Ask A Better Question, Get A Better Answer. How AI Can Impact Banking

By Stuart Grant, Global GTM for Capital Markets, SAP

Asking the right questions is as important as answering them. It becomes even more critical as disruption, change and competitive threats take hold.

“The exponential pace of new technologies, and the confluence of multiple trends are influencing how banks operate and serve customer needs,” according to Deloitte’s 2024 Banking Outlook. The sharp edges of industry convergence, embedded finance, open data, digital identity, and fraud will all continue to be felt this year and into the next. It makes for a continued bumpy ride for the banking industry, which is why so many banks are looking to AI technology to help create advantage.

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Heightened competition and evolving customer expectations are causing banks to rethink their strategies to stay ahead. AI is reshaping the art of the possible on how banks operate and serve customers. The ability to ask the right questions, combined with AI’s power to deliver better insights (and then better follow up questions) is becoming a key differentiator. In fact, one of the core skills of tomorrow will be the ability to ask questions that haven’t yet been thought of or were previously thought impossible to answer.

Below are four areas AI can deliver fast answers to intelligent questions.

1. Anticipating market trends – A financial analyst asks, “What market trends will impact our clients in the coming quarter?” Traditionally, compiling data to answer this question would take days. Today, AI can sift through massive datasets in minutes, providing actionable insights into shifting trends, emerging risks, and potential opportunities.

2. Predicting customer behavior – A relationship manager asks, “Which clients are at risk of leaving?” AI-driven customer analytics use historical data and predictive models to flag at-risk customers. Banks can then intervene early, tailoring their outreach strategies to retain valuable clients and reduce customer churn.

3. Enhancing risk management – A risk officer asks, “How can we identify emerging risks faster?” AI-driven risk models can analyze vast amounts of data to uncover early warning signals that may not be immediately obvious. AI can use this analysis to better assess and predict risks, such as credit defaults or fraudulent activities and enhance a bank’s ability to manage and mitigate risk. By identifying patterns and anomalies across portfolios, AI enables banks to respond proactively to emerging risks, potentially averting crises and reducing financial exposure.

4. Optimizing back-office efficiency – A back-office manager asks, “How can we improve our invoice processing?” AI automates and streamlines this process, significantly reducing manual effort and minimizing errors. The result is faster, more efficient operations, which in turn can lead to cost savings by identifying inefficiencies and areas for automation.

As financial institutions face the complex landscape of economic uncertainty, regulatory changes, and technological disruption, AI’s ability to provide clearer, data-driven insights will be essential. But asking the right questions is only the beginning. The real challenge is ensuring that AI is securely and responsibly integrated into decision-making processes. Modern, cloud-based enterprise systems are already doing the heavy lifting in this area by embedding AI into their core systems. In 2024, the ability to balance innovation with security and compliance will be what sets leading banks apart​.