setting realistic performance targets.

Allows for performance comparison across different types of loans, helping to identify if specific products have more complex or inefficient processes.

This information is a core data point for any loan and should be available in the main loan details section within ICE Mortgage Technology.

The applicant's credit score is a key factor in the lending decision and can influence the complexity of the underwriting process. Applications with lower credit scores may require more rigorous review and documentation.

This attribute provides a valuable dimension for risk-based analysis. By segmenting applications into credit score bands, analysts can investigate whether there is a correlation between credit score and processing times, rework rates, or final decision outcomes. This can help in refining risk assessment processes and managing resources more effectively.

Provides a risk dimension for analysis, helping to determine if credit risk correlates with process complexity, cycle time, or decision outcomes.

This data is typically sourced from a credit reporting agency and stored within the borrower's information in ICE Mortgage Technology.

This attribute segments customers based on their profile or relationship with the lender. The needs and required documentation for a first-time homebuyer can be very different from those of an investor or someone refinancing a loan, potentially leading to different process paths.

Analyzing the process by Customer Type can uncover variations in customer experience and process efficiency. It helps answer questions like, 'Do first-time homebuyers experience longer cycle times?' or 'Are refinance applications processed more quickly?'. These insights can inform customer service strategies and process adjustments.

Allows for customer-centric process analysis to understand if different types of customers experience different process efficiencies or challenges.

Consult ICE Mortgage Technology documentation. This may be derived from the loan purpose or other applicant data.

This attribute distinguishes between tasks executed by software, such as an automated credit check or sending system-generated disclosures, and tasks requiring human intervention. This information is key for automation initiatives.

Analyzing the process with this attribute helps quantify the level of automation and identify opportunities for further improvement. It is used to calculate KPIs like 'Manual Activity Frequency' and can highlight manual bottlenecks that are prime candidates for automation, ultimately aiming to reduce costs and improve speed.

Helps quantify the extent of automation in the process and identify manual activities that are bottlenecks, providing a basis for future automation initiatives.

This is often derived by mapping activity names or user IDs (e.g., 'System') to an automation status. It is unlikely to be a direct field in the source system.

A boolean flag that indicates if an activity is being performed for a second or subsequent time within the same loan application. This is typically identified when an activity follows a later step in the standard process, such as 'Supporting Documents Requested' occurring after 'Underwriting Decision Rendered'.

Analyzing rework is fundamental to understanding process inefficiency. By filtering for activities where IsRework is true, analysts can quantify the frequency and impact of rework loops. This helps identify the root causes, such as incomplete initial documentation or unclear requirements, and is crucial for calculating the Application Rework Rate KPI and driving process simplification efforts.

Directly quantifies process inefficiency by flagging repeated work, making it easy to measure the frequency of rework and investigate its root causes.

This attribute is not in the source system. It is calculated by process mining software by detecting repeated activities or backward loops in the process flow for a case.

This attribute provides the date and time of the most recent data pull. It is essential for understanding the freshness of the data being analyzed and for managing data refresh schedules.

While not typically used for analyzing the process itself, it is vital for dashboard reporting and data governance. It informs users about how current the analysis is and helps diagnose issues related to outdated information.

Informs users of the data's freshness, which is critical for ensuring that analyses and dashboards are based on up-to-date information.

This timestamp is typically generated and added to the dataset during the data extraction and loading (ETL) process.

The total time elapsed from the beginning to the end of a loan application case. It is calculated as the difference between the timestamp of the first event, e.g., 'Loan Application Created', and the last event, e.g., 'Funds Disbursed' or 'Loan Denied'.

This attribute is a primary key performance indicator for measuring overall process efficiency. It provides a high-level view of how long it takes to process a loan from start to finish. Analysts use this metric to track performance over time, benchmark against industry standards, and identify the impact of process improvement initiatives. Breaking down the average cycle time by dimensions like Loan Product Type or Application Channel reveals which process variants are more or less efficient.

This KPI directly measures the end-to-end efficiency of the loan origination process, providing a critical metric for performance tracking and accelerating service delivery.

Calculated by subtracting the timestamp of the first event from the timestamp of the last event for each Loan Application ID.

