In consumer lending, demand doesn't arrive politely. Interest rates shift, credit windows open and close, and suddenly a fintech built on speed is fielding two or three times the volume it forecast — with the same customer expectations attached.

That is the operating reality for a leading AI-powered lending platform that connects borrowers to bank and credit union partners using machine learning to look beyond conventional credit scores. When application volume surges, borrowers still expect a knowledgeable human on the line the moment they call. When volume drops, the cost of a fixed contact center becomes a drag on the business.

How do you build a customer-facing organization that can scale up and back down without breaking service quality, blowing up costs, or burning out your people? The lender's answer, built with TTEC over more than a decade, is a flexible staffing model that has quietly become one of the most reliable pressure valves in fintech customer experience.

The problem

The client operates in one of the most volume-volatile corners of consumer lending. Its product portfolio spans personal loans, small dollar loans, and home equity lines of credit (HELOC). It is purpose-built for credit-underserved consumers who don't fit neatly inside a traditional FICO score. Demand for that product is highly sensitive to macroeconomic conditions -- application volume can double, or halve, faster than a typical workforce plan can react.

The client supports borrowers via voice channels with loan application status inquiries, document submission guidance, account access issues, escalated calls tied to loan denials or APR disputes, and real-time identification of system and website issues on the client's platform.

Its growth and an unplanned volume surge became a burden with numerous pain points:

Traditional fixed-staffing models were too expensive and too rigid. Constant hiring and offboarding in response to volume swings drove up payroll, benefits, and training costs while eroding quality — every ramp meant a wave of green associates.

Volume forecasts underestimated actual demand, particularly during a dramatic sustained surge that lasted nine months.

Associates on virtual computer infrastructure were losing up to an hour per shift to login failures, VPN issues, and headset problems, which were direct hits to productivity and morale.

Escalated callers were a daily reality. In a business that doesn't negotiate loan amounts, denials, or APR, de-escalation skill is the whole game.

Authentication compliance by confirming every caller before discussing account information was both a regulatory requirement and a fraud control that had to hold up under high volume.

Data quality was slipping. Associates were over-using a generic "Other" disposition code, masking the real reasons customers were calling and starving the client's product teams of clean contact-driver data.

For borrowers, this meant longer waits during peak periods, delayed funding when account access broke down, and higher-stakes conversations at exactly the moments people are most anxious about their financial futures. For the lender, it meant reactive staffing, mounting cost pressure, and an intelligence gap about their own customers.

TTEC was uniquely positioned to solve this because we already had 12 years of institutional knowledge, proven outcomes, and relationship strength. The client originally partnered with us in 2014, making this one of TTEC’s longest-standing fintech relationships. 
 

Our solution

Working together with the client, we designed and now operate TTEC’s FlexEXstaffing model built specifically for volume-volatile lending — a dynamic hour-fluctuation model that replaced the traditional fixed-hours BPO arrangement. When demand climbs, our onshore associates' hours flex up. When it recedes, hours are dialed back. Part-time colleagues who prefer flexible schedules are a structural component of the model, not an afterthought.

The result is that TTEC quickly scaled up more than 50% FTE without a new hire class, and scaled back down without layoffs. Payroll, benefits, training, and onboarding costs came down for both parties without sacrificing service quality because experienced associates remained on the program year-round instead of cycling out.

The FlexEX model is the operational spine, but three other pieces made the difference during the surge and beyond:

Rapid scale with quality intact. When loan volume ran far ahead of the client's forecast, we scaled 3x associates in under five months — back-to-back hiring classes, including one class of 50 associates — while holding QA scores at or above the 92% target throughout the ramp.

Full escalation ownership. TTEC's leadership team handled 100% of escalated calls internally, both live transfers and scheduled callbacks. The client's internal teams didn't absorb the escalation load, and the client has demonstrated its trust by granting TTEC account-level system access typically reserved for internal staff.

Proactive intelligence for the client. In multiple documented cases, TTEC identified new product changes, system bugs, and emerging applicant issues before the client's own internal teams were aware — prompting the client to expedite associate training and product fixes. The frontline became an early-warning system, not just a call queue.

We also moved fast on operational hygiene. When the client raised a concern that associates were over-using the "Other" disposition code, we identified the root cause, retrained associates, and drove the code from a top 10 occurrence to outside the top 30 in a single month. Our WFM team now issues staffing recommendations two months in advance based on the client's ordered hours and historical patterns, so hiring decisions get made before gaps open — not after.

Two platform upgrades are currently in flight to compound those gains: migration to Genesys as the unified phone, QA, and workforce management platform, and a transition from virtual computers to client-provided laptops that is already recovering tech-related downtime at the start of every shift. Included in the new platform are AI tools including note summaries and an agent assist knowledge bot. In addition, an active authentication compliance initiative has shown month-over-month improvement, and the client has expressed satisfaction with the trajectory even before the target is fully reached.

Results

As a result of our work, the client has maintained 100% of its KPI targets, including <2% abandon rate, AHT of less than 7 minutes, 80% of calls answered within 20 seconds, QA score of 92%, and 92% schedule adherence.

The FlexEX model worked as designed by flexing down 1,000 hours in one month, saving the company hiring, onboarding, and training costs and maintaining quality performance when volume slowed.

The program is now positioned to absorb the start of the busy season with a WFM plan already in motion, rather than reacting to another surge in progress.

Beyond operations, TTEC is actively engaging with the client's VP-level leadership to bring TTEC's broader solution portfolio — analytics, automation, and WFM tooling — into the conversation. The client is also preparing a CX pilot with us that de-prioritizes handle time and other productivity metrics to use proactive support to drive loan acceptance rates and other outcomes.