Banking: How AI is reshaping roles, risk, and relationships

One of the most unexpected outcomes of Artificial Intelligence (AI) ascent is the transition of data personnel from back-office functions to client-facing roles in modern banking.

With the advent of AI models that anticipate customer needs, conduct instantaneous credit scoring, and predict delinquency risks, banks are now able to issue loans at an unprecedented scale.

Supporting this expansion is a growing cohort of data scientists, many of whom are increasingly involved in marketing functions.

Initially, banks adopted basic digital tools—such as chatbots—to improve customer service.

But AI truly gained traction in credit analysis and scoring. Given that many Kenyans use multiple banks and mobile lending applications, AI algorithms can assess a customer’s creditworthiness by analysing vast datasets. This empowers banks to make better-informed lending decisions.

Today, lenders are finding it more efficient to serve niche markets by recommending customised products, thereby maximising value within the banking ecosystem.

By harnessing AI’s capabilities, they are developing and deploying financial products tailored to individual customer needs. For instance, AI can identify which products are most suitable for a specific client and generate personalised recommendations.

This advancement has dramatically expanded the banking frontier, allowing for more effective customer modelling based on opportunity and risk.

The result is fast, efficient pre-approved loan facilities. AI models can anticipate which customers are likely to need credit, evaluate their transaction behaviours, and set pre-approval limits—delivering services on demand.

AI has also revolutionised fraud prevention, particularly through the development of cybersecurity systems designed to protect customer deposits. These systems analyse transaction patterns, identify potential fraud, and intervene in real time to protect funds.

There’s no doubt that the speed at which AI is transforming the banking sector is remarkable. A wide range of solutions is emerging in the market, offering banks new ways to execute growth strategies and integrate AI into their operations.

A robust data strategy is vital to successfully leveraging AI. This should begin with a clear definition of the institution’s needs, followed by a thorough evaluation of the technology acquisition process, implementation plans, and monitoring frameworks to ensure measurable financial outcomes.

To fully harness the benefits of AI, the demand for data scientists and digital experts is growing rapidly, resulting in a surge of opportunities in the digital job market.

As the world continues to embrace AI on a large scale, we must reimagine our professional roles. To stay ahead of automation and remain relevant in an AI-driven job market, we must become intentionally AI-enabled—equipping ourselves with a blend of technical, analytical, and interpersonal skills to thrive in the evolving workplace.

The writer is the Chief Data Officer at Absa Kenya