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AI Agent Profile · LendingIQ · Agent #82 · SLA

Onboarding SLA Agent AI

Function: Onboarding SLA TrackerInvoked via: real-time TAT monitoring · bottleneck detection · SLA breach escalationRuntime: AWS Bedrock · ap-south-1Model: Claude Sonnet 4Context window: 200K tokens

DivisionOnboarding

Resume

What this agent does

The Onboarding SLA Agent AI monitors every active application in real time against LendingIQ's committed TAT milestones — tracking time at each application stage, detecting where applications are spending more time than expected, and escalating to the operations head before SLA breaches become borrower-visible delays. It replaces the manual SLA tracker with a continuous, application-level monitoring capability that provides early warning of bottlenecks before they accumulate into systemic TAT failures.

Primary functions

TAT Monitoring

Continuous · all active applications at all stages

Invoked continuously — stage transition events from the LOS drive the TAT clock in real time

  • Maintains a TAT clock for every active application — measuring the elapsed time at the current stage and the cumulative elapsed time since application submission. The TAT clock stops when an application is on hold (waiting for borrower documents, waiting for co-applicant KYC, waiting for valuation) and resumes when the hold is resolved — distinguishing between time consumed by the lender's process and time consumed by the borrower's response. Both are tracked; only the lender-controlled time is counted against the SLA commitment.
  • Monitors each application against the stage-level TAT targets — the time budget allocated to each stage in the application process: KYC verification (24 hours), QC review (2 hours), credit assessment (48 hours for standard applications, 72 hours for complex cases), disbursement (24 hours after credit approval). An application that is within its stage-level budget is green on the dashboard; one approaching the budget is amber; one that has exceeded it is red.
  • Sends a 4-hour advance warning to the operations head for any application approaching its overall SLA boundary — providing enough time for the operations team to escalate the application within the current stage, adjust prioritisation, or communicate proactively with the borrower. A borrower who receives a proactive communication before the SLA is breached has a better experience than one who contacts LendingIQ to enquire about their application after the promised TAT has passed.
Output: Real-time TAT dashboard — all active applications with current stage, time at stage, cumulative time, SLA status (green/amber/red), and hold status. 4-hour advance warning for applications approaching the SLA boundary. SLA breach escalation at the moment of breach.

Bottleneck Detection

Real-time and weekly · stage-level pattern analysis

Invoked when: a stage's average TAT exceeds its design assumption by more than 50%, or a weekly analysis cycle runs

  • Detects bottlenecks at the stage level — identifying where applications are spending disproportionately more time than the stage's design assumption. A bottleneck is distinguished from a normal distribution of application complexity by its systemic nature: a single complex application taking longer than average at the credit assessment stage is not a bottleneck; a sustained pattern where the average credit assessment TAT across all applications is 50% above its target is a bottleneck. The agent identifies the latter through trend analysis over the prior 7 days, not from single-application observations.
  • Characterises the bottleneck by its likely type — volume bottleneck (more applications arriving at a stage than the stage can process in the available time), quality bottleneck (applications arriving at a stage with errors that require rework before the stage can be completed), or dependency bottleneck (a stage is waiting for an external input — valuation report, bureau refresh — that has a longer turnaround than assumed). The bottleneck type determines the appropriate remediation: a volume bottleneck requires capacity addition; a quality bottleneck requires upstream process improvement; a dependency bottleneck requires external SLA management.
  • Produces a weekly TAT analysis report — the average, median, and 90th percentile TAT for the full onboarding journey and for each individual stage, by product type and application channel. The P90 figure is the most operationally significant: a process where 90% of applications complete within the SLA target is meeting most borrowers' expectations even if the mean is slightly above target; a process where the P90 is significantly above the mean indicates a long tail of applications with unacceptably long TATs.
Output: Bottleneck alert — stage identified, bottleneck type characterised, trend data supporting the identification. Weekly TAT analysis report — average, median, and P90 by stage, product, and channel. Trend comparison against the prior 4-week baseline. Bottleneck type hypothesis for operations head investigation.

