What is needed to provide personalized financial guidance to more than 140 million people every day? That is the question that I asked 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, view a loan option or to browse for a better credit card. What we rarely consider is the technology that runs behind the curtain. Wan revealed that his teams drive more than 60 billion daily AI forecasts to understand the needs of the members, to protect their privacy and to guide them to the right financial choices. He explained why accuracy is everything in Fintech. A misguided recommendation can mean more than a bad customer experience; It can damage someone’s credit score and stop their progress.
Our conversation also looked at what happened after intuitive credit karma had acquired. Two very different technical piles had to be brought together and identity systems had to be united, so that members could move seamlessly between credit karma and products such as TurboTax. WAN compared the process with playing two complex board games at the same time, where success depends on strategy and cooperation.
We have also investigated how credit karma combines traditional AI with generative AI. From early chatbot experiments to the contemporary wallet -analyzer and tax adviser, WAN shared how his teams decide when they will continue with new tools and when they should delay to guarantee safety and trust. He also gave us a glimpse into the future, where agent-to-agent technology could bring the American open bank style to the US
So how do you scale up personalization without losing confidence? And what can every manager learn from the balance of Credit Karma between speed, culture and responsibility? I would like to hear your thoughts after listening.
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