The duration of an activity, calculated as the difference between its EventEndTime and EventTimestamp. This metric is essential for identifying which specific steps in the loan origination process are consuming the most active work time.

In analysis, ProcessingTime helps pinpoint bottlenecks at the activity level. By aggregating this metric, analysts can compare the efficiency of different activities, loan officers, or departments. For instance, a high average processing time for 'Underwriting Commenced' could indicate resource constraints or process complexities that need investigation. It is a fundamental building block for performance monitoring and continuous improvement initiatives.

Measures the active work time of individual process steps, helping to identify the most time-consuming activities and distinguish them from idle time.

This attribute is not in the source system. It is calculated during data transformation using the formula: EventEndTime - EventTimestamp.

This attribute provides the geographical location of the property. Lending regulations, market conditions, and processing requirements can vary significantly by state, which may influence the loan origination process.

Property State is a useful dimension for geographical analysis. It allows for comparing process performance, such as cycle times and approval rates, across different regions. This can help identify regional bottlenecks or highlight the impact of state-specific regulations on the process.

Enables geographical analysis of the process, helping to identify regional performance differences that may be caused by market conditions or state-specific regulations.

This is a standard field in the property information section of the loan application data in ICE Mortgage Technology.

This attribute provides context for the 'DecisionOutcome'. When a loan is denied or requires rework, this field specifies why, for example, 'High debt-to-income ratio' or 'Incomplete documentation'.

This information is invaluable for root cause analysis. By analyzing the most frequent reasons for denials or rework, the organization can identify systemic issues in the process or problems with application quality. These insights can lead to targeted improvements, such as clearer instructions for applicants or additional training for loan officers.

Provides the 'why' behind loan denials or rework, enabling root cause analysis to address systemic issues and improve first-pass yield.

Consult ICE Mortgage Technology documentation. This information is often captured in reason code fields or notes associated with a decision milestone.

Indicates whether an activity or the entire case is completed within its service level agreement target. It is typically derived by comparing the actual cycle time against a predefined SLA target, such as the UnderwritingSlaTarget.

This attribute is critical for performance and compliance monitoring. Dashboards often use SLAState to visualize the percentage of loans meeting their targets, allowing managers to track performance against key objectives. Segmenting SLA performance by loan officer, product type, or channel can reveal areas of excellence or opportunities for improvement, ensuring the organization meets its service commitments.

Provides a clear, at-a-glance indicator of performance against key time-based targets, making it easy to monitor and report on SLA compliance.

This attribute is not in the source system. It is calculated by comparing the actual duration of a process segment with its corresponding SLA target.

This attribute specifies the software or application that generated the process data, such as 'ICE Mortgage Technology Encompass' or a connected CRM. It is particularly useful in environments where data is aggregated from multiple sources.

In analysis, SourceSystem helps in data validation and provides context about the origin of an event. It can be used to filter analysis for specific systems or to investigate data quality issues that may be unique to one source.

Provides crucial context about data origin, which is important for data validation, troubleshooting, and understanding process variations across different systems.

This value can be manually added during data extraction or may be available in data headers if the export originates from a data warehouse.

This attribute identifies the organizational unit responsible for the underwriting phase of the loan. In large organizations, departments might be specialized by region, loan type, or risk level.

Similar to the Assigned Loan Officer, this attribute allows for performance analysis at a team or department level. It can be used to compare workloads, efficiency, and SLA adherence across different underwriting groups, helping management to identify high-performing teams and share best practices.

Enables performance analysis and comparison at the team or department level, which is useful for resource management and identifying systemic issues within specific groups.

Consult ICE Mortgage Technology documentation. This may be part of the user data associated with the underwriter or a separate routing field.

This attribute defines the expected maximum time for completing the underwriting process, from 'Underwriting Commenced' to 'Underwriting Completed'. It serves as the benchmark against which actual performance is measured.

This is a critical input for calculating SLA adherence. It allows for the creation of an 'SLAState' attribute to flag underwriting tasks as 'On Time' or 'Late'. Dashboards tracking SLA performance rely on this target to provide managers with a clear view of whether service commitments are being met.

Provides the benchmark needed to objectively measure and monitor underwriting performance against service level agreements.

This may not be a field in the source system and could be business knowledge that is joined with the data during transformation. It might vary by loan type or region.