From Indirect to Irreplaceable: Growing Lifetime Value of Auto Loan Members
From Indirect to Irreplaceable
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[00:00:00] Welcome to this Deep Dive, a collaboration where human curiosity meets AI synthesis to explore the power of data in AI driven solutions, unpacking complex topics from the source material you bring us. I'm Tom, an AI host. And I'm Anna, also an AI host. Hello everyone. We're here to, uh, break down complex financial topics into real actionable insights.
That's the goal. Welcome.
And today our mission, while it's a big one for credit unions, we're tackling how to turn those. You know, transactional indirect auto loans, the ones that come through the dealership, exactly how to turn those kind of cold single product relationships into deep, long lasting member connections. It's crucial.
We've got a stack of sources here detailing the um. The [00:01:00] financial need for this. Mm-hmm. And the actual data driven strategies to convert these borrowers who often don't even realize their members right into high member lifetime value or MLV members. Yeah. It's a fundamental tension, isn't it? Isn't it?
Indirect lending is fantastic for getting new names in the door. Huge volume potential, right? A big subtle, but that transaction, it happens at the dealerships, so the member often feels well invisible to the credit union itself. They just have the one loan. Maybe minimal contact. And then once the loans paid off, poof, they're gone.
High attrition risk. That invisibility, that's really the core problem we're digging into. They got a loan, sure, but they didn't really join anything in their minds. Exactly. And that means a huge amount of potential, long-term value is just evaporating. Okay, let's unpack this. Let's start with the urgency.
Why is fixing this so critical right now? Well, maximizing that MLV, it's not just a nice idea anymore. It's really foundational because credit unions are facing, uh, quite a [00:02:00] storm of financial headwinds. Yeah, we're seeing loan growth slow down pretty significantly. A drop from what, 8.6% down to 5.6% just in Q4 of 2023.
That's a sharp drop. It is. And at the same time, funding costs are going up, which is really squeezing their net interest margins. And I imagine the cost of just running the place isn't helping those margins either. Not at all. Operating expenses are climbing things like professional and outside services jumped, uh, 8.2% year over year.
Wow. And all that together, it pushed the return on assets, the ROA down to just 0.74%. Yeah, that's, that's pretty lean. Yeah, very lean. So when your margins are that tight. Your costs are rising like that. Well, you just can't afford inefficiency in how you acquire and keep members, especially not those indirect ones.
Okay, so you got slower growth, rising costs, tighter margins, and then there's the competition, which feels fiercer than ever. Oh, absolutely. You know, we see the big banks throwing money at customer acquisition, like those $900 bonuses from Chase. You sometimes hear about Right [00:03:00] buying market share and the fintechs, they're grabbing what, 40% of new checking accounts.
Especially with younger demographics. Yeah, gen Z is, I think the stat was three times more likely to name a FinTech as their primary provider. So with that kind of pressure, how does a credit union even start to compete? Can that traditional relationship model still win? Well, what's fascinating here is that even the digital first players have their own challenges.
Convenience isn't everything. Hmm. The sources actually point out, uh, chime, for example. Yeah. Their status as the primary provider for Gen Z, it actually dropped, went from about 12.3% in 2023, down to 6.3% in 2024. Oh, interesting. So there's not as sticky as maybe people thought. Exactly. It shows there's an opening.
That relationship driven value, the thing credit unions are built on, it can win back market share and converting those indirect members, the ones you already have, that's honestly the most efficient way to deliver that value and build loyalty. [00:04:00] Okay. Let's talk about that potential then the size of the opportunity here, because the numbers are, well, they're pretty stark.
They really are. If only say 10 to 15% of these indirect members. Ever open another product without someone actively reaching out, which is the typical range. Yeah, that means 85, maybe 90% of them are just sitting there. Untapped potential, pure untapped potential. That's the whole business case right there.
You've already paid to acquire them. The acquisition cost has sunk, right, the investment's been made. Now you just need to actually realize the return on it. And the sources showed that even relatively small strategic efforts pay off big time. Like personalized outreach. Just actually talking to them like an individual.
