How GenAI can be used to supercharge financial services from the inside out.
There's a lot of talk about how Generative AI can be used to improve customer experience, but what are the implications for internal software and back office processes?
In this episode of The Fintech Show, Trisha Price from Pendo, Marnix van Stiphout from ING, and Søren Andreasen from Nordea discuss the transformative impact AI is having in this area.
Tune in to this informative episod...
How GenAI can be used to supercharge financial services from the inside out.
There's a lot of talk about how Generative AI can be used to improve customer experience, but what are the implications for internal software and back office processes?
In this episode of The Fintech Show, Trisha Price from Pendo, Marnix van Stiphout from ING, and Søren Andreasen from Nordea discuss the transformative impact AI is having in this area.
Tune in to this informative episode to find out how:
- AI can automate KYC and CDD processes.
- Banks are leveraging AI to tailor user interfaces based on roles and experience.
- Tech can help surpass challenges posed by legacy systems.
Leveraging AI for Digital Transformation
AI adoption in all industries is growing and this is certainly true of financial services. According to the FCA, in the UK, 75% of firms are already using artificial intelligence (AI), with a further 10% planning to use AI over the next three years. Many organisations are now thinking about how it can be used to boost internal processes and the day to day lives of employees. But just implementing these tools doesn't necessarily guarantee success. Trisha Price, who is Chief Product Officer at Pendo, points out that the success of this depends on how well financial institutions use data.
She highlights three types of data that are crucial: quantitative (how employees use applications), qualitative (how they feel about them), and visual (tracking user behavior like repetitive clicks, which indicate frustration). By analyzing these data points, financial institutions can refine employee and customer experiences, ensuring that the software investments they make, actually do yield productivity gains and business value.
AI’s Role in Banking Operations
So how can AI be used in banking? We’ve looked at this before and got more great thoughts in this episode.
Marnix Van Stiphout, Chief Operations Officer at ING, acknowledges that while machine learning has been integral to banking for years—powering services like instant lending—generative AI (GenAI) presents new opportunities. One area he sees particular promise in is streamlining Know Your Customer (KYC) and Customer Due Diligence (CDD) processes, which traditionally require significant manual effort. AI-driven automation can gather and analyze vast amounts of data, enabling faster decision-making and reducing operational costs.
Søren Rode Jain Andreasen, Head of Digital Customer Engagement Hub at Nordic bank Nordea, echoes this sentiment, noting that many banks, including their own, are already using AI internally to enhance efficiency. AI-driven automation shortens process cycle times and improves customer experience while maintaining data security. It’s also being used internally for everything from risk assessments to capital requirement models, and GenAI is quickly becoming another essential tool.
AI Powered Decision Making
Of course, we’re also interested to learn how AI is shifting the role of bankers by acting as a decision-support tool. Price talks about how AI-driven assistants can analyze customer data to suggest personalized product recommendations and pricing strategies. Beyond insights, AI agents are beginning to take on tasks traditionally handled by employees, further streamlining operations and improving customer interactions.
Van Stiphout emphasizes the strategic question of whether to build or buy AI solutions. He suggests that banks should develop AI tools in-house if they directly impact client satisfaction. However, echoing Price’s earlier thoughts, he stresses that successful AI implementation depends on data readiness—ensuring that data is clean, structured, and accessible.
Another key challenge in banking is legacy systems, something Andreasen clocks onto. Advisors often have to navigate multiple platforms, increasing the risk of errors when transferring data. The good news is AI can help automate these processes and detect inconsistencies, reducing error rates and enhancing operational accuracy.
Personalization Through AI
We talk about personalisation a lot and this is something that has come up before, in interviews with the likes of CX bot, Zingly.ai. But it’s not just personalising the customer experience that could be valuable.
Price also discusses AI’s role in creating personalized experiences for employees too. Consumer platforms like Amazon and Netflix have shaped expectations for personalization, and financial institutions must follow suit. AI can tailor software based on the user’s role, experience level, and language preferences. For instance, an underwriter and a retail banker should have distinct interfaces suited to their tasks. Similarly, first-time users might benefit from a simplified experience, while seasoned professionals require quick access to advanced functionalities.
She also highlights AI’s role in localization, enabling automatic translation of banking interfaces to serve diverse customer bases. This ensures seamless communication and improves accessibility for global users.
As shown by this discussion AI is no longer a futuristic concept it’s a present day reality and it’s changing the way banks operate. Watch the video to find out how it could work for your organisation and check out our website for more great videos just like this one.
