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Risks and Rewards of Generative AI: Productivity to Accelerate

Yossi Chad ENGAGE2023 NY - Global Banking | Finance

NICE Actimize recently held its annual financial services industry technology conference, ENGAGE 2023, with more than 500 participants and 200 financial institutions attending the New York event. Generative AI was a key trend addressed throughout the conference, including a keynote forum that uncovered the “Risk and Rewards of Generative AI,” led by the company’s Global Head of Product, Chad Hetherington, and Global Head of Engineering, Yossi Levin. The technology executives saw positive growth for Generative AI innovations with a wide range of use cases under development that could increase productivity throughout bank operational functions. 

How do you see the immediate impact of Generative AI playing out at financial institutions – what are the rewards? 

Hetherington – Generative AI will generate a massive impact, particularly in accelerating productivity. Much like what we saw with the personal computer revolution, the real leap forward is squarely focused on efficiency. But the human touch will still be critical in its implementation. Whether it aligns with onboarding functions or with investigation teams, the core operations areas will experience a very material impact. According to Goldman Sachs, over the next ten years we will see a 7 percent increase in global GDP which translates to about 7 trillion dollars, while lifting overall productivity by 1.5 percent. We advise our financial institutions to have the proper controls around Generative AI to ensure the right business outcomes. Many people define it as an advanced search engine, but it clearly delivers much more than that. 

What are FIs saying are the most critical gains where generative AI is applied? 

Levin – We have observed that Engineering and Data Science teams have been very quick to adopt the new technology in order to increase velocity to bring innovation to market faster. But when it comes to applying the technology to solving business problems, we should think about multiple horizons of execution and results. Low hanging fruit should be picked quickly – those quick projects that get fast results. But the bigger projects that can profoundly impact the business also need to start now. Big long-term bets can drive results that are meaningful to the overall operation.  

What use cases are emerging that integrate Generative AI at financial services institutions? 

Levin – We are seeing a focus around text-driven use cases. The “co-pilot” use case are taking shape of decision recommendation or decision support. This addresses the need to reduce labor cost while keeping the human in the middle to validate AI recommendations. But it does not stop there. Text generation use cases are next. Things that are hard or lengthy to do and easy to review are also in flight. These use cases should be carefully released and teams should be trained on the various risks so they do not take AI recommendations blindly. During these processes, we should be careful not to de-humanize customer care. At first, AI may not be great at handling a client who was scammed out of his or her life savings. Moreover, while dealing with money laundering prevention, AI mistakes can have serious implications so initial efforts should be measured carefully. At this point, the man in the middle is relevant. I do think as humans take more of a reviewers’ role than doers role, we need to make UI and UX fit the new role.

What advice would you give financial institutions as they look to adopt Generative AI throughout their operations? 

Hetherington – With good training data, there are use cases where Gen AI can accurately suggest what we should do in a given scenario. And we are seeing the tech evolve and tackle its weaknesses quite quickly. Examples include how to action an alert or fix a bug in software. The most advanced use cases are fully autonomous, where the machine drives decisions, and we oversee them. Imagine working your pre-investigated alerts over your morning coffee.

How will Generative AI impact the job market? 

Levin –  The Challenger Report, which reports on the jobs market here in the US, added a new job cut code related to AI. In May, it was estimated that 3900 jobs were cut because of AI. But AI is not creative nor strategic. It is still necessary for humans to drive this innovation. Some roles will be handed over to AI for sure. The expertise in these roles will still be needed, so it is not role elimination we are looking at but instead some reduction as well as the emergence of entirely new fields. Therefore, technologists should make themselves savvy very fast to stay relevant. 

Since the technology is relevant for multiple fields, I believe that in the coming years more roles will be created than roles eliminated. 

Where do you see vendors bringing innovation to Generative AI? What is in the works at NICE?

Hetherington  NICE Actimize has a number of initiatives in place that we are investing in, and we are committed to bringing Generative AI in a responsible way to protect our financial institution customers’ interests as well as the interests of their customers. Many of our meetings at ENGAGE revolved around moving into Generative AI in meaningful ways which could accelerate performance across the institution. We are focused on use cases where financial services firms have painful business problems and we have data and domain expertise that others do not.

Our parent company, NICE, has also made significant inroads in Generative AI and has recently announced a series of breakthroughs utilizing this advanced technology. NICE this week was the first to introduce an enterprise-grade AI for the CX business, based on domain-specific business cases, with humanized conversations with the highest level of security guardrails while ensuring responses are aligned with brand needs and goals.

As an industry, we have yet to understand the full potential of generative AI, but we have seen that this is a transformative leap forward. It provides reasoning capabilities that are much more “human-like.” Today, we have a massive ecosystem and industry that includes almost 30M developers worldwide. This provides a substantial accelerating force for this technology. What is hard to imagine is that this technology has the potential to empower all 8B people on this planet to become developers. Never have we had a force multiplier as we do with Generative AI.   



Global Banking & Finance Review


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