---
title: "Risk Is a Growth Function"
episode: 138
podcast: "The LeanScale Podcast"
publisher: "LeanScale"
guest: "Lalitha Rao"
guest_title: "Chief Risk Officer, Imprint"
date_published: 2026-10-13
date_modified: 2026-10-21
duration: 00:43:02
word_count: 6892
topics: ["gtm-strategy", "enterprise-sales", "sales-leadership", "ai-in-gtm", "revenue-operations"]
canonical_url: https://www.leanscale.team/knowledge/podcast/lalitha-rao-tyler-dibble-imprint-risk-is-a-growth-function/
source: "LeanScale Knowledge Hub — https://www.leanscale.team/knowledge"
license: "Free to quote and cite with attribution to The LeanScale Podcast."
---

# Risk Is a Growth Function

_Lalitha Rao (Chief Risk Officer) and Tyler Dibble (Chief Revenue Officer) on running risk and revenue at Imprint off one profitability target: partner data as underwriting signal, the risk leader in the sales room, no handoffs across seven-year partnerships, and owning every word your AI helped write_

**Episode 138 · The LeanScale Podcast**  
Lalitha Rao, Chief Risk Officer, Imprint · Hosted by Anthony Enrico  
Published October 13, 2026 · Updated October 21, 2026 · 00:43:02  
Canonical: https://www.leanscale.team/knowledge/podcast/lalitha-rao-tyler-dibble-imprint-risk-is-a-growth-function/

**Topics:** GTM Strategy · Enterprise & Public-Sector Sales · Sales Leadership · AI in GTM · Revenue Operations


## Executive summary

This is the first two-guest episode of The LeanScale Podcast, and both guests are a CRO at the same company. Lalitha Rao is Imprint's Chief Risk Officer. She spent several years at Capital One, led small business risk at Stripe and ran credit policy at Square Financial Services. Tyler Dibble is Imprint's Chief Revenue Officer, with a background in consumer fintech lending at SoFi, Chime and OnePay. Imprint is a payments and loyalty platform that runs co-brand credit card programs for brands including Booking.com, H-E-B, Crate & Barrel, Rakuten and, as of the day the episode was recorded, Kroger.

The episode starts with a role reversal. Asked about their last real disagreement, Lalitha describes pushing a policy expansion that would use new alternative data sources to send fewer applicants through identity verification, which raises approvals and conversion. Tyler was the one who asked whether this was the right environment for it, given how much AI has improved the tools available to fraudsters. They settle disagreements like this easily because, beyond their separate team metrics, both are accountable for company profitability and for helping partners grow. Lalitha says she is not paid to minimize losses. Her job is to find ways to say yes safely within the risk appetite. Tyler says that when the target is shared, disagreements are about pace and test size, not direction, and no tiebreaker is needed.

Partner data is what turns risk into a growth lever. From Rakuten, Imprint can see how long someone has been a member and how their spend and engagement have trended. Lalitha calls this orthogonal signal that other issuers can't get from the credit bureau, and Imprint uses it to approve more applicants, size credit lines to usage and give credit line increases after as few as two on-time payments. She makes that case in enterprise sales conversations herself. Tyler's sales motion starts from the partner's business metrics, such as trips booked, store visits and share of wallet, rather than cardholder counts. Logos are won through sales, mostly via partner word of mouth; cardholders through marketing. Because Imprint built its own processing stack rather than relying on TSYS or Fiserv, it can offer things like SKU-level rewards at H-E-B, and those features bring in inbound interest from other brands.

Both leaders describe a no-handoffs model. The team that lands a brand also grows the program, and the risk team works on partner data from the first day of a partnership that typically runs seven years or longer. On AI, Lalitha credits Imprint's CTO and tech team with building a central platform first: standardized data access, permissions, controlled deployment and observability. Her team then automated weekly reporting and governance documentation and built agents that do work that used to need teams of analysts. Over about fifteen months, revenue grew about 2.5x and the loan book grew 150%, newer cohorts have lower loss rates, and the risk team grew by only four or five people. Tyler's rebuilt martech stack lets the team launch a new partner without adding headcount in proportion. Both insist on accountability: "that's what the agent told us" is not an answer for a partner, and "Claude got it wrong" is not an excuse inside the company.

The episode is most useful for revenue executives, founders and RevOps leaders who have to bring risk, legal or finance into the go-to-market motion, and for anyone in embedded finance, partnerships or long-cycle enterprise sales. It shows shared incentives between functions that usually pull against each other, and a practical order for adopting AI: platform first, use cases second.


## Key takeaways

1. **Pay the risk leader to find ways to say yes** — Lalitha describes risk at Imprint as something other than a traditional control function. She is not incentivized to minimize losses. Her role is to drive growth and find ways to say yes safely within the company's risk appetite. In the most recent disagreement between the two leaders, she was the one pushing to raise approvals and reduce identity-verification friction.
   _Why it matters:_ If risk, legal or security is paid only to prevent downside, it will act as a brake on every deal. Giving that function a growth objective with a stated risk appetite changes which questions it asks.
   _For:_ Revenue Executives, Founders

2. **A shared profitability target removes the need for a tiebreaker** — Each team tracks its own leading indicators. Lalitha watches approval and offer-acceptance rates, and Tyler watches accounts added. Both are accountable for the same outcome: company profitability and helping partners grow. Tyler separates what each team measures from what both are accountable for. With a shared North Star, he says, disagreements are about pace or the size of a test, not about direction.
   _Why it matters:_ Functions that pull against each other usually have competing scorecards. Keep separate team metrics, but make the accountable outcome the same for both leaders, so that disagreements become questions about sequencing.
   _For:_ Revenue Executives, Founders, RevOps Leaders

3. **Optimize for growth that lasts through the cycle** — In the disagreement, Lalitha wanted to use new alternative data sources to send fewer applicants through identity verification. Tyler asked whether this was the right time, given that AI has also improved fraudsters' tools. She walked him through the data and the safeguards, and the expansion went ahead. Both describe the goal as growth that is durable and resilient through the economic cycle. Tyler adds that overextending a cardholder hurts the customer and also the partner brand that customer is loyal to.
   _Why it matters:_ When growth depends on a partner's customers, a bad outcome for one customer is also a problem for the partner relationship. Questioning the timing of an expansion is part of protecting that relationship, not resistance to growth.
   _For:_ Revenue Executives, Sales Leaders

4. **Partner data gives underwriting signal the bureau can't** — From a partner like Rakuten, Imprint can see how long a customer has been a member, how they have transacted over time and how their spend and engagement have trended. Lalitha calls this a deep signal of intent and loyalty, orthogonal to credit bureau data and not available to other issuers. It lets Imprint approve applicants whose credit history has a blemish, size credit lines to actual usage, and increase engagement for the partner.
   _Why it matters:_ In any embedded or partner-led business, the partner's first-party data can be the main competitive advantage. Asking for that data early, as part of the deal, is a commercial decision as well as a technical one.
   _For:_ Founders, Revenue Executives, RevOps Leaders

5. **Sell to the partner's business metrics, not your product's vanity count** — Tyler says the important number is not how many cardholders a partner has. It is the behavior the partner wants and the business metrics it wants to move, such as visits, trips, the types of trips booked or share of wallet in its stores. The card program, its value proposition, its reporting and its targeting are designed around those goals. He also warns that scale matters: driving 10x the outcome across only 12 cardholders does not matter to the partner's business.
   _Why it matters:_ Enterprise partnerships are easier to sustain when your reporting uses the buyer's terms. Track both the behavior change and the number of people it reaches, because either one alone is not enough.
   _For:_ Sales Leaders, Revenue Executives

6. **Bring the risk leader into the sales room** — Lalitha joins enterprise sales conversations. Imprint's advantage comes from using partner data to extend more credit and right-size lines, partners want to hear directly how cardholder data and accounts are kept secure, and the risk team's speed is a selling point. Imprint gives credit line increases after as few as two on-time payments rather than waiting 12 to 18 months for data to mature. The risk team also builds response and targeting models to reach new customers near a partner's stores who are not yet in its loyalty base.
   _Why it matters:_ When the strongest part of your offer sits in a function that is usually kept away from customers, such as risk, security or data, bring that leader into the deal. They can make the advantage credible in a way a salesperson repeating it cannot.
   _For:_ Sales Leaders, Revenue Executives, Founders

7. **Sales-led for logos, marketing-led for cardholders** — Imprint wins new brands through sales and grows cardholders inside each program through its own marketing and partner channels, placing the application in context at checkout or onboarding. New logos have come mainly from word of mouth and introductions through existing partners, plus targeted outreach to brands with an existing program Imprint wants to win. Tyler says Imprint signs three to five logos a year and is aiming for five to ten a year within 18 to 24 months.
   _Why it matters:_ With a small number of very large customers, turning existing partners into promoters is the most efficient way to get introductions. Planning for 5 to 10 logos a year calls for a different go-to-market than planning for hundreds.
   _For:_ Sales Leaders, Marketing Leaders, Founders

8. **Owning the stack turns product capability into inbound** — Imprint built its own vertically integrated processing stack instead of relying on processors like TSYS and Fiserv. That made it possible to offer SKU-level rewards at H-E-B. Lalitha says capabilities like this produce inbound interest from brands that saw what Imprint did for a partner and want the same thing for their customers.
   _Why it matters:_ A difficult infrastructure investment can work as a demand-generation channel when it produces something prospects can see in a peer's program.
   _For:_ Founders, Marketing Leaders

9. **No handoffs from signature to scale** — Tyler's team lands a brand, runs its go-to-market and keeps responsibility for growing the program after launch. Lalitha's team works on partner data from the first day. The partnerships typically run seven years or longer, so Imprint wants to avoid the context loss that comes from passing an account between teams. Tyler tells his team that partners should never hear that another team dropped the ball, because every team is Imprint. Anthony contrasts this with go-to-market teams split across six to ten people, where the relationship weakens at each handoff.
   _Why it matters:_ In long-term strategic accounts, every handoff loses context and costs trust. Consider having one team own the whole revenue outcome, with specialist functions working alongside from day one rather than taking over later.
   _For:_ Revenue Executives, Sales Leaders, RevOps Leaders

