will you do? super spike Will the evolution of artificial intelligence (AI) herald the end of the world?
or, new era?
Jason BurenSenior Vice President of Product Management, CCC Intelligent Solutions Co., Ltd..Cloud platform for the insurance and automotive industries tells PYMNTS that in his view it is clearly the latter and that we are entering an era of tremendous potential.
“It’s a really exciting time,” Barren said, adding that the business landscape is starting to leave the “first wave” of AI platforms pre-trained on public data and enter what he calls the “second wave.” I added that there is.
“In the second wave, organizations will use generative AI against their own internal data to solve narrower problems and take the lead with domain-specific, secure and proven data.” explained Mr.
Additionally, by using wholly owned corporate data, Power your internal AI enginecompanies can leverage the generative capabilities of technology to generate unique insights and advantages that competitors cannot replicate.
read more: The Role of Generative and Predictive AI in Future Payments
Data-Rich Environments Drive Data-Driven Transformation
Decades of digitalization of the business environment have created an operational enterprise infrastructure that enables knowledgeable organizations to gain insight through a future-proof flywheel of data-driven and often automated solutions. can now be collected, processed and extended.
Building on the transformation that predictive AI has already brought, Verlen said he sees two key things across the payments space where generative AI could have an immediate impact.
The first, he says, is the ability of generative AI to evolve fraud detection strategies and approaches.
“AI can create synthetic data, allowing us to train anti-fraud models without resorting to labor-intensive means. [legacy approaches]’” Mr. Veren pointed out.
The challenge with cheating is that there are very few real positives in the training data. This is where creating synthetic data is beneficial. Large language models can reference more data than previous approaches, so supervised learning may be able to better detect certain patterns that previous generations failed to detect.
Finally, Verlen exploits what many consider a weakness of generative AI: its tendency to “hallucinate” and create false content and unsourced hoaxes. By doing so, companies could even jump on the bad guys by charting, he added. Create a new attack vector likelihood map.
“There are certain areas where going a little off the rails can actually be a plus, and in that case it allows you to consider other scenarios that you might not have thought of on your own,” explained Verlen. “A lot of fraud detection is done by looking for outliers, which is often a labor-intensive and expensive process. can indicate vectors that are likely to come.”
Also read: AI regulation should target data origins and protect privacy
take over what has already been done and move it forward
Over the last few decades, predictive AI solutions and machine learning (ML) tools have already accelerated the agility and effectiveness of many business processes.
Generative AI needs to go further before it can be successfully commercialized.
“A lot of what we do in Large Language Models (LLMs) can actually open up more possibilities for new business use cases than just performance gains. [and even new businesses]’ said Velen. “The potential inherent in AI to push new horizons of efficiency and productivity in the macro environment is almost unbelievable.”
Already within CCC’s industry, AI is being used in a variety of workflows and use cases to enhance and in some cases completely transform historical processes.
Warren gave the example of a car accident in which the vehicle was a total loss and was declared a “total loss.”
In this case, the AI tool can look at pictures of the vehicle and identify the damage so the insurer can decide whether to assess the vehicle, Verlen explained. In that case, the insurance company can contact the lessor of the vehicle, make a payment, take ownership of the vehicle, and repossess the vehicle. All this in just a few hours instead of days or weeks previously spent processing transactions.
“AI will greatly improve the speed and convenience of the payment process, and not just the payment workflow. [where AI will have an impact]But we target everything involved in payment deployment by creating a specific context that drives responses,” he said.
Still, “these generations and technology waves have always coexisted and will continue to coexist for some time,” warns Berlen, manual processes being augmented by AI solutions and vice versa.
He believes that this period of “coexistence” will allow individuals to have “more time” to see things that are actually unique, thus creating new business value through “collaboration between generative AI and human intelligence.” He stressed that it would create something deeper and more meaningful.
“Every time we hit a pivotal moment, it is predicted to be a doom loop for humanity in terms of employment, but what happens 100% of the time? Quite the opposite. Productivity explodes. It has improved, more jobs have been created and we are enjoying a more vibrant economy,” added Baren. [generative AI] Because of technology, the words ‘replace me’ do not accurately capture the nature of change. ”
Rather, he says, AI will help enhance workflows by making labor-intensive workflows smarter, more productive, and increasingly optimized.
