Artificial intelligence and finance: an unstoppable symbiosis towards efficiency and personalization

Artificial intelligence and finance: an unstoppable symbiosis towards efficiency and personalization

It is a fact that artificial intelligence (AI) It is already present in all industries around the world. It has already reached levels that were difficult to imagine a while ago: voice recognition, speech synthesis, automatic translation, drug discovery and the development of robotics, so the question that must be asked is: what is the scope of AI in the world of finance.

A priori, the national and international experts who consulted Ambit For this note they already talk about a transformation of the sector, driven by AI. One of them comments on the case of a “bot” that, from January 23 to June 11 and with an initial investment of US$1,000, had made a profit of US$5,600an impressive increase of 560% during the trial period. And this is just the tip of the iceberg.

Impact of AI on the industry

As explained to this medium Tory Jacksonhead of Business Development and Strategy at Galileo Financial Technologiesartificial intelligence is profoundly and lastingly transforming the financial landscape. From personalizing the customer experience to protecting against fraudAI is setting new standards in private banking.

According to Jackson, the most notable impacts of these technologies on the financial industry include: The evolution of chatbots towards personalized interactions with generative AI and fraud prevention and security, the generation of new risk models, where AI plays a crucial role in fraud detection and prevention, as well as “Advanced tools that analyze large volumes of data to identify suspicious patterns and prevent fraudulent activities before they occur.”

That look matches that of Vassilis Tziokashead of Enterprise Business Development at Matter Labswho analyzes that large-scale language models (LLM) “are excellent for analyzing big data while automating “routine tasks” and slow processes, such as manual data entry and transaction processing.

Tziokas also highlights the personalized and contextual customer experience, as it turns out that generative AI can provide personalized financial advice and asset recommendations based on risk profiles and individual customer behaviors.

At the same time, he mentions that AI virtual assistants can interact with customers in a multimodal way (voice, text and video), which makes the customer experience more complete and interactive. And he highlights, like Jackson, next-generation fraud prevention and risk management. “AI can predict market trends, credit risks and fraudulent activities by analyzing historical data and identifying patterns before human auditors can discover them,” he explains.

But more importantly, “AI can enable Real-time monitoring of global transactionshelping in the early detection of irregularities,” adds Tziokas.

Impact on employment in the financial sector

“The impact on the sector It is not less than the rest of the industries“, Explain Gaston Addatidirector of the Computer Engineering program at UCEMA, in conversation with this medium. For the teacher, AI “is affecting both people and companies in a certain sector.”

But for Addati, the financial sector, specifically, will be which will increasingly require the use of artificial intelligence and along with it, “it will be necessary to further increase security not only to prevent fraud, but to guarantee the reliability of investments”.

Addati adds that technical knowledge in “Programming, algorithms and AI models will be crucial” for what is to come. However, data analysis at the intersection with financial market knowledge will require specialists capable of mastering both worlds, “that of technology and that of finance.”

Tziokas, for his part, argues that there is natural concern about the displacement of high-level jobs due to the great automation that AI can enable, but estimates that technology will generate even more jobs or improve existing ones in the medium and long term. This is because financial institutions will need more AI specialists such as data developers, software engineers and machine learning experts, compliance specialists and AI policies.

Artificial Intelligence generative solution

Financial language models need access to sensitive data and information to achieve accurate and personalized predictions and decision making.

For Paula VillamarinGlobal Communications Manager of dLocal“the future of AI in the financial and fintech sector is promising.” The expert believes that the intelligent adoption of AI can create a more agile, secure and customer-centric financial ecosystem“which is why collaboration between companies, universities and governments is essential to promote its development.”

While, Santiago SinelnicofPrincipal Solutions Architect at Red Hatexplains that, on the one hand, AI will be the default interface between humans and computers, and, therefore, “between the client and their banks, offering relationship paradigms that are infinitely more personalized than the current ones.”

In this context, in addition to the evolution of the “Virtual Assistants” that each bank implements, application initiatives such as OpenBanking will be key, since they enable the consumption of bank products and services through any AI with which the client prefers to interact.

AI risks in finance

While the opportunities presented by AI are vast, It is also crucial to navigate regulatory and compliance challenges.Experts are clear in pointing out that innovation must go hand in hand with compliance to ensure that new technologies are not only effective, but also safe and reliable and, in turn, efficiently protect the digital, identity and physical security of users.

In this regard, Tziokas mentions Three risks arising from the AI ​​revolution in the sector and should be monitored for beneficial use.

  • Data privacy and transparency in decision-making: Financial language models need access to sensitive data and information to achieve accurate and personalized predictions and decision making, but “This creates unprecedented challenges regarding fair use of data and privacy preservation mechanisms.“, he says, although he points out that there are major advances in technology that address these problems.
  • Cyberattacks: In the same way that AI can enable better risk management solutions, “it can also empower cybercriminals to launch sophisticated attacks on financial institutions,” he warns, which can lead to Data breaches, financial losses and reputational damage.
  • Algorithmic bias: AI models can inherit biases from training data and fine-tuning processes, leading to unfair or discriminatory decision-making, especially in loans and credit evaluationPeople need to know (transparency) how decisions about their financial status were made.

The real challenge, and the great opportunity in this new era, lies in balancing innovation and regulation to build a financial future where technology and humanity converge harmoniously, offering more efficient services, safe and personalized for everyone.

Source: Ambito

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