10. **Build the AI platform before the AI use cases** — Lalitha credits Imprint's CTO and tech team with making AI adoption possible on the risk team. They invested first in a central platform that standardized data access and added scaffolding and guardrails: the right permissions, controlled deployment of changes, and observability into each workflow's data sources, logic, reproducibility and confidence. Specialized team use cases were built on top of it. Anthony connects this to his view that most AI strategy is really a data model problem.
   _Why it matters:_ Teams that start with agents before data access, permissions and observability are in place end up rebuilding. Fund the shared foundation first and let each function build on it.
   _For:_ RevOps Leaders, Revenue Executives

11. **Start AI adoption with the weekly report everyone hates** — The first thing the risk team automated was weekly reporting, which required gathering data from many sources every week. That early success helped people adopt AI in other ways. The team went on to automate governance documentation for new models and policies, and built a set of agents that do work that would otherwise need teams of analysts. Lalitha says a risk analyst's day is entirely different from three or four months ago.
   _Why it matters:_ Pick a first use case that is painful, recurring and easy to check. A visible early success builds the habit that larger AI projects depend on.
   _For:_ RevOps Leaders, Revenue Executives

12. **Growth up, losses down, headcount nearly flat** — Lalitha reports that over roughly the last year and a quarter, revenue grew about 2.5x and the loan book grew 150%. Newer cohorts have materially lower loss rates than cohorts from a year ago. The risk team grew by only four or five people, and roadmap work planned for next year moved into this year.
   _Why it matters:_ In a lending business, faster growth with lower losses is the evidence that risk is working as a growth function. Report the two together.
   _For:_ Revenue Executives, Founders

13. **AI-enabled martech lets you add partners without adding headcount** — Tyler's team launched a rebuilt martech stack this year, integrated with Snowflake and Imprint's platform, that uses the same data as the risk models. Early-lifecycle actions are similar for every card (use it, add it to a digital wallet, make a first transaction, earn and redeem rewards), but each has to look like it came from a partner brand that may be 100 years old. That used to be almost entirely manual. Now one click produces a new design implementation and communications, cycle times are fast enough to learn from failed tests, and Imprint has added brands without adding design, analytics or martech operations headcount in proportion.
   _Why it matters:_ When every new customer needs its own branded version of the same lifecycle, AI-assisted production plus shared data turns a cost that grows with each customer into one that does not.
   _For:_ Marketing Leaders, RevOps Leaders

14. **You own every word of a document with your name on it** — Tyler says an answer to a partner can never be "that's what the agent told us". Imprint has to be able to show its work. Lalitha's team found that as Claude adoption rose, documents sent to her for review became three times longer and had far fewer charts, because Claude prefers tables. Charts help sanity-check numbers, so the team wrote guidelines. She also heard "Claude got it wrong" after mistakes and rejected it, pointing out that nobody ever blamed Excel. Anthony cites Clay's policy that you are accountable for anything published under your name.
   _Why it matters:_ AI adoption needs explicit standards on document length, how analysis is shown and who is accountable. Otherwise output grows faster than quality, and the blame shifts to the tool.
   _For:_ Revenue Executives, RevOps Leaders, Sales Leaders

15. **Next: reach all of a partner's customers, not just a slice** — Tyler says an unsecured credit card can only serve some of a partner's customers, so Imprint is building new products and integrations that work at whatever technical level a partner has. Lalitha says that as consumers' interactions with brands change, including through agentic commerce, competing on price and features alone will get harder. Imprint's response is a fuller view of each customer from bureau data, partner data, customer service and in-app interactions to decide the next best action. On the day of recording, Imprint announced a co-brand program with Kroger.
   _Why it matters:_ A partner platform's growth limit is usually the share of the partner's customers its core product can serve. Broadening the product and personalizing with combined data is how it expands.
   _For:_ Founders, Revenue Executives


## Frameworks

### Risk as a Growth Function (06:13)

**Definition:** The risk leader is measured on enabling durable growth, finding ways to say yes safely within a stated risk appetite, rather than on minimizing losses.

Lalitha says she is not incentivized to minimize losses. In practice this means pushing approval-rate expansions when new data supports them, joining sales conversations, using partner data to approve more applicants and size credit lines, and giving early credit line increases to customers who pay on time. Her proof is that revenue and the loan book grew while newer cohorts' loss rates fell.

### Measured Separately, Accountable Together (06:35)

**Definition:** Each function tracks the leading indicators it controls, while both leaders share accountability for one outcome. At Imprint that outcome is company profitability and partner growth.

Risk tracks approval and offer-acceptance rates, and revenue tracks accounts added. Tyler separates what each team measures, where it has the most control, from what both are accountable for. With one North Star, disagreements are about pace and test size, and he says a tiebreaker is not needed.

### Scale and Behavior Together (11:06)

**Definition:** A partner program is judged on whether it changes the partner's key business behaviors and whether it does so at a scale that matters to the partner's business.

Tyler builds the card's value proposition, reporting and targeting around the partner's metrics, such as visits, trips and share of wallet, rather than cardholder counts. His counterexample is driving 10x the outcome across 12 cardholders, which does not matter to the partner. He returns to the idea when explaining why Imprint is building products beyond the unsecured card.

### No Handoffs (23:21)

**Definition:** The team that lands a partner also launches and grows the program, and specialist functions such as risk work alongside from the first day instead of receiving the account later.

Imprint's partnerships typically run seven years or longer. Tyler's team keeps responsibility for growth after launch, and Lalitha's team works on partner data from day one and keeps iterating as the partner changes. The aim is that nobody has to backtrack because they lacked context, and the partner never hears that another team dropped the ball.

### Platform Before Use Cases (28:00)

**Definition:** Invest centrally in standardized data access, permissions, controlled deployment and observability before teams build specialized AI workflows on top.

Lalitha credits Imprint's CTO and tech team with this foundation. Each AI workflow should make clear what data sources it uses, what its logic is, how reproducible it is and how confident the team can be in its output. With that in place, her team automated weekly reporting and governance documentation and built analyst-level agents. Tyler applies the same principle with partners: you have to be able to show your work.

### Your Name, Your Words (37:00)

**Definition:** Whoever puts their name on a document, recommendation or partner communication is accountable for every word, whatever tool helped produce it.

Lalitha rejects "Claude got it wrong" as an excuse, since nobody ever blamed Excel. Tyler covers the standard when onboarding new team members: use the tools to get there faster, but don't ship anything you would not stand behind. Anthony connects it to Clay's published policy on AI-written content.


## Quotes

_Speakers inferred from an undiarized transcript — verify before attributing._

> "Risk at Imprint is really not a traditional control function. I am not incentivized to minimize losses. Really, my role is to drive growth, to find ways to say yes, but say that safely while staying within our risk appetite."
>
> — Lalitha Rao, The LeanScale Podcast Ep. 138 (06:13)

> "We're both really optimizing for growth, but growth that is durable and resilient and would last us through the economic cycle."
>
> — Lalitha Rao, The LeanScale Podcast Ep. 138 (03:22)

> "These are brands with 100-year legacies, more than 100-year legacies. They're not optimizing for a number on a slide tomorrow. They're optimizing for long-term, durable relationships with their customers."
>
> — Tyler Dibble, The LeanScale Podcast Ep. 138 (04:04)

> "There's actually very few disagreements about the direction that we should go. Sometimes it's about the pace. Sometimes it's about the scale of a test."
>
> — Tyler Dibble, The LeanScale Podcast Ep. 138 (07:11)

> "A tiebreaker is not needed when we're working off the same target."
>
> — Tyler Dibble, The LeanScale Podcast Ep. 138 (07:28)

> "He used to say the most important component of a race car to make sure it can go fast is brakes."
>
> — Anthony Enrico, The LeanScale Podcast Ep. 138 (07:45)

> "That additional information to us is a deep signal of high intent and loyalty that gives us orthogonal information that's just not available to other issuers through the credit bureau alone."
>
> — Lalitha Rao, The LeanScale Podcast Ep. 138 (09:10)

> "It's understanding that the important number isn't how many card holders do you have. It's like, what is the behavior that you want to see? What are the business metrics that you want to move?"
>
> — Tyler Dibble, The LeanScale Podcast Ep. 138 (11:06)

> "If we say, we're driving 10X the outcome, but it's only across 12 card holders, well, that doesn't matter for their business."
>
> — Tyler Dibble, The LeanScale Podcast Ep. 138 (12:21)

> "Even two payments in, we'll give you a credit line increase. We won't wait for a year or 18 months for the data to bake."
>
> — Lalitha Rao, The LeanScale Podcast Ep. 138 (14:36)

> "That leads to inbounds, not even outbounds, right? So we get brands reaching out to us based upon, hey, I saw what you're doing over there. I love that. I've never seen that before in a value prop."
>
> — Lalitha Rao, The LeanScale Podcast Ep. 138 (19:58)

> "Now that it's live, how do we grow this program? That's not someone else's job, that's also my team's job."
>
> — Tyler Dibble, The LeanScale Podcast Ep. 138 (23:52)

> "These are long-term partnerships, they're not one-year deals, they're typically seven years or longer, and you can't do that by handing off to someone who is picking up and starting without context."
>
> — Tyler Dibble, The LeanScale Podcast Ep. 138 (25:00)

> "The day in the life of somebody on the risk team today at Imprint is entirely different from what it was even three or four months ago."
>
> — Lalitha Rao, The LeanScale Podcast Ep. 138 (27:43)

> "We built a suite of agents within the team that are doing the work that it would take teams of analysts to do."
>
> — Lalitha Rao, The LeanScale Podcast Ep. 138 (30:12)

> "Mostly your AI strategy is more of a data model problem."
>
> — Anthony Enrico, The LeanScale Podcast Ep. 138 (31:27)

> "An answer to a question can never be, that's what the agent told us, right? We have to be able to show our work."
>
> — Tyler Dibble, The LeanScale Podcast Ep. 138 (32:16)

> "Claude is amazing and Claude is a great coworker that helps you drive better outcomes. But the accountability has to be with the individual. Did anyone ever say Excel got it wrong?"
>
> — Lalitha Rao, The LeanScale Podcast Ep. 138 (37:03)

> "Your name is on the document. You own every word in it. Use the tools to get there faster and help refine the data and your ideas. But you have to own the outcome."
>
> — Tyler Dibble, The LeanScale Podcast Ep. 138 (37:28)

> "It's going to be harder and harder to compete on things like pricing and product features alone."
>
> — Lalitha Rao, The LeanScale Podcast Ep. 138 (40:25)


## Practical advice by role

### Revenue Executives

- Give risk, security or compliance leaders a growth objective with a stated risk appetite, not just a loss-minimization target.
- Keep separate team metrics, but make both leaders accountable for the same outcome, such as company profitability, so disagreements are about pace rather than direction.
- Bring the leader who owns your hardest-to-copy capability, whether risk, data or security, into enterprise sales conversations.
- Report growth and quality together, for example revenue and loan book growth alongside cohort loss rates, so the case for a risk-enabled growth function is visible.