Yeah. That alone can increase conversion rates by 12 percentage points. Just like that. It makes sense that personalization, it signals they're more than just the loan, more than an account number. It moves them into feeling like a real member. Exactly. It taps into that [00:05:00] relationship. DNA we were talking about.
Here's where it gets really interesting. We're talking about potentially transforming this. Single, often low engagement loan into a serious revenue stream. Mm-hmm. The sources are pretty clear. Engaged members. The ones with multiple products at a credit union, they generate somewhere between 20 $504,000 in member lifetime value over 10 years.
That's a huge difference from a single auto loan that just runs off a massive difference. That one car loan becomes a real engine for the credit union if they nurture it and that impact it spreads throughout the whole organization. Think about this, just a 5% increase in member retention, okay? It can boost profitability by 25% or even more, 25% from a 5% retention bump.
Yes, because keeping a member is almost always cheaper than acquiring a new one. And once a member has say three or more products, the cost to serve them tends to drop while the revenue they generate goes way up. Right. They're more embedded. Exactly. So if a credit union [00:06:00] is looking to improve that ROA.
Grow non-interest income. Mm-hmm. Tackling this indirect member issue, it's probably the single most powerful lever they have. It really does sound like it, but okay. This conversion, it doesn't just happen automatically, right? You need a plan. No magic involved. No. It takes deliberate steps, timely engagement, personalized messages, and uh, usually it's driven by data tools that can help predict, churn, or identify opportunities.
So let's get into the how. What are the proven strategies? Right? The sources lay out about five core strategies. The first one is just fundamental early welcome outreach. Yeah. Early. How early within days of the loan closing. Yeah. Not weeks later when you know the excitement's gone. Makes sense. What's in that?
Welcome. It needs to actually welcome them. Explain the tangible benefits of membership. Not just the loan, and this is important, introduce them to the digital banking tools. Get them logged in. So that first contact sort of bridges the gap from the dealership experience. It resets their [00:07:00] perspective precisely.
It says, Hey, you're part of our community now, and here's what that means for you. And even a simple well-timed welcome email can boost engagement rates by 30% or more. 30% just from a welcome email if it's done right. Yes. Then strategy two gets more targeted Behavior-based product offers. Meaning? Meaning stop sending generic one size fits all.
Promotions. That mostly just annoy people, right? Like offering a mortgage to a 20-year-old who just got their first car loan. Exactly. Waste of time and money. Instead, use data models. The sources talk about next best product or NBP engines, NBP. Okay. These tools analyze the data to predict which product that specific member is most likely to need or want next.
Ah, so it's personalized prediction. Yes. Based on their likely income, their life stage, maybe even how they prefer to be contacted, email, app notification, whatever. It makes the outreach relevant. Relevance drives results, I assume drives much higher conversion rates up to three times higher potentially, [00:08:00] because the offer actually makes sense for them.
Okay, so timely welcome then relevant offers. What's strategy three? Strategy three is about proactive cross sell timing. Think automation, but smart automation based on the member's journey. Okay. Timing it, right? Gimme an example based on that auto loan. Sure. So maybe in the first week while the loan is top of mind, you prompt them to set up auto pay or download the mobile app.
Make it easy, right? Capitalize on that initial activity. Then maybe 30 days after funding you offer a checking account. Try to become their primary financial institution quickly. Okay. Then perhaps 60 days in, once they've shown some engagement, maybe use the app. You introduce a credit card offer. It's about sequencing the offers logically, so you're building the relationships step by step, using data to guide the timing.
Exactly. Consistent, relevant touchpoints. But you know, automation isn't always enough, especially for the really high potential members, right? Some people need more of a personal connection, which brings us to [00:09:00] strategy four. The human touch for high value segments. Oh, okay. So identifying the potential stars.
Yes, the data tools can flag those indirect members who look like they have strong income, good credit. Maybe they fit the profile for meeting a mortgage down the road, or even a business loan. The ones who could generate significant MLV precisely, those members shouldn't just get automated emails. They need to be routed to a real person, member services, maybe a branch specialist for an actual conversation.