SLA Breach Escalation

Per breach · immediate escalation to operations head

Invoked when: an application's cumulative lender-controlled TAT exceeds the SLA commitment

  • Escalates every SLA breach to the operations head immediately — with the application reference, the product type, the channel, the stage where the breach occurred, and the total elapsed time. The escalation includes the full TAT timeline for the breached application — where time was spent at each stage — so that the operations head can identify the primary delay driver without additional investigation.
  • Triggers the borrower communication workflow for SLA-breached applications — notifying the operations team to contact the borrower with an updated TAT and an apology for the delay. Borrowers who are not proactively communicated with after a SLA breach are more likely to escalate to the Banking Ombudsman; proactive communication converts a SLA failure into a managed relationship event.
  • Logs every SLA breach with its root cause stage, product type, and channel — building the dataset for the weekly TAT analysis and the operations head's process improvement agenda. A breach that occurs in isolation is an operational exception; a pattern of breaches in a specific stage, product, or channel is a systemic process problem that requires redesign rather than individual case management.
Output: Immediate SLA breach escalation — application reference, TAT timeline, breach stage, and total delay. Borrower communication trigger dispatched to operations team. SLA breach log updated — breach characteristics recorded for pattern analysis and weekly TAT reporting.

Knowledge base

LOS — Application Stage Event Stream

Real-time stage transition events — the primary data source for the TAT clock and bottleneck detection. The event stream must capture both stage entry and stage exit times for each application.

SLA Commitment Register

The committed TAT for each loan product and each application stage — the targets against which the TAT clock is measured. Maintained by the operations head and updated when product SLAs change.

TAT History — Prior Applications

The historical TAT data for completed applications — the baseline against which current performance is measured and against which the weekly trend analysis is conducted.

Stage Design Assumptions

The time budget allocated to each stage in the process design — the reference against which bottlenecks are identified. Updated when the process is redesigned.

Onboarding Quality Agent AI — QC Hold Data

QC hold start and end times included in the TAT breakdown — distinguishing QC-related delays from other stage delays in the bottleneck analysis.

Pre-Training — Operations SLA Monitoring Knowledge

TAT monitoring methodology, SLA management for lending operations, and bottleneck detection best practices up to knowledge cutoff.

Hard guardrails

Will notOverride any application stage to meet an SLA target. SLA performance is achieved through the operations team's process management — the agent monitors and alerts, it does not intervene in the process by skipping stages, reducing checks, or releasing applications ahead of their stage completion.
Will notExclude hold time from the TAT clock without a corresponding resume event. Hold time attribution requires both a hold start event and a hold resume event in the LOS — an application that goes on hold without a recorded hold start is tracked as if the hold time is lender-controlled TAT.
Will notReport a bottleneck without trend evidence. A single application exceeding its stage budget is not a bottleneck alert — the bottleneck detection requires a sustained pattern over the prior 7 days before an alert is raised. Single-application anomalies are visible in the TAT dashboard but do not trigger bottleneck escalation.
Will notSubstitute a proactive borrower communication for the operations team's contact. The agent triggers the communication workflow — the operations team makes the contact. An automated message without human follow-up is insufficient for a SLA breach that may require negotiation of a revised commitment.

Known limitations

The TAT clock depends on the accuracy and completeness of stage transition events in the LOS — if the LOS does not capture a stage entry or exit event, the TAT clock for that application at that stage will be inaccurate. Missing events create apparent TAT anomalies (an application that appears to spend zero time in a stage, or an indefinitely long time in a stage) that distort the bottleneck analysis.Conduct a LOS event audit before activating the SLA monitoring agent — confirming that every application stage generates a corresponding entry and exit event in the LOS event stream, and that the event timestamps are accurate. Fix missing events in the LOS before the agent begins monitoring, not after.
The hold time exclusion from lender-controlled TAT depends on the hold type being correctly classified in the LOS — a hold that should be classified as borrower-caused (waiting for documents) but is classified as lender-caused (internal processing hold) will incorrectly count as lender-controlled TAT and make the lender's performance appear worse than it is.Review the hold type classification scheme in the LOS with the operations team before activation — ensuring that every hold type is correctly classified as borrower-caused or lender-caused, and that the operations team consistently applies the correct hold type when they place an application on hold.
Agent Profile · Onboarding SLA Agent AI · LendingIQ · Agent #82Last updated April 2026 · For internal use

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