### Founders

- Ask for partner first-party data as part of the deal. It can be your main advantage over competitors who rely on generic data sources.
- Weigh building core infrastructure yourself when it enables features prospects can see in a peer's program. Imprint's SKU-level rewards at H-E-B produced inbound interest.
- Plan the go-to-market around a realistic number of logos. With 3 to 5 large partners a year, existing partners as promoters and referrers will usually beat broad outbound.
- Before launching AI use cases, fund a shared platform with standardized data access, permissions, deployment controls and observability.

### Sales Leaders

- Open partner conversations with the metrics the partner wants to move, such as visits, trips or share of wallet, and design your reporting around them rather than around your product's usage counts.
- Track whether behavior changes and how many people it reaches. A big lift on a tiny population will not hold a partner's attention.
- Don't hand off accounts after signature. The team that lands the logo should stay accountable for growing it, and specialist teams should be involved from day one.
- Never give a partner an answer you can't explain. "The agent told us" is not a defensible position.

### RevOps Leaders

- Make the first AI automation a painful, recurring, easy-to-check job such as multi-source weekly reporting, and use that success to build the habit.
- Document the data sources, logic and reproducibility of each AI workflow so outputs can be traced.
- Feed the same modeled data into risk or finance models and into marketing and lifecycle systems, so one data investment benefits more than one function.
- Write AI output standards covering length, charts versus tables and named accountability. Without them, document length grows and quality checks get weaker.

### Marketing Leaders

- Template the early lifecycle (activation, digital wallet, first transaction, first reward) and use AI to generate partner-branded versions, so adding a partner does not require adding headcount.
- Surface the offer in the partner's own context, such as checkout or onboarding, where it is relevant and personalized.
- Use response and targeting models to reach new customers near a partner's locations who are not yet in its loyalty base, so the program brings the partner incremental customers.


## AI takeaways

**Thesis:** Imprint's AI gains on both the risk and revenue sides come from a central platform built first: standardized data access, permissions, controlled deployment and observability. Teams then automate the recurring work and add agents. Both leaders also hold that a person, not the tool, is accountable for every output.

- **** — 
- **** — 
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- **** — 

**Agent & automation ideas**

- A weekly risk-reporting agent that gathers data from every source and produces the standard report, with lineage for each figure.
- A governance-documentation agent that drafts the required documentation whenever a new credit model or policy is deployed.
- A next-best-action agent that combines bureau, partner, customer-service and in-app context to decide a credit line, offer or message for each customer.
- An in-checkout credit agent that offers an on-the-spot line increase when a purchase, such as a flight, would push a cardholder over the limit, covering related purchases as well.
- A partner-brand lifecycle agent that turns the standard activation sequence into a partner-specific design and communications set in one step.
- A document-review agent that flags proposals that are too long, missing charts or lacking a named owner before they reach a decision-maker.


## Operations takeaways

### Revenue operations

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### Pipeline & marketing ops

- **.** 
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- **.** 


## Metrics mentioned

| Value | Metric | Context |
| --- | --- | --- |
| About 2.5x | Revenue growth | Over roughly the last year and a quarter, per Lalitha. |
| 150% | Loan book growth | Same period. Lalitha adds that newer cohorts have materially lower loss rates than cohorts from a year earlier. |
| About 4 to 5 people | Risk team headcount added | The increase in the risk team over the same period of growth, which Lalitha credits largely to AI adoption. |
| 3 to 4x | Trips booked by Booking.com cardholders | An Imprint cardholder with Booking.com books three to four times as many trips as a member without the card. |
| As few as 2 payments | Time to first credit line increase | Imprint gives increases after two on-time payments rather than waiting 12 to 18 months for data to mature. |
| 3 to 5 today; target 5 to 10 | New logos per year | Tyler's target is five to ten a year within the next 18 to 24 months. |
| 7+ years | Typical partnership length | Why Imprint avoids handoffs: the relationships are long-term, not one-year deals. |
| More than a dozen | Brands live | Brands live on Imprint at recording, before the Kroger launch. |
| 3x | Document length after Claude adoption | An analysis by a leader on Lalitha's team found that proposals and strategy documents sent for her review tripled in length and had far fewer charts. |
| $1.2 billion | Valuation | Cited by Anthony when asking about Imprint's go-to-market strategy. |


## Entities mentioned

- **Imprint** (company) — Employer of both guests. A payments and loyalty platform running co-brand credit card programs for large consumer brands, with more than a dozen brands live at recording. Imprint built its own vertically integrated processing stack, uses partner data in underwriting, and reports about 2.5x revenue growth and 150% loan book growth over about fifteen months while loss rates on newer cohorts fell. Anthony cites a $1.2 billion valuation. · https://www.leanscale.team/knowledge/company/imprint/
- **Rakuten** (company) — Imprint co-brand partner. Lalitha's main example of partner data in underwriting: membership tenure, transaction history and the trend in spend and engagement give signal the credit bureau does not. · https://www.leanscale.team/knowledge/company/rakuten/
- **Booking.com** (company) — Imprint co-brand partner. Lalitha says an Imprint cardholder with Booking.com books three to four times as many trips as a member without the card. She also describes a planned experience where a cardholder about to exceed their limit on a flight gets an on-the-spot increase covering the hotel and car rental too. · https://www.leanscale.team/knowledge/company/booking-com/
- **H-E-B** (company) — Imprint co-brand partner. Imprint's own processing stack lets it offer SKU-level rewards at H-E-B, which Lalitha says produces inbound interest from other brands. Also an example of targeting nearby shoppers who are not yet H-E-B customers. · https://www.leanscale.team/knowledge/company/h-e-b/
- **Crate & Barrel** (company) — Imprint co-brand partner. Cited as an example of targeting people near a store who do not yet have the card, and among the enterprise logos Imprint has won through sales. · https://www.leanscale.team/knowledge/company/crate-and-barrel/
- **Kroger** (company) — New Imprint co-brand partner. The partnership was announced and the program went live on the day of recording. Tyler describes Kroger as the largest standalone grocery store in the United States, with a national presence across more than a dozen brands. · https://www.leanscale.team/knowledge/company/kroger/
- **TSYS** (company) — Card processor named by Lalitha as one of the external processors Imprint does not depend on, because it built its own vertically integrated stack. · https://www.leanscale.team/knowledge/company/tsys/
- **Fiserv** (company) — Card processor named alongside TSYS as one of the external processors Imprint does not depend on. · https://www.leanscale.team/knowledge/company/fiserv/
- **Snowflake** (company) — Integrated with Imprint's rebuilt martech stack. Tyler says the Snowflake integration lets the same modeled data used in risk models drive personalization and faster lifecycle-marketing cycle times. · https://www.leanscale.team/knowledge/company/snowflake/
- **Emailage** (company) — Where Anthony worked with Tom Miller, whose race-car-brakes analogy he uses to describe risk's role in growth. · https://www.leanscale.team/knowledge/company/emailage/
- **Lalitha Rao** (person, guest) — Chief Risk Officer at Imprint (ex-Capital One, Stripe, Square), who runs risk as a growth function. · https://www.leanscale.team/knowledge/guest/lalitha-rao/
- **Tyler Dibble** (person, guest) — Chief Revenue Officer at Imprint (ex-SoFi, Chime, OnePay), who leads enterprise co-brand partnerships with a no-handoffs model. · https://www.leanscale.team/knowledge/guest/tyler-dibble/
- **Anthony Enrico** (person, host) — Co-founder of LeanScale and host of The LeanScale Podcast. · https://www.leanscale.team/knowledge/guest/anthony-enrico/
- **Tom Miller** (person, mentioned) — Author of 'Call Your Shots' and a veteran go-to-market operator (multiple IPOs, buy- and sell-side M&A); Anthony Enrico's former CRO at Emailage. · https://www.leanscale.team/knowledge/guest/tom-miller/
- **Claude** (tool, AI Assistant) — Used widely by Imprint's risk team. Lalitha's team found that as Claude adoption rose, documents sent for review became three times longer and had fewer charts because Claude prefers tables, which led to guidelines. She calls Claude a great coworker but rejects "Claude got it wrong" as an excuse.
- **Clay** (tool, GTM Data / Enrichment) — Anthony cites Clay's company policy on AI-written content: you are accountable for anything published under your name, and more is not better.
- **Microsoft Excel** (tool, Productivity / Spreadsheet) — Lalitha's comparison for AI accountability: nobody ever said Excel got it wrong.


