Since late 2022, it seems artificial intelligence (AI) has pervaded nearly all corners of society. In reality, AI has been at the helm of a seismic shift in how we operate, especially within the banking sector. Both experts and bank executives can attest to the powerful efficiencies AI can bring, whether through streamlining business operations, optimising loan pricing, reducing redundancies, redefining risk management, or facilitating the flow of real-time information.

As financial institutions consider how to leverage AI to boost efficiency and improve customer experiences, they must also contend with some of the unique challenges that any new technology – artificial or otherwise – can bring.

The challenges

The majority of financial institutions recognise the opportunity of AI, with 80% of senior banking executives believing that effectively utilising AI is the defining factor in market competitiveness and 77% of bankers believing that the ability to unlock the value of AI will be the difference between the success or failure of banks. However, the adoption of AI, especially in the highly regulated financial services industry, is not without its fair share of perceived risks.

Contrary to popular belief, these challenges rarely stem from the technology itself. Rather, roadblocks often emerge around the issues of trust, security, and explainability that accompany this relatively new technology. When integrating AI, siloed data from legacy systems poses a significant challenge to an effective implementation. Trust must be established that the entire data set is healthy, clean and does not contain hidden bias in order to be activated in a solution and to fully realise the operational efficiency gains. In terms of explainability, AI’s decisions must be transparent and understood to secure the confidence of both banker and customer alike.

The fast-paced nature of emerging technologies in general poses its own set of difficulties when it comes to workforce adaptability and ensuring that the full potential value of the technology is unlocked. Management and employees need to be committed to continually optimising and evolving AI strategies as demands change and new capabilities are unlocked. Lastly, the importance of finding trusted and reliable partners is paramount. These partners should be technologically advanced, experienced in navigating the intricacies of large-scale data management, and committed to customer success.

While these challenges are necessary to consider, the transformative successes within sectors such as healthcare and retail banking show that they can be overcome to enhance both efficiency and customer experience. In short: the challenges of AI may seem daunting, but the rewards can make it more than worthwhile.

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The implementation

So, how can financial institutions incorporate responsible AI innovation into strategy decisions? The answer lies in the use of generative, conversational and predictive AI technologies. These technologies not only streamline operations for banking professionals but also frees them up to focus on areas where their human expertise is more specialised and valuable, such as responding to customers’ policy-related questions and delivering personalised service based on customer behaviour, preferences, and needs.

With AI automating redundant and manual processes, such as underwriting and approval processes, evaluating risk profiles and credit scores, there is a marked increase in productivity and risk management. By using algorithms and machine learning to automate and expedite routine tasks, AI can also reduce operational costs for these institutions.

But it’s not all about the bank; the customer stands to benefit significantly from AI technologies as well. Artificial intelligence offers a gamut of personalised services and product recommendations based on individual needs, financial patterns and unique preferences. This can result in more satisfied customers and a boost in operational efficiency for banks.

The ultimate goal of responsible AI development should be to prioritise trust, security and transparency. Keeping that goal top of mind will ensure proper data activation and easily understandable actions and recommendations once an AI implementation and ongoing optimisation is undertaken. Human intervention should also be a key part of any financial institution’s AI design philosophy so that it functions as a reliable, safe and honest backstop in an ever-increasing world where speed and immediacy could take a back seat to prudent decision making

The transformation

The transformation of the banking sector with the use of AI will reap many rewards: optimised loan pricing, reinforced risk management, compliance, control measures and financial growth, and the ability to generate valuable insights to drive strategic decision-making.

In this future landscape, the immediate thought is that AI will become the usurper of jobs. However, this is not entirely accurate in our view. While AI will undoubtedly take over some time-consuming operations, it will redefine the workforce rather than replace it. For example, the responsibility of oversight and maintaining ethical practices will firmly remain within human jurisdiction. This is a clear testament that, while AI is indeed powerful, it cannot be left completely unchecked.

Bankers will still need to ensure that AI technologies are not, for example, embedding bias into credit decisions or misinterpreting policies, especially as regulations evolve and change. In addition, until such time as regulators fully articulate and put in place the practices to govern, monitor, and manage decision making relative to AI generated actions, the speed and intensity of transformation related to this exciting technology will be throttled in a prudent manner.

The advent of AI within the financial sector continually proves to be a significant asset. Yet, as we chart our path forward, we must ensure that it remains just that – an asset, not a replacement. The ultimate goal of this transformation should be to create a balance between tech-enabled efficiency and the importance of human oversight to improve all experiences in the banking ecosystem.

Anthony Morris is SVP of Global Banking Strategy, nCino