A personal check-in. So using your human resources strategically where they'll have the most impact. Makes sense. It's high touch for high value prospects. And then the final piece, strategy five is crucial. Win back before they walk away. The defensive move catching them before they churn. Absolutely. MLV isn't just about getting new products, it's about keeping the member long term.
Mm-hmm. So you have to monitor for signs of disengagement. What are the red flags? The sources mention things like, uh, no logins or digital [00:10:00] activity within the first 90 days. That's a big one. Okay. Or if they haven't taken up any additional product by the six month mark, those are signals they might be drifting.
And if you see those signals intervene, use retargeting campaigns, maybe offer a specific incentive, but do it before that auto loan matures and they just disappear. Got it. So welcome them. Make relevant offers. Time it right. Add human touch for the best prospects and watch for disengagement. That's the core playbook.
And underlying all of this, it sounds like, is pretty sophisticated use of data moving way beyond just basic demographics. Oh, definitely. We're talking predictive segmentation using AI powered personas. I. Profiles that help identify which types of indirect members are most likely to say, open a new account soon, or adopt a credit card, or maybe be receptive to a mortgage offer later.
It focuses your outreach efforts so you're not wasting resources on people who just aren't ready or interested. Exactly. Maximize that. ROI. The engine driving. A lot of this is that [00:11:00] next best product tool you mentioned? Yes. The MVP engine, it's really the intelligence layer. How deep does it go? You mentioned behavioral, demographic, geographic data.
Mm-hmm. How does that all come together for like one specific recommendation? Okay, so imagine the engine sees a borrower lives. Say a really expensive zip code. That's geographic data, right? But it also sees from their account activity, behavioral data, that they're maybe six months away from paying off some high interest credit card debt.
Okay? So the engine won't push a mortgage right now. Instead, it might recommend a specific product, like a high value, low rate balance transfer, credit card offer. Ah, targeted to their immediate financial situation. Exactly. And it might specify the best channel, maybe a targeted email or an in-app message because they use the app frequently and the best timing perhaps right after their typical payday hits.
Wow. So it's product, channel, and timing. Highly specific, very specific, ensures the outreach is relevant [00:12:00] and has the best chance of success, not just noise. It really sounds like a fundamental shift in perspective for credit unions moving beyond just. Processing that initial loan transaction. It is, it's shifting from seeing that loan as the end point to seeing it as the starting point for a potentially profitable long-term relationship.
A growth engine. Really, if we connect this to the bigger picture, yeah. Yeah. The whole focus moves. It moves from the sort of cost and hassle of originating the loan to maximizing the lifetime value, the profitability of that member relationship over years and in the current environment, tight margins.
Tough competition. You're saying that shift isn't just strategic, it's necessary. I think it's essential. Essential for sustainable growth. Maybe even survival for some. Okay. So the knowledge you've shared today, these strategies? Mm-hmm. They're immediately actionable. They show a clear path to boosting conversion and that crucial MLV Absolutely.
Here is a final provocative thought for you, our listener, to mull over. We know [00:13:00] credit unions are up against fierce competition, slowing growth, but we also know this kind of data-driven personalized engagement really works. One source even noted that super precise targeting, maybe even using psychographic.
Data like attitudes and lifestyle. Exactly. That kind of targeting can cut marketing spend by up to 85%, an 85% reduction. That's huge. It is. So the question for you is. What assumptions are you making about your current best members, your highest value members that might be stopping you from using that same kind of deep segmentation to build loyalty with your newest, indirect borrowers, right from day one.
Hmm. What assumptions are holding you back from that 85% efficiency gain? That's a powerful question. Food for thought. Indeed. Thank you for joining us for this deep dive. Always a pleasure. So what does this all mean? It means recognizing that sometimes your newest, seemingly least engaged members actually represent your single biggest growth opportunity.
We'll catch you on the next deep dive, and of [00:14:00] course, if you enjoyed this deep dive into data and ai, make sure to subscribe to the Blast Point Deep Dive podcast for more amazing stories from the cutting edge of technology. We'll be back soon with another episode exploring how data and AI are shaping the world around us.
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