## FAQ

**Q: What does it mean that risk is a growth function at Imprint?**

A: At Imprint, the payments and loyalty platform behind co-brand cards for brands like Booking.com, H-E-B and Kroger, Chief Risk Officer Lalitha Rao is not incentivized to minimize losses. Her job is to drive growth by finding ways to say yes safely within the company's risk appetite. In practice that means expanding approval rates when new data supports it, using partner data to approve applicants the credit bureau would score poorly, giving credit line increases after as few as two on-time payments, and joining enterprise sales conversations. Over about fifteen months, Imprint's revenue grew about 2.5x and its loan book 150%, while loss rates on newer cohorts fell.

**Q: How do a Chief Risk Officer and a Chief Revenue Officer stay aligned?**

A: At Imprint, each leader tracks the leading indicators their team controls. Risk watches approval and offer-acceptance rates, and revenue watches accounts added. Both are accountable for the same outcome, company profitability and helping partners grow. Chief Revenue Officer Tyler Dibble says that with a shared target, disagreements are about pace or the size of a test, not direction, so no tiebreaker is needed. In their most recent disagreement, the risk officer was pushing to expand approvals and the revenue officer asked whether the fraud environment made it the right time.

**Q: How can partner data improve credit underwriting?**

A: A co-brand partner can share data the credit bureau doesn't have. Imprint's Chief Risk Officer Lalitha Rao gives the example of Rakuten: how long a customer has been a member, how they have transacted over time and how their spend and engagement have trended. That is a strong signal of intent and loyalty, independent of bureau data. Imprint uses it to approve applicants whose credit history has a blemish, size credit lines to how the customer actually spends and redeems rewards, and increase engagement for the partner brand.

**Q: Why should a Chief Risk Officer join sales conversations?**

A: When a company's advantage depends on risk capability, the risk leader can explain it more credibly than a salesperson. Imprint's Chief Risk Officer joins enterprise partner conversations because partners want to hear how their customers' data and accounts are kept secure, how partner data lets Imprint extend more credit, and how quickly the risk team acts, for example giving credit line increases after two on-time payments rather than waiting 12 to 18 months. She also explains the response and targeting models that bring the partner new customers who are not in its loyalty base.

**Q: What is a no-handoffs go-to-market model?**

A: In a no-handoffs model, the team that wins a customer also launches and grows the account, and specialist functions work alongside from the first day instead of taking over later. At Imprint, the revenue team that lands a brand keeps responsibility for growing the card program, and the risk team works on partner data from day one. Because the partnerships typically run seven years or longer, Imprint wants to avoid the context lost when an account passes between teams. Chief Revenue Officer Tyler Dibble says a partner should never hear that another team dropped the ball.

**Q: How did Imprint's risk team adopt AI?**

A: Imprint's CTO and tech team first built a central platform that standardized data access and added guardrails: permissions, controlled deployment of changes, and observability into each AI workflow's data sources, logic and reproducibility. The risk team's first automation was its multi-source weekly report. It then automated governance documentation for new models and policies and built agents that do work that used to need teams of analysts. Chief Risk Officer Lalitha Rao says the risk team grew by only four or five people while revenue grew about 2.5x.

**Q: Who is accountable when AI produces a mistake?**

A: The person whose name is on the work. Imprint's Chief Risk Officer Lalitha Rao rejects "Claude got it wrong" as an excuse, pointing out that nobody ever blamed Excel. Chief Revenue Officer Tyler Dibble tells new team members they own every word of a document with their name on it and should not ship anything they wouldn't stand behind. With partners, he says, "that's what the agent told us" is never an answer, and you have to be able to show your work. Imprint also added guidelines after Claude adoption tripled document length and reduced the number of charts.


## Timeline

- **00:00** — Cold open + intro: two CROs, one company
- **01:16** — The last disagreement: risk pushed to expand, revenue asked to wait
- **05:09** — One profitability target: why no tiebreaker is needed
- **07:58** — Partner data as underwriting signal (Rakuten, Booking.com)
- **10:32** — GTM that starts with the partner's business metrics
- **12:44** — Why the Chief Risk Officer is in the sales room
- **16:11** — Sales-led for logos, marketing-led for cardholders
- **19:10** — Owning the stack: SKU-level rewards at H-E-B
- **23:21** — No handoffs: one team from signature to scale
- **27:08** — AI on the risk team: build the platform first
- **31:18** — AI in GTM: a rebuilt martech stack and faster cycle times
- **35:08** — "Claude got it wrong" is not an answer
- **38:38** — What's next for Imprint, and the Kroger launch


## Related episodes

- **Ep. 122: Your AI Strategy Is a Data Model Problem** (Jake Toepel (LeanScale)) — Anthony quotes this episode's thesis to Lalitha, and her account of building the data platform before the use cases is a working example of it.
- **Ep. 111: Your AI Agents Have God Mode (And Nobody Vetted Them)** (Mark van Oppen (SecureAuth)) — A CRO arguing for turning the CISO into the department of yes, which parallels Imprint's risk leader being paid to find ways to say yes. It also covers AI governance and permissions.
- **Ep. 81: Sell to the Blocker, Not the Champion** (Leigh Gross (Synctera)) — Another fintech CRO on large-committee deals and bringing compliance and risk into the sale instead of routing around them. · https://www.leanscale.team/knowledge/podcast/leigh-gross-compliance-killed-my-deal/
- **Ep. 8: How to Become a Shot Caller** (Tom Miller (Emailage)) — Tom Miller is the source of the race-car-brakes line Anthony uses to describe risk's role in growth. · https://www.leanscale.team/knowledge/podcast/tom-miller-shot-caller/
- **Ep. 124: How a $20K Pilot Became a $30M Deal** (Tim Yandel (Imubit)) — Long-cycle enterprise selling and partner trust, close to Imprint's seven-year partnerships and its focus on the partner's business outcomes.
- **Ep. 69: Inside the Mind of a Modern CRO** (Brett Kelly (Inovonics)) — Another view of the modern CRO role and AI as a way to produce more rather than cut staff, as in Imprint growing brands without matching headcount. · https://www.leanscale.team/knowledge/podcast/brett-kelly-modern-cro/
- **Ep. 119: The Agent Was Never the Hard Part** (Kushal Sharma (Circle)) — The same lesson Lalitha describes: the agents are the easy part, and the data access and guardrails underneath decide whether they work.


## Full transcript

_Machine-transcribed and not diarized; speaker attribution is inferred._  
_Transcript only, as a separate file: https://www.leanscale.team/knowledge/podcast/lalitha-rao-tyler-dibble-imprint-risk-is-a-growth-function/transcript.md_

