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Вміст надано Neil C. Hughes. Весь вміст подкастів, включаючи епізоди, графіку та описи подкастів, завантажується та надається безпосередньо компанією Neil C. Hughes або його партнером по платформі подкастів. Якщо ви вважаєте, що хтось використовує ваш захищений авторським правом твір без вашого дозволу, ви можете виконати процедуру, описану тут https://uk.player.fm/legal.
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3429: How Credit Karma Scales GenAI to Power 60 Billion Predictions a Day

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Вміст надано Neil C. Hughes. Весь вміст подкастів, включаючи епізоди, графіку та описи подкастів, завантажується та надається безпосередньо компанією Neil C. Hughes або його партнером по платформі подкастів. Якщо ви вважаєте, що хтось використовує ваш захищений авторським правом твір без вашого дозволу, ви можете виконати процедуру, описану тут https://uk.player.fm/legal.

What does it take to deliver personalized financial guidance to more than 140 million people every single day? That is the question I put to Wan Agus, Head of Engineering at Intuit Credit Karma, in this episode of Tech Talks Daily.

Most of us open the Credit Karma app to check our credit score, look at a loan option, or browse for a better credit card. What we rarely consider is the technology running behind the curtain. Wan revealed that his teams are powering more than 60 billion daily AI predictions to understand members’ needs, protect their privacy, and guide them toward the right financial choices. He explained why accuracy is everything in fintech. A misplaced recommendation can mean more than a poor customer experience; it can damage someone’s credit score and hold back their progress.

Our conversation also looked at what happened after Intuit acquired Credit Karma. Two very different tech stacks had to be brought together, and identity systems had to be unified so members could move seamlessly between Credit Karma and products like TurboTax. Wan compared the process to playing two complex board games at once, where success depends on strategy and collaboration.

We also explored how Credit Karma is blending traditional AI with generative AI. From early chatbot experiments to today’s Wallet Analyzer and Tax Advisor, Wan shared how his teams decide when to push forward with new tools and when to slow down to ensure safety and trust. He also gave us a glimpse into the future, where agent-to-agent technology could bring open banking-style transparency to the U.S.

So how do you scale personalization without losing trust? And what can every business leader learn from Credit Karma’s balance between speed, culture, and responsibility? I would love to hear your thoughts after listening.

*********

Visit the Sponsor of Tech Talks Network:

Land your first job in tech in 6 months as a Software QA Engineering Bootcamp with Careerist

https://crst.co/OGCLA. Click or tap to follow the link." href="https://emea01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fcrst.co%2FOGCLA&data=05%7C02%7C%7Cd612b8a0aa6c4f08a31908dde5729a6f%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C638919002555348411%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=aI2VIHyOm57M6sowtgiI9S8lOBuYflAX15O4TQ3Safc%3D&reserved=0" rel="noopener noreferrer">https://crst.co/OGCLA

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535 епізодів

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iconПоширити
 
Manage episode 508002416 series 80936
Вміст надано Neil C. Hughes. Весь вміст подкастів, включаючи епізоди, графіку та описи подкастів, завантажується та надається безпосередньо компанією Neil C. Hughes або його партнером по платформі подкастів. Якщо ви вважаєте, що хтось використовує ваш захищений авторським правом твір без вашого дозволу, ви можете виконати процедуру, описану тут https://uk.player.fm/legal.

What does it take to deliver personalized financial guidance to more than 140 million people every single day? That is the question I put to Wan Agus, Head of Engineering at Intuit Credit Karma, in this episode of Tech Talks Daily.

Most of us open the Credit Karma app to check our credit score, look at a loan option, or browse for a better credit card. What we rarely consider is the technology running behind the curtain. Wan revealed that his teams are powering more than 60 billion daily AI predictions to understand members’ needs, protect their privacy, and guide them toward the right financial choices. He explained why accuracy is everything in fintech. A misplaced recommendation can mean more than a poor customer experience; it can damage someone’s credit score and hold back their progress.

Our conversation also looked at what happened after Intuit acquired Credit Karma. Two very different tech stacks had to be brought together, and identity systems had to be unified so members could move seamlessly between Credit Karma and products like TurboTax. Wan compared the process to playing two complex board games at once, where success depends on strategy and collaboration.

We also explored how Credit Karma is blending traditional AI with generative AI. From early chatbot experiments to today’s Wallet Analyzer and Tax Advisor, Wan shared how his teams decide when to push forward with new tools and when to slow down to ensure safety and trust. He also gave us a glimpse into the future, where agent-to-agent technology could bring open banking-style transparency to the U.S.

So how do you scale personalization without losing trust? And what can every business leader learn from Credit Karma’s balance between speed, culture, and responsibility? I would love to hear your thoughts after listening.

*********

Visit the Sponsor of Tech Talks Network:

Land your first job in tech in 6 months as a Software QA Engineering Bootcamp with Careerist

https://crst.co/OGCLA. Click or tap to follow the link." href="https://emea01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fcrst.co%2FOGCLA&data=05%7C02%7C%7Cd612b8a0aa6c4f08a31908dde5729a6f%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C638919002555348411%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=aI2VIHyOm57M6sowtgiI9S8lOBuYflAX15O4TQ3Safc%3D&reserved=0" rel="noopener noreferrer">https://crst.co/OGCLA

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