Cases, tasks, and smart queues
Work is modeled as cases and tasks, routed through smart queues with priority aging — so the oldest, riskiest work surfaces instead of sinking.
Servicing Control Plane · part of the LendEasy platform
Keep servicing work, policy checks, and evidence in one place
Manage cases, tasks, and priority queues for people and AI. LendEasy checks policy before each action, tracks contact limits in real time, and records the result.
Servicing mission control
Humans and AI agents · one set of queues
Smart queues · priority aging on
Collections48Hardship12Disputes7Bankruptcy5
SLA health · business-hours calendars
On track
164
Due soon
6
Breached
1
Aged to the top of the queue
Case #C-2417 — Collections
Next action: outbound call · waiting 3 days
The oldest, riskiest work surfaces instead of sinking — and every action still clears the gate
The control plane
Put servicing policy into the workflow
Cases, tasks, queues, calls, and messages all use the same policy checks before an action reaches a borrower.
Omnichannel interactions
Keep voice, email, chat, and voicemail on the case, with consent, timing, and contact limits checked for each channel.
Rules with a clear source and version
Each rule records the regulation or policy it implements, the jurisdiction it covers, and when that version took effect.
Checked again before action
Eligibility is evaluated when a message is sent or a call is placed, not only when the work enters a queue. Missing or stale information holds the action.
Real-time contact budgets
Configured contact-frequency thresholds are computed per debt in real time and can align with Regulation F presumptions where applicable, alongside state rules and lender policy.
Rules matched to product type
The engine knows whether an obligation is consumer or commercial and applies only the rules configured for that product type.
Cases, tasks & queues
Keep urgent and aging work visible
Every servicing task belongs to a case and a queue. Routing considers skill, capacity, risk, and wait time so important work reaches the right person or AI agent.
Smart queues with priority aging
Queues route by skill, capacity, and policy — and re-rank continuously as work ages. SLAs run on business-hours calendars, so a case opened Friday afternoon is not already breached on Monday morning. Humans and AI agents pull from the same queues, under the same priorities, visible in the same command center.
Omnichannel, on the case
Voice, email, chat, and voicemail stay attached to the case. Consent, timing windows, and contact limits are checked per channel, and each interaction appears in the case timeline.
The compliance gate
Check policy before the action
Messages, calls, and payments are evaluated when they are about to run, using current account facts and the applicable rule version.
Checked before execution, not reported after
Every send and every dial passes the compliance engine at the moment it happens — for humans and AI agents alike. There is no path around the gate.
Every rule answers for itself
Each rule records its source, jurisdiction, effective date, and version, so a past action can be traced to the rule used at the time.
Missing information holds the action
If required information is absent or too old to support a decision, the action waits for updated facts.
Budgets computed in real time
Configured contact-frequency thresholds are live, per-debt computations workers can see before they dial, rather than a nightly reconciliation report.
Events & reconciliation
Turn system mismatches into assigned work
LendEasy compares expected outcomes with events from the core. If a payment, protection, or status change is missing, it opens a case with an owner and due date.
- Ledger facts include an as-of time, so each decision knows how current its information is
- Core events confirm outcomes continuously, keeping the servicing view aligned with the system of record
- If an expected payment or status change does not appear, LendEasy opens an assigned case instead of leaving the mismatch in a report
A mismatch becomes work
A promise with no matching payment, a protection that should have stopped outreach, or an unconfirmed status change opens a case in a queue with an owner and due date.
The evidence trail
Every action leaves a record built for the examiner
Each decision records the facts used, their as-of times, the rule versions checked, any human approval, and the final outcome. Records are linked and tamper-evident.
Tamper-evident by construction
Records are hash-chained — each commits to the hash of its predecessor, so any after-the-fact edit breaks the chain visibly. The graph is queryable, and litigation or exam evidence exports in one click rather than being reconstructed from logs.
One trail for humans and AI
AI and human actions share one audit trail. AI records also include the model and prompt versions used, so reviewers see the same core facts regardless of who did the work.
Part of the LendEasy platform
How the platform pieces connect
The workspace, AI agents, and lending core all use the policy checks and audit trail provided by the control plane.
FAQ
Questions servicing leaders ask
It is the layer between your servicing team and system of record. It manages cases, tasks, queues, calls, and messages. Before an action runs, it checks the configured policy and records the outcome, whether a person or AI did the work.
Follow one action from queue to audit record
Bring a policy-sensitive workflow or reconciliation problem. We will trace a real action from intake through policy check and final outcome, against our core or yours.