### 00:00 — Cold open + intro: two CROs, one company

**[0:00]** Today is a first for this show to guest, both of whom are CRO and they work at the same company.

**[0:07]** Give me to the last decision where the two of you genuinely did not agree.

**[0:12]** What was the call and how did it actually get settled?

**[0:15]** Tyler, our chief revenue officer, was actually the first one to say hold on is, you know,

**[0:22]** this is the right environment for us to be actually making that change.

**[0:26]** It feels like that spray and pray email blast motions haven't been as effective.

**[0:34]** And I think that leads to inbounds, not even outbounds based upon,

**[0:37]** hey, I saw what you're doing over there. I love that. I've never seen that before.

**[0:40]** Mostly your AI strategy is more of a data model problem.

**[0:44]** An answer to a question can never be that's what the agent told us, right?

**[0:48]** We have to be able to show our work, our new partnership with Kroger and went live with that

**[0:53]** program. Kroger is the largest standalone grocery store in the United States.

**[0:57]** Seeing risk and revenue together on the same team.

**[1:01]** I think it's a model for how companies should be approaching this.

**[1:06]** I would love to hear what is next for imprint.

### 01:16 — The last disagreement: risk pushed to expand, revenue asked to wait

**[1:16]** So you two have the same three letter title and you sit on the same P&L.

**[1:21]** Take me to the last decision where the two of you genuinely did not agree.

**[1:27]** What was the call and how did it actually get settled?

**[1:31]** Yeah, this is a fun one and I think it's going to be a surprising one too.

**[1:39]** Actually, the last thing that I can recall is just from a couple of weeks ago.

**[1:45]** And I was advocating for a policy expansion. We've invested a lot in alternative data sources

**[1:54]** to be able to enhance our fraud detection and mitigation capabilities.

**[1:59]** And the idea was to be able to reduce the customers that we are sending through

**[2:06]** what we call an IDB intervention.

**[2:08]** Now, even though our IDB process is quite frictionless and easy to do,

**[2:14]** we take adding any friction into our flow very, very seriously.

**[2:20]** And there's a very high bar.

**[2:21]** So where we can reduce that, we're excited to do that.

**[2:25]** And it certainly helps with conversion.

**[2:27]** So I was advocating for this change to our policy

**[2:31]** to actually expand approval rates and reduce the surface area of IDVs.

**[2:37]** And Tyler, our chief revenue officer, was actually the first one to say,

**[2:45]** hold on, is this the right environment for us to be actually making that change,

**[2:51]** given the fact that AI tooling available to fraudsters has also rapidly increased innovation

**[3:00]** in terms of the type of fraud that we are seeing.

**[3:03]** So it was very interesting.

**[3:05]** Of course, I walked him through the rationale here

**[3:10]** and how we were enabling it safely in a very data-driven manner

**[3:15]** and felt confident with that decision.

**[3:17]** But just that example should give you a sense of the dynamic here.

**[3:22]** We're both really optimizing for growth,

**[3:27]** but growth that is durable and resilient and would last us through the economic cycle.

**[3:35]** Tyler, what kept you both aligned where you have the chief risk officer saying,

**[3:41]** hey, let's accelerate.

**[3:42]** And you're actually in the seat trying to hold back.

**[3:45]** What mechanism is keeping you both together?

**[3:48]** I think it's less about holding back.

**[3:49]** And it's more about ensuring that the growth that we're driving is durable and resilient.

**[3:55]** That's what Lillieth and I are both focused on.

**[3:58]** It's what the whole leadership team here is focused on.

**[4:00]** But the other side of that in my job is working with our partners directly.

**[4:04]** And these are brands with 100-year legacies, more than 100-year legacies.

**[4:08]** They're not optimizing for a number on a slide tomorrow.

**[4:12]** They're optimizing for long-term, durable relationships with their customers.

**[4:17]** And that's what we need to enable.

**[4:19]** And so making sure that we are supporting them,

**[4:24]** we're helping them build those relationships without causing blowback, right?

**[4:28]** So us overextending a customer and they getting into trouble on their credit card,

**[4:33]** not only is it terrible for the customer,

**[4:34]** it's the brands don't want to see that either, right?

**[4:36]** We want to make sure that we are setting these customers up for success

**[4:41]** because it's not just their personal success,

**[4:43]** which is incredibly important in terms of financial empowerment,

**[4:46]** but also success of the brand for which they have a deep relationship

**[4:50]** and we're trying to support that relationship.

**[4:53]** And so there is absolutely a trade-off between

**[4:55]** short-term quick dopamine hits of growth

**[4:59]** and then building for the long-term, durable, resilient kind of platform

**[5:04]** and user base that we need to see with our partners and our members.

### 05:09 — One profitability target: why no tiebreaker is needed

**[5:09]** So when you both sit down in executive meeting,

**[5:11]** you're going to a board meeting together,

**[5:13]** do you have a shared target, shared goal that makes this decision-making easier?

**[5:19]** Because I've seen it where one executive has a goal to accomplish something,

**[5:23]** so they're going to do everything they can to hit their number.

**[5:25]** Another one has something else,

**[5:27]** but they're competing against each other.

**[5:29]** What type of goal system do you all have set up to keep you aligned?

**[5:34]** I can get us started here, Tyler, jump in.

**[5:36]** We definitely have our individual metrics that we are looking at.

**[5:40]** You know, I'm looking at things like approval rates,

**[5:43]** I'm looking at offer acceptance rates,

**[5:47]** and Tyler is, of course, focused on how many accounts are we adding.

**[5:51]** But ultimately, we are both also accountable

**[5:55]** for making sure that we are balancing that risk and reward trade-off

**[6:01]** in an optimal manner and maximizing for profitability as well.

**[6:06]** So I think that is, you know, an area where, you know,

**[6:09]** it's very clear to us that that's ultimately the objective.

**[6:13]** Risk at imprint is really not a traditional control function.

**[6:19]** I am not incentivized to minimize losses.

**[6:24]** Really, my role is to drive growth, to find ways to say yes,

**[6:29]** but say that safely while staying within our risk appetite.

**[6:35]** Yeah, I think I'd say there's a big difference

**[6:38]** between what do we measure within our given teams

**[6:40]** and where we have the most control and what are we accountable for, right?

**[6:44]** And so we're measuring the things that are leading indicators

**[6:46]** of that durable growth that we talked about.

**[6:48]** But ultimately, we're both accountable for company profitability

**[6:52]** and helping our partners grow these brands

**[6:55]** and the relationships with their customers.

**[6:56]** That's what we're accountable for.

**[6:59]** And it actually makes it really easy at the end of the day

**[7:02]** when that's the North Star.

**[7:04]** And that's what not just the two of us,

**[7:06]** but the whole company culture is focused on, is supporting that outcome.

**[7:11]** There's actually very few disagreements about the direction that we should go.

**[7:15]** Sometimes it's about the pace.

**[7:16]** Sometimes it's about the scale of a test, things like that.

**[7:18]** How quickly can we get the learnings

**[7:20]** because we're all really excited about something.

**[7:23]** But in terms of the direction and the decision-making, it's really helpful.

**[7:28]** A tiebreaker is not needed when we're working off the same target.

**[7:35]** I worked with a CRO, his name's Tom Miller,

**[7:38]** and he ran companies like Zscaler.

**[7:40]** Him and I worked together at E-mailage,

**[7:41]** and he's worked at a number of excellent cybersecurity companies.

**[7:45]** And he used to say the most important component of a race car

**[7:49]** to make sure it can go fast is brakes.

**[7:52]** And if you don't have those brakes,

**[7:55]** then you're putting the entire race at risk.

### 07:58 — Partner data as underwriting signal (Rakuten, Booking.com)

**[7:58]** Lalitha, how do you see risk as part of the overall go-to-market strategy

**[8:04]** and growth strategy that you're working on with Tyler?

**[8:06]** Definitely.

**[8:06]** I think we work so closely throughout the life cycle of a deal, if you will.

**[8:13]** And there's really no clean handoffs, as such, across our teams.

**[8:19]** And it's very deliberate.

**[8:21]** So right from the beginning of a deal, we are so in sync about if we can get data

**[8:28]** from our partners that enables us to understand their customer base better,

**[8:36]** we're able to just underwrite in a much more effective manner.

**[8:39]** So to make this real with a partner like Rakuten,

**[8:43]** we're able to get information around how long has a customer been a member with Rakuten?

**[8:50]** How have they been transacting over time?

**[8:53]** What has been that trajectory in terms of spend and engagement?

**[8:57]** And that gives us such great signal from a risk perspective.

**[9:02]** So even if somebody looks like their credit score might not be perfect

**[9:07]** or they might have a blemish on their credit history,

**[9:10]** that additional information to us is a deep signal of high intent and loyalty

**[9:17]** that gives us orthogonal information that's just not available to other issuers

**[9:23]** through the credit bureau alone.

**[9:25]** So we leverage that to be able to expand approval rates, to be able to say yes more,

**[9:31]** expand access to credit, right size the credit lines and the exposure we are taking

**[9:38]** to really be tailored to the usage patterns of that customer,

**[9:44]** their unique spend and reward redemption history as well.

**[9:48]** And that just allows us again to deepen the engagement

**[9:52]** and drive more engagement for our brand partners and more monetization as well.

**[9:58]** So just to make this real, with booking.com a card holder,

**[10:03]** an imprint card holder with booking.com books three to four times as many trips

**[10:09]** as another member that doesn't have a card.

**[10:13]** So we do see this actually drive that incremental spend and engagement in a very tangible way.

**[10:21]** I think unlocking that growth but keeping it safe,

**[10:25]** having your proprietary data that can enable that I think is a huge strategic advantage.

### 10:32 — GTM that starts with the partner's business metrics

**[10:32]** You all are running up on a $1.2 billion valuation recently.

**[10:37]** Tyler, what has been the go-to-market strategy to get imprint to where it is today?

**[10:45]** And what go-to-market motions are working really well?

**[10:50]** Yeah, I think first off, it's finding brands that really want to build those

**[10:54]** relationships with their customers.

**[10:56]** From my team, when we're working with partners day in and day out,

**[10:59]** whether they've already become a partner and launched a program

**[11:02]** or were in early days of the conversation,

**[11:06]** it's understanding that the important number isn't how many card holders do you have.

**[11:11]** It's like, what is the behavior that you want to see?

**[11:12]** What are the business metrics that you want to move?

**[11:15]** And how can we build a card program around those strategic goals and priorities?

