While AI has already made significant strides in fintech, generative AI is a new frontier that could revolutionize financial services.

Artificial intelligence (AI) is nothing new in the finance industry. According to forecasts, the market for AI in fintech would expand at a rate of 28.6% and reach $31.71 billion in 2027. AI is currently being used in a variety of various use scenarios. 90% of fintech companies now employ AI, according to the Cambridge Centre for Alternative Finance. But a new creature has emerged: generative AI, which has the potential to completely alter the way we think about financial services.

However, the business is now only at the beginning stages, and generative AI still has a long way to go before it can realize its full potential.

How are financial services utilizing Gen AI? remarked Robert Antoniades, Information Venture Partners‘ co-founder and general partner. “It’s not being used, is the straightforward reply. In no way broadly. But what Gen AI has done is raised awareness of AI’s potential in the banking sector.

While businesses have introduced technologies like Chat GPT to assist streamline operations involving customers, he explained that the technology might have a significant impact on the back end of financial services.

However, this would only be feasible if the technology was 100 percent correct. It most definitely isn’t right now.

The Path to Exactness

Just a week ago, a stark example of how wrong Gen AI may be was made.

Social media erupted with enthusiasm on June 1 after “anonymous sources” reportedly informed journalists that SEC Chairman Gary Gensler had resigned awaiting “an internal investigation.” These assertions were refuted some hours later.

that was the journalist that published these untrue statements, then? a bot using generative AI.

In the financial services industry, 100% accuracy is required for anything that is significant, according to Antoniades. There is no place for delusions. Errors cannot be tolerated. Although not accurate, AI-generated replies are interesting to observe because they are actually rather good.

“It’s acceptable when used for marketing or prospecting. But no, not at all for financial advice. for keeping records. Definitely not.

The effects of accuracy could be disastrous

When contemplating prospective Generative AI use cases in the financial services industry, the necessity for perfection becomes evident.

Many have targeted financial advising with generative AI in finance. Many cannot afford financial advising services. However, Generative AI could personalize advising services based on client interactions.

“Gen AI is actually a very interesting use case there of how to provide that interaction and contextualization between the customer and the financial institution,” Antoniades said. “It can now have what one would consider a conversation with a client after ingesting all that data,” the author says.

Consider that you call a call center every day. Visit their website. Talking, browsing, and listening are ways to interact. I think generative AI’s strength is creativity. Communication ability.

Fraud and AML have also been identified as areas that might be greatly improved and are already using a growing amount of AI and machine learning models to improve results.

However, Antoniades clarified that updating infrastructure might be a particularly disruptive application of the technology.

Banking infrastructure hasn’t evolved in years. It uses COBOL, a 1959 language, and has survived changing technologies.

The creaking framework is aging. New programmers prefer more general code because the structure requires extensive bespoke programming to modify.

Antoniades said this will modernize infrastructure. He stated that generative AI could produce obsolete COBOL code and create a patch to speed up infrastructure transition.

Financial institutions risk switching platforms. However, Gen AI can now update infrastructure and programming to help a financial institution adapt to the present.

Mistakes in these outdated frameworks could be fatal.

“You want to know the money is there when you make a deposit in your bank account,” Antoniades said. It can’t be 99.9% present. Always there. They should provide accurate advice. Avoid 90% accuracy.

Financial institutions are aware of the possibility, according to Antoniades. All the sector needs right now is enough advancement for GenAI’s results to be nearly flawless.

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