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Credit unions that moved beyond bureau scores and isolated point solutions grew loans nine times faster than the industry median over the trailing twelve months, without a corresponding increase in credit risk. That gap did not come from better individual tools. It came from connecting fraud intelligence, underwriting, and pricing into a single decisioning layer where every signal informs the next and which learns from each decision.

Most lending stacks are still built the other way: capable components running in sequence, with no shared intelligence between them. This session examines what the shift to an integrated decisioning layer involves, what the data shows about the gap it creates, and what a credit union needs to evaluate about its current infrastructure to understand where it stands.

Key Takeaways:

How connecting fraud, underwriting, and pricing into a shared intelligence layer produces compounding improvements that structurally separate it from point solutions, regardless of how capable each individual model is on its own.

A practical framework for identifying your current system's blind spots, what those blind spots cost at different asset sizes, and what a move toward integrated decisioning requires in time and organizational effort.

Your underwriting engine is doing half its job.

It approves. It declines. It stops there. The decision gets made. The learning doesn't.

AI can change that, but for most credit unions, it's still deployed at the gate and left there.

The real opportunity is what AI does with the entire member journey that follows that decision.

One system of intelligence that learns continuously from every loan decision, member interaction, and portfolio outcome, running the full member journey: fraud, cross-sell, limits, early warning, auto lending. One engine. Decisions that improve on their own.

In this webinar, we'll show how - with live metrics and governance mechanics that keep decisioning explainable, auditable, and regulator-ready.

Key Takeaways:

The Lifecycle Playbook - How to map AI decisioning across every use case and plug it into your existing LOS and CRM, so you're building integrated intelligence, not accumulating point solutions.

Continuous Learning in Practice - How to feed post-origination signals back into pricing, limits, and early warning models.

Governance Without the Friction - How to run lifecycle decisioning with audit trails, fair-lending checks, and bias monitoring - board-ready, regulator-ready, and unified in one view.

Every credit application carries more than a simple yes or no. In the seconds after a member hits "apply," your credit union needs to assess credit risk, spot potential fraud, set the right price, and identify opportunities to deepen the relationship. Traditionally, these decisions happen in silos, scattered across different models, systems, and stages of the lending workflow.

This webinar explores how MeridianLink Multiscore integration with Scienaptic AI lets credit unions return multiple actionable signals from a single application evaluation. Instead of just approve, review, or decline, you also get real-time insights on fraud risk, rate recommendations, and cross-sell or balance optimization eligibility, all within the lending flow.

The session focuses on how Multiscore functionality strengthens three critical areas: fraud detection and prevention, balance and offer optimization, and smarter auto lending through LendSmart.

Attendees will learn how delivering these insights upfront reduces manual intervention, accelerates decision timelines, and enables more personalized member experiences without adding operational complexity. The discussion will also highlight how these capabilities remain explainable, compliant, and fully embedded within existing lending workflows.

Key Takeaways:

1. Turning one application into multiple, real-time lending decisions

2. Activating fraud, pricing, and growth signals together at the point of decision

3. Driving faster automation and more personalized member experiences without added complexity

Auto lending looks disciplined on the surface, but beneath it sits a quiet problem: most auto loans are priced using static rate sheets that fail to reflect real deal risk. Vehicle depreciation, deal structure, market conditions, and portfolio objectives are not fully considered, leading to mispriced loans, inconsistent returns, and lost members in an increasingly competitive market.

In this session, we introduce LendSmart Auto, our AI-powered pricing optimization engine for auto lending. LendSmart evaluates each loan on an individual basis by integrating collateral valuation, predictive risk modeling, and portfolio ROA targets to propose the appropriate rate and structure tailored to that specific loan application. Pricing decisions move from broad assumptions to precise, data driven outcomes.

Designed for lending and risk leaders, this webinar explains how modern precision pricing works in practice, why it delivers stronger margins without raising member rates, and how credit unions can bring consistency, fairness, and confidence back into auto lending.

Key Takeaways: Why traditional rate sheets systematically misprice auto loans How deal level pricing improves both portfolio returns and member experience What AI driven pricing looks like in a real credit union environment

AI is no longer just a tool for underwriting - it’s a catalyst for growth. But most credit unions haven’t unlocked its full potential. Lending experiences remain fragmented, and growth efforts often stall at the point of approval.

The real opportunity lies in applying AI across the entire member journey - predicting needs, personalising offers, preventing risk, and deepening relationships.

That requires more than just AI models. It demands a unified strategy across lending, marketing and member expereince, built on shared data, real-time intelligence, and cross-functional collaboration.

In this session, we’ll explore how credit unions can use AI to:

• Grow approvals without compromising risk

• Personalise experiences across prescreens, originations, fraud prevention, cross-sell, and collections

• Upgrade data and decisioning infrastructure to support smarter, faster decisions

Smarter lending isn’t just about better decisions - it’s about sustainable, scalable growth.