**[11:20]** If I never talked to a partner leadership team about the number of card holders,

**[11:26]** the number of transactions, great, because it means that we can talk about

**[11:29]** how we're driving the business and things that actually matter for their business,

**[11:33]** whether it be visits or trips or booking different types of trips

**[11:39]** or total share of wallet at their store.

**[11:42]** And so that's really what it is about, is understanding what matters most to them

**[11:46]** and figuring out who in the organization can get us that insight

**[11:52]** in a way that isn't this quarters or strategy. And it's always a little bit hard to manage

**[11:57]** as leadership has changed at our partners, but focusing on those goals

**[12:03]** and then building not just our reporting around, it's not just what we talk about,

**[12:08]** but it's designing the value prop of the card program,

**[12:11]** how we engage with those customers, where we go find them, right?

**[12:16]** Because it's a balance, we want to impact those metrics.

**[12:21]** But if we say, we're driving 10X the outcome, but it's only across 12 card holders,

**[12:27]** well, that doesn't matter for their business.

**[12:29]** We need to manage both the scale and the behavior and business outcomes together

**[12:34]** to make sure that we're capturing the share of checkout, the outcomes that they want,

**[12:39]** in a way that is actually meaningful for their business and not just a side quest.

### 12:44 — Why the Chief Risk Officer is in the sales room

**[12:44]** When you're in a strategic deal, I mean, I'm seeing logos like booking.com,

**[12:49]** Rakuten, these are huge enterprise accounts.

**[12:52]** Lalitha, do you ever get involved in the sales process or sales strategy

**[12:57]** in order to close these deals?

**[12:59]** Such a good question. And actually I do, right?

**[13:02]** Because so much of what we, our mode is to be able to really use this data.

**[13:12]** We sit so uniquely at the intersection of both the customer and the merchant,

**[13:17]** which gives us this ability to use this additional information from our partners

**[13:23]** to really drive much more access to credit,

**[13:26]** to really right size those credit lines, to drive more spend and engagement.

**[13:31]** So I definitely do join in on those conversations.

**[13:37]** Our partners also want to make sure that the experience that we are offering

**[13:42]** to their cardholders is very, very secure, that we have the state of the art security

**[13:50]** infrastructure in place as well, so that we can keep their cardholder information

**[13:56]** very secure and safe and make sure that the accounts is also very secure.

**[14:02]** So they definitely want to hear from me.

**[14:04]** I think the other thing that we are also uniquely positioned to do is we are a small risk team,

**[14:15]** but we are very nimble in our approach as well.

**[14:18]** So what we do is we're able to iterate very quickly.

**[14:21]** So if we see a cardholder is actually paying us on time,

**[14:26]** showing positive behaviors like linking their bank accounts so we can auto debit their payments,

**[14:32]** we'll actually give them a credit line increase fairly quickly.

**[14:36]** Even two payments in, we'll give you a credit line increase.

**[14:41]** We won't wait for a year or 18 months for the data to bake.

**[14:45]** So we do talk to them about all these capabilities we have

**[14:49]** that really enable us to, again, drive more of that spend and engagement.

**[14:55]** The other thing that I love that's very much a part of our playbook is

**[15:00]** we also want to drive incrementality for our partners.

**[15:04]** So we want to bring in new customers that actually are not currently in their loyalty database already.

**[15:15]** And we are actually able to do this quite successfully as well.

**[15:20]** We're really investing in creating response modeling and targeting modeling

**[15:27]** that allows us to understand who should we be targeting that may be in the vicinity

**[15:32]** of a Crate and Barrel store or an HEB store that doesn't have a card

**[15:38]** that's potentially not a shopper today at HEB,

**[15:41]** but they see this really compelling credit card offer and that brings them into the store.

**[15:48]** So I think that's very much a part of our strategy as well.

**[15:51]** And we're really investing in terms of being able to drive that incrementality

**[15:57]** and new audiences that use the credit card as a gateway in terms of interacting with the brand.

**[16:07]** This seems like a really big competitive advantage.

### 16:11 — Sales-led for logos, marketing-led for cardholders

**[16:11]** Maybe I'll ask a silly question.

**[16:12]** I'm assuming most of the growth is a sales-led motion to get into companies

**[16:19]** like Booking and Rakuten and Crate and Barrel.

**[16:22]** Are you landing mainly through partner channels or sales-led initiatives?

**[16:27]** Or is there a product-led motion going here as well?

**[16:31]** In terms of landing new brands and partnerships, that'd be a sales-led.

**[16:34]** But in terms of within that partnership driving customer growth and member growth

**[16:40]** for our card program, that's a marketing we're driving through marketing,

**[16:44]** both our own marketing and through our partner channels.

**[16:47]** So working with partners on their experiences and their ecosystem

**[16:51]** to make sure that we're surfacing the card, the application,

**[16:55]** whether it's at checkout or onboarding, it depends on their experience.

**[16:59]** But doing it in the right moments where it's contextual and personalized and relevant

**[17:03]** for that customer so that we can get them into the application and serve them,

**[17:09]** they can get more value from that brand.

**[17:11]** So it depends on which partner you're talking about.

**[17:14]** Makes a ton of sense.

**[17:16]** I'm curious, I feel like sitting here, September 30th,

**[17:21]** 2026, so much has changed in GoToMarket, especially in the last couple of years.

**[17:27]** What are some motions that seem to be working to get in front of the brands?

**[17:32]** It feels like that spray and pray, email blast motions haven't been as effective.

**[17:39]** What are you doing today in 2026 to get in front of new logos?

**[17:44]** In terms of getting in front of new logos, I think we have, to date,

**[17:47]** really focused on word of mouth, right?

**[17:51]** So it's not a huge industry.

**[17:54]** We also don't have thousands of partners either, right?

**[17:57]** So there's an opportunity for us to focus on the partners we do have

**[18:02]** and turn them into promoters.

**[18:04]** We do some outreach to brands or enterprise logos that we think would be ripe

**[18:10]** or they have an existing program and we want to win that deal.

**[18:15]** Oftentimes, there's a conversation with an existing partner or someone we've worked

**[18:20]** with already as a way to help us get a foot in the door.

**[18:23]** That has been really effective for us in the past as we've gotten to this scale.

**[18:28]** But we're still exploring new ways to continue to add more and more logos every year.

**[18:34]** We'll never be in a place, I think, for a traditional unsecured credit card program

**[18:40]** where we're adding 500 logos a year.

**[18:43]** I think that's not the business that we're in.

**[18:46]** But we've been doing three to five per year and we're going to target moving that.

**[18:52]** Can we get to five or 10 logos a year in the next 18 to 24 months?

**[18:59]** That's the target.

**[19:00]** And so reaching directly out to those brands, we've built a reputation.

**[19:03]** We've built the foundation and trying to start those relationships early and proactively.

### 19:10 — Owning the stack: SKU-level rewards at H-E-B

**[19:10]** I'll just add to that.

**[19:11]** I think a couple of other things that, like Tyler said, it's that word of mouth that is

**[19:16]** so strong for us is also driven by the fact that we've actually invested

**[19:20]** in building our own vertically integrated tech stack.

**[19:24]** So we don't rely on external processors like T-SYS and Piserv.

**[19:31]** And that's actually a huge advantage for us because it just allows us

**[19:35]** to meet the partners where they're at in a very unique way.

**[19:40]** So an example of this is at HEB, we're able to do Q-level rewards.

**[19:46]** And we were able to really bring in that level of differentiation and granularity

**[19:52]** to our product offering, which I think is very unique and bodes very well for us.

**[19:58]** And I think that leads to inbounds, not even outbounds, right?

**[20:01]** So we get brands reaching out to us based upon, hey, I saw what you're doing over there.

**[20:05]** I love that.

**[20:05]** I've never seen that before in a value prop.

**[20:08]** And how can I get that for my customers?

**[20:11]** That's been, it's very much a privilege and an amazing place for us to be.

**[20:16]** And it's exciting for us.

**[20:18]** And so that's why, that's how we've kind of gotten to where we are today

**[20:22]** is by starting with some of those more dynamic and flexible integrations

**[20:26]** that are only possible because we have our own tech stack.

**[20:30]** I think the winning formula of build a great product,

**[20:34]** take care of your customers always seems to help companies grow

**[20:37]** and get them to where they want to be.

**[20:39]** I'm curious, this proprietary tech stack,

**[20:43]** as well as the proprietary data you have to do your own risk assessments,

**[20:46]** feels like a really strong strategic advantage.

**[20:49]** Lalitha, are you involved quite a bit on enablement of the teams

**[20:52]** that are driving expansion of your existing customers

**[20:55]** and getting in front of the existing customers

**[20:57]** for how they can continue to unlock growth?

**[21:00]** Definitely.

**[21:00]** I think this is something, again, that we're very much a lock step here.

**[21:05]** Like the thing we want to do is, in terms of where we are very uniquely positioned

**[21:14]** to serve our partners, we are a complete data insights

**[21:21]** and intelligence platform, but also a holistic payments platform.

**[21:26]** And we're investing in building out newer payment methods

**[21:30]** for our partners, launching newer products

**[21:32]** so we can really tailor our product offering

**[21:36]** to be very customized to the individual customer.

**[21:40]** I think if you think about where we are headed in this era

**[21:43]** of agentic commerce as well, it's increasingly becoming so important

**[21:50]** to be able to deepen engagement, but do that through the lens of personalization.

**[21:57]** And that's really where we're investing.

**[21:59]** So we are looking to invest in building a holistic understanding

**[22:07]** of each and every customer from the lens of, of course,

**[22:10]** the traditional credit bureau data, but also taking into account

**[22:14]** the partner data we've spoken about, but also very importantly,

**[22:18]** taking into account all the interactions the customer has had

**[22:22]** with our customer service team, all the interactions

**[22:27]** the customer has had in app with us and taking all that context

**[22:31]** at any given time to really determine what is that next best action

**[22:37]** for the customer that's going to deepen engagement,

**[22:41]** bring in more lifetime value and really expand monetization.

**[22:45]** You know, an example that I love to share is that we have a customer

**[22:50]** that's, you know, in the checkout flow, booking an airline ticket

**[22:54]** at booking.com, and this is going to tip them above their credit limit.

**[22:59]** How do we build an experience where we give them a credit limit on the spot

**[23:04]** that allows them to not only book their airline ticket,

**[23:07]** but also their hotel and car rental with us.

**[23:12]** So, you know, that those are the kind of experiences

**[23:16]** that we are looking to develop that are just so deeply personalized.

### 23:21 — No handoffs: one team from signature to scale

**[23:21]** One of the things I'd love to, if I can, like that I think has been coming through

**[23:24]** that maybe is a little different about Imprint,

**[23:27]** is a lot of other folks out there, a lot of companies out there

**[23:32]** will have, you know, the sales team and the revenue team,

**[23:34]** then hands off to legal or hands off to risk to solve problems.

**[23:39]** We argue, like Lillitha and I in particular, but Imprint in general,

**[23:43]** we don't do handoffs, right?

**[23:46]** We, you know, my team lands a brand, a logo,

**[23:50]** my team drives, go to market for that,

**[23:52]** then I don't hand off, okay, now that it's live,

**[23:56]** how do we grow this program, right?

**[23:58]** That's not someone else's job, that's also my team's job, right?

**[24:01]** And how do we get the right data from the partner

**[24:04]** to drive approval rates and drive this flywheel for personalization?

**[24:08]** Lillitha's team is focused on that from day one of the partnership

**[24:12]** and we continue to iterate on that over time

**[24:14]** because the partner evolves, their customers change.

**[24:17]** We bring on new capabilities, new alternative data sources.

**[24:21]** We're constantly kind of building on those

**[24:23]** and so it's that partner obsession that is true across my team, Lillitha's team,

**[24:28]** but really the whole company that means by having that continuity across,

**[24:32]** we don't have any handoffs, right?

**[24:33]** There's no, oh, I didn't know that, I didn't have that context before,

**[24:36]** so like, you know, that's not what the partner wanted,

**[24:39]** so we'll have to backtrack and fix that or that's not possible.

**[24:43]** We can tell them, we know what we can deliver,

**[24:45]** we know what matters to them and we can very quickly on day one,

**[24:49]** start delivering what we need to on those business outcomes we talked about earlier

**[24:55]** and then continue to build on that foundation

**[24:58]** over the duration of the partnership, right?

**[25:00]** These are long-term partnerships, they're not one-year deals,

**[25:02]** they're typically seven or longer, seven years or longer

**[25:05]** and so we're trying to build significantly

**[25:09]** both in terms of capability and scale and outcomes over that duration

**[25:14]** and you can't do that by handing off to someone

**[25:16]** who like is picking up and starting without context, right?

**[25:20]** Super important to us.

**[25:22]** Yeah, and I think you're ahead of the curve on this,

**[25:25]** but I would say a lot of other CROs are following a similar trend.

**[25:30]** We went from having a hyper-fractionalized go-to-market team

**[25:34]** where you have the BDR, SDR, closing AE, onboarding specialist,

**[25:40]** then you have the CSM, then you have the existing,

**[25:42]** you have six to ten people involved in a deal,

**[25:46]** all with the relationship decaying along the way.

**[25:49]** And nobody really owning the entire outcome,

**[25:52]** and especially if you're in this type of business

**[25:55]** where there are large, long-term strategic partnerships

**[25:58]** with the brand, with the partners that you're working

**[26:00]** to get to the brands through.

**[26:02]** I think that full-stack revenue ownership is very important.

**[26:07]** Totally agree, and I think it's really,

**[26:10]** the way I talk to my team about it is I don't ever want to hear,

**[26:13]** the partnership never hear that,

**[26:14]** "Oh, that team dropped the ball, let me go find them,"

**[26:17]** because that team is imprint, right?

**[26:19]** We're all imprint, they should care that it's imprint,

**[26:22]** and if we drop the ball, we should own it,

**[26:23]** we just shouldn't drop the ball, right?

**[26:26]** And so making sure that we are operating as one team

**[26:30]** and presenting to both the partner,

**[26:32]** but also the member, right?

**[26:34]** As one team, and especially when you're member-facing,

**[26:37]** one team includes the enterprise brand

**[26:39]** that we're working closely with.

**[26:40]** We are representing their brand,

**[26:43]** and we have to make sure that we are not just their brand,

**[26:45]** but their culture and their way of doing customer support,

**[26:49]** their way of communicating.

**[26:51]** All of that has to come through

**[26:52]** in every interaction that we have,

**[26:54]** both with the employees at our partners,

**[26:56]** but also with their customers and our members.

**[27:01]** And again, I think that's the right trend,

**[27:03]** kind of wearing the same banner as a company.

### 27:08 — AI on the risk team: build the platform first

**[27:08]** One area I'd like to get into

**[27:10]** is how imprint is implementing AI,

**[27:16]** either on the product side, the risk management,

**[27:19]** risk mitigation side, but also the revenue side,

**[27:22]** and how you're using in your marketing materials,

**[27:26]** and also how you're using AI

**[27:28]** to help take care of your customers.

**[27:31]** Maybe, Lalitha, we could start with you.

**[27:32]** Yeah, definitely.

**[27:34]** I think this is a topic that's near and dear to my heart.

**[27:38]** It's just been such a journey over the last few quarters,

**[27:43]** and I will say, honestly, the day in the life

**[27:46]** of somebody on the risk team today at Imprint

**[27:48]** is entirely different from what it was

**[27:51]** even three or four months ago.

**[27:54]** One thing I'll call out is,

**[27:55]** and I know Tyler will dig into

**[27:57]** how the marketing and the growth teams are using AI,

**[28:00]** but really, at the crux of it

**[28:02]** is the fact that our CTO and tech teams

**[28:06]** really enabled us to do this

**[28:07]** by investing in a centralized platform, if you will,

**[28:12]** that really standardized data access,

**[28:15]** made sure that we had the right scaffolding

**[28:18]** and guardrails in place that unlocked teams

**[28:21]** to build specialized use cases around it.

**[28:24]** So I think I can't underscore enough

**[28:27]** that all this wouldn't have been possible

**[28:29]** without those centralized investments

**[28:31]** that the tech team made,

**[28:33]** and made it really easy for folks

**[28:35]** to get access to the tools,

**[28:37]** but also made sure that it was safe access,

**[28:40]** that it was the right permissioning in place,

**[28:43]** that we had the right rigor

**[28:45]** around how changes are deployed,

**[28:49]** and the right observability through and through

**[28:52]** in terms of, if you have an AI workflow,

**[28:55]** really understanding what are the data sources behind it,

**[28:58]** what is the logic behind it,

**[29:00]** how reproducible it is,

**[29:02]** and how certain you are in terms of the outcomes from it

**[29:06]** was very, very key.

**[29:09]** But aside from that,

**[29:10]** I think, excited to share that it has been

**[29:13]** such an enabler for us on the risk team side.

**[29:18]** A lot of time was spent on very manual,

**[29:20]** sort of more tedious work,

**[29:22]** but very important work,

**[29:23]** like making sure you're gathering data

**[29:25]** from many different sources,

**[29:27]** creating weekly reporting.

**[29:29]** This was actually the first thing

**[29:30]** that we invested in automating,

**[29:32]** and it was a pain point for the team,

**[29:34]** because the team had to do this every week,

**[29:37]** and it was such a big unlock,

**[29:39]** and just helped folks start to get their rhythm

**[29:42]** around adopting AI in different ways.

**[29:46]** But aside from that,

**[29:48]** there's a lot of other work around things

**[29:50]** like making sure we're investing

**[29:52]** in the right governance documentation

**[29:54]** when we deploy new models

**[29:57]** and policies as well

**[29:59]** that we could actually automate using AI,

**[30:02]** and that freed up time for the team

**[30:05]** to spend their time on work

**[30:07]** that's actually strategic,

**[30:09]** work that's actually going to move

**[30:10]** the needle for our partners,

**[30:12]** and we built a suite of agents

**[30:14]** within the team that are doing the work

**[30:16]** that it would take teams of analysts to do.

**[30:20]** So it's been a big unlock,

**[30:22]** and these numbers are very much showing up

**[30:24]** in our metrics.

**[30:26]** So over the last close to a year and a quarter,

**[30:32]** we've seen so much growth within our book,

**[30:34]** our revenue has gone up by about 2.5x,

**[30:38]** our loan book has grown by 150%,

**[30:43]** and our losses have actually improved.

**[30:45]** Newer cohorts are materially lower loss rates

**[30:50]** than cohorts from a year ago,

**[30:53]** and we've done that by barely increasing

**[30:56]** the team size by about four or five

**[31:00]** additional folks on the team.

**[31:03]** So we've been able to accomplish so much more

**[31:07]** from the existing team

**[31:09]** and accelerated so much of our roadmap

**[31:11]** from next year to this year.

**[31:14]** It's been really, really fun to see that.

### 31:18 — AI in GTM: a rebuilt martech stack and faster cycle times

**[31:18]** I want to go back to the first half

**[31:21]** of what you're mentioning as well,

**[31:23]** because I think that's so important.

**[31:24]** It's been the biggest topic I've been speaking on

**[31:27]** that mostly your AI strategy

**[31:30]** is more of a data model problem.

**[31:32]** So can you organize the data?

**[31:35]** Can you build the semantic layer?

**[31:37]** Can you build the context graph

**[31:38]** where AI agents can actually make sense

**[31:40]** of the data, connect the dots?

**[31:42]** And I think it sounds like you've seen

**[31:45]** a tremendous amount of value from that investment.

**[31:49]** Tyler, I'm curious if you're seeing the same thing

**[31:51]** on the go-to-market tech stack side as well,

**[31:56]** and seeing that investment unlock productivity

**[31:59]** on the GTMT.

**[32:01]** Massively, actually, yeah.

**[32:02]** And I think one thing I'll mention is,

**[32:04]** Lalitha touched on observability,

**[32:07]** and I think that's from my seat.

**[32:09]** Also, when I talk to partners,

**[32:10]** we have some partners that are fully AI-pilled,

**[32:13]** and some of which were the other side of the scale.

**[32:16]** And an answer to a question can never be,

**[32:19]** that's what the agent told us, right?

**[32:22]** We have to be able to show our work,

**[32:24]** and yes, we want to move fast,

**[32:25]** and they love the outcomes,

**[32:26]** but sometimes they want to be able to tick and tie

**[32:30]** if they really need to,

**[32:31]** if it really comes down to it.

**[32:32]** And so that observability is incredibly important as well.

**[32:36]** What's happening, how do we drive growth,

**[32:38]** and how is it impacting us?

**[32:39]** One example I'll give is we just rebuilt this year,

**[32:42]** just launched an entirely new MarTech stack

**[32:46]** that allows us to really massively increase

**[32:50]** the level of personalization

**[32:53]** to drive much faster cycle times,

**[32:56]** due to integrations with Snowflake,

**[32:58]** and into our platform.

**[33:00]** So all the data modeling,

**[33:01]** and all the access to data

**[33:02]** that Lolita is talking about for the risk models,

**[33:04]** we're also feeding into,

**[33:05]** how do we drive certain behaviors

**[33:07]** and outcomes for our partners

**[33:09]** across all of the brands that we have, right?

**[33:12]** So we have more than a dozen brands that are live today.

**[33:17]** At the end of the day though,

**[33:18]** the number of actions is not that different,

**[33:21]** at least in the first couple of weeks

**[33:22]** of having a credit card, right?

**[33:24]** I need to use my card,

**[33:25]** I want to add it to my digital wallet,

**[33:27]** drive my first transaction,

**[33:28]** how do I earn and redeem rewards the first time?

**[33:31]** But I go back to we have to make that feel,

**[33:33]** look and feel just like it is

**[33:35]** as if it's coming from these 100 year old brands,

**[33:39]** where these customers have deep relationships.

**[33:43]** And doing that at scale,

**[33:44]** it's been a massive challenge in our history, right?

**[33:47]** As we add new partners,

**[33:48]** it was almost entirely manual to scale these things.

**[33:51]** Now we can do that in a fully AI enabled platform

**[33:55]** with access to the data,

**[33:57]** one click to drive a whole new design implementation

**[34:01]** in our Martech stack,

**[34:03]** and then actually get the comms out to customers

**[34:06]** and see the behavior change or not.

**[34:08]** Sometimes it doesn't, right?

**[34:10]** We wish it always did,

**[34:11]** we wish we always got it right, but we don't.

**[34:13]** And that's okay because that cycle time is so fast

**[34:17]** in this new environment

**[34:19]** that we can learn and improve these things,

**[34:21]** but also it allows us to scale brands

**[34:25]** and add more brands without scaling headcount

**[34:27]** in a linear way, right?

**[34:28]** So from a design team, from an analytics team,

**[34:32]** from a Martech enablement and ops team,

**[34:35]** we haven't really had to scale that headcount

**[34:40]** as we've added new brands, especially over the past year.

**[34:43]** So that's been a huge improvement and unlock for us

**[34:46]** while still driving the outcomes that we want, right?

**[34:48]** And seeing the outcomes that we need for our partners.

**[34:52]** Well, and I think sometimes people

**[34:53]** don't really realize the magnitude

**[34:56]** of improving the cycle time,

**[34:57]** improving the conversion rate of these things,

**[34:59]** just a few points.

**[35:00]** And if you can leverage AI to do that,

**[35:04]** I mean, the investment beyond pays for itself

**[35:07]** once you've done that.

### 35:08 — "Claude got it wrong" is not an answer

**[35:08]** And I just wanna make a comment

**[35:09]** on something you said earlier,

**[35:10]** 'cause I think it's an interesting time

**[35:13]** where people are putting together AI slop documents

**[35:19]** and putting a lot of AI slop content out into the universe.

**[35:22]** And I've actually seen, I saw Clay,

**[35:26]** the enrichment solution for GTM teams,

**[35:29]** they just put out an announcement

**[35:32]** that they have a company policy on AI written content

**[35:36]** that if you publish something with your name on it,

**[35:39]** then you are accountable for everything

**[35:41]** that's written in there.

**[35:42]** And they even have guidelines on,

**[35:44]** hey, more isn't more.

**[35:46]** So don't just keep creating giant documents

**[35:49]** and thinking that it feels thorough.

**[35:50]** But I do think we're getting into this era

**[35:52]** where people are gonna have to kind of reel that back

**[35:54]** and then really own any content they put their name on.

**[35:58]** That so resonates actually with what we've seen

**[36:02]** in terms of our evolution of using AI as well.

**[36:05]** So actually one of the leaders on my team did this analysis

**[36:08]** where we were seeing,

**[36:10]** clutter adoption was skyrocketing.

**[36:13]** The number of proposals and new strategy recommendations

**[36:17]** that were coming my way for review were increasing as well.

**[36:22]** But what we saw is that the length of the documents tripled.

**[36:26]** The number of charts in the document

**[36:30]** came down dramatically

**[36:31]** because Claude likes to work more with tables.

**[36:34]** So as a result of that, we actually did think about

**[36:38]** how do we put guidelines here in terms of best practices?

**[36:42]** Charts are a great way to also sanity check numbers

**[36:45]** and intuition and build intuition

**[36:48]** about whether the proposal makes sense as well.

**[36:52]** So we actually went through that phase and chapter.

**[36:55]** So that very much resonates with me.

**[36:58]** We also had instances where we would have mistakes

**[37:00]** and then we would hear Claude got it wrong.

**[37:03]** And it's really, Claude is amazing

**[37:07]** and Claude is a great coworker

**[37:09]** that helps you drive better outcomes.

**[37:11]** But the accountability has to be with the individual.

**[37:16]** Did anyone ever say Excel got it wrong?

**[37:19]** Has that ever happened?

**[37:20]** Never was an acceptable answer ever.

**[37:24]** I love how this has been personified.

**[37:28]** Your name is on the document.

**[37:29]** You own every word in it.

**[37:30]** Use the tools to get there faster

**[37:32]** and help refine the data and your ideas.

**[37:34]** But you have to own the outcome

**[37:37]** and you have to own the recommendation word for word.

**[37:40]** And if that's not what you're comfortable with,

**[37:43]** don't ship it.

**[37:45]** Whether to me, a coworker or a partner especially, right?

**[37:49]** And so that to me is incredibly important.

**[37:52]** I talk about that to my team.

**[37:54]** It's part of my, when I onboard new people on my team,

**[37:57]** it's one of the things we talk about directly.

**[37:59]** We have amazing tools.

**[38:01]** We have access.

**[38:02]** We live in the future, let's be honest, right?

**[38:04]** But that doesn't mean that you can ship something

**[38:07]** that you're not proud of

**[38:08]** or you don't feel ownership over, ever.

**[38:11]** And I think it's incredible.

**[38:12]** It wasn't even acceptable to say,

**[38:13]** "Hey, the intern got it wrong."

**[38:15]** I don't care if the intern got it wrong.

**[38:16]** You're the one presenting it to the board.

**[38:18]** You're the one presenting to the executive team.

**[38:20]** You own it.

**[38:21]** Yep, a hundred percent.

**[38:23]** So I think it's incredibly important,

**[38:25]** especially in partner facing roles too, right?

**[38:27]** Because then it's not the tool got it wrong

**[38:29]** and it's imprint got it wrong.

**[38:32]** That's right.

**[38:32]** And I think having that mentality kind of across the board

**[38:35]** always helps drive that accountability.

### 38:38 — What's next for Imprint, and the Kroger launch

**[38:38]** I'm curious, you all have done a tremendous job.

**[38:41]** I love seeing the partnership.

**[38:42]** I love how you're leveraging risk as a lever for growth

**[38:47]** and really approaching the market as one team.

**[38:51]** I would love to hear what is next for imprint

**[38:55]** and what is next for your go-to-market motions

**[38:57]** and how you're going to take care

**[38:58]** of your customers and partners.

**[39:00]** I mean, I think what's next is really building

**[39:02]** out new capabilities and adding new products.

**[39:06]** So I mentioned sort of earlier,

**[39:09]** this concept of you need both the behavioral outcomes

**[39:11]** but the scale so that it matters, right?

**[39:14]** And so in a world where we have unsecured credit cards

**[39:18]** as our core product, which is the world we live in today,

**[39:22]** it's impossible for us to serve all of our partners customers

**[39:25]** and to help them build relationships

**[39:27]** with all of their customers.

**[39:29]** And so we are focused really, really deeply

**[39:32]** on how do we bring products to market?

**[39:34]** How do we drive integrations with our partners,

**[39:38]** no matter where they are

**[39:39]** and what level of capability they have within their ecosystem

**[39:43]** that allows them to serve and deepen relationships

**[39:45]** with all of their customers, not just a slice of them.

**[39:50]** So we have some exciting things coming later this year

**[39:52]** and in next year that will help us do that.

**[39:55]** I wish we could talk a little bit more about them today

**[39:57]** but we're not quite ready to do that.

**[40:00]** And I'll just add to that, definitely,

**[40:05]** with all the AI adoption as well,

**[40:07]** we are shipping at a very rapid clip as well.

**[40:11]** So lots of exciting updates coming here.

**[40:14]** But I will say, again, in this era of potentially

**[40:21]** just everything changing in terms of how consumers interact

**[40:25]** with brands, it's going to be harder and harder

**[40:28]** to compete on things like pricing

**[40:31]** and product features alone.

**[40:34]** So you have to kind of really, like I said,

**[40:37]** go back to those data insights

**[40:39]** that can drive deep personalization.

**[40:42]** And I think we are really uniquely set up

**[40:44]** to be that data payments and customer intelligence platform

**[40:50]** for these really large brands to drive every day's spend

**[40:55]** and drive habituation and ultimately drive better outcomes

**[41:00]** for the customers and also our brands.

**[41:04]** And building off of what Lalitha said,

**[41:05]** one of the things we're really excited about today

**[41:08]** is we announced our new partnership with Kroger

**[41:11]** and went live with that program.

**[41:13]** Kroger is the largest standalone grocery store

**[41:15]** in the United States.

**[41:16]** They have a national presence

**[41:18]** across more than a dozen brands

**[41:22]** and are one of the premier partners

**[41:24]** for driving every day's spend

**[41:26]** in relationships with their customers.

**[41:27]** And so we've got a new program in market

**[41:30]** that we announced today

**[41:31]** and really excited to grow that over the coming years

**[41:35]** and looking forward.

**[41:38]** Huge congratulations.

**[41:39]** That's a massive win.

**[41:41]** And I think really just a testament

**[41:43]** to everything that we're talking about here.

**[41:45]** How you're going to market, how you're partnering as a team,

**[41:47]** how you're differentiating in the market as well.

**[41:50]** So just a huge congratulations to landing that logo.

**[41:53]** Well, I love the conversation we had today.

**[41:57]** This is unique for the Lean Scale podcast

**[42:00]** and I appreciate you both participating in this.

**[42:03]** Seeing risk and revenue together on the same team.

**[42:07]** I think it's a model for how companies

**[42:10]** should be approaching this.

**[42:12]** And everything you talked about

**[42:13]** from how you align with your goals and incentives,

**[42:17]** how you're really operating as one team,

**[42:20]** aligned to the same target.

**[42:21]** It's one imprint brand.

**[42:23]** It's not different parts of the company

**[42:25]** that are pointing fingers at each other.

**[42:27]** And then really differentiating through technology and AI

**[42:30]** and how you're taking care of your customers

**[42:32]** and your partners. Amazing story.

**[42:34]** You guys have had incredible success so far

**[42:36]** and I cannot wait to see what you both do next.

**[42:40]** So Lalitha, Tyler, thank you so much for being on the show.

**[42:43]** And it sounds like we might have to catch up again

**[42:45]** in the next six to 12 months to see how things are going.

**[42:48]** Thanks so much. We're really excited.

**[42:50]** I think we have a lot more to talk about next year too.

**[42:53]** So looking forward to it.

**[42:55]** Thank you so much. Such a fun dialogue.

**[42:57]** Really appreciate you having us.

**[43:02]** [BLANK_AUDIO]


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