Financial companies' annual revenue grows 10% with the aid of Artificial Intelligence

Charlie Taylor

Financial services companies are looking for new ways to define and execute more assertive Artificial Intelligence (AI) strategies. AI solutions can operate in virtually every function of the company, such as customer service, cybersecurity, account acquisition and regulatory compliance. Technology also contributes to organizations' gross revenue and bottom line, according to a NVIDIA study. NVIDIA Enterprise spoke with industry professionals around the world executive leaders, managers, developers and IT architects from financial technology companies, managers investment banks and retail banks and, based on this, produced the study “State of AI in Financial Services” (“The State of AI in Financial Services”, in the original) focusing on the main technological benefits and challenges of the current market. financial services professionals see the potential of AI and are willing to invest more in technology to deliver what it promises. Companies, who see how AI can generate a competitive advantage, create products, increase gross revenue and reduce costs to improve results, are the ones that are making the most of the technology's potential ”, comments Marcio Aguiar, director of NVIDIA Enterprise in Latin America.

Companies: AI increases revenue and reduces cost

Most participants recognize that business Artificial Intelligence has its value: 83% agreed with the statement “AI is important for the company's success in the future”. The survey results show that, for financial services companies, AI brings growth opportunities. More than half of the respondents with a formal opinion responded that the technology will increase the company's annual revenue by 10%, with 34% also saying that the revenue growth is more than 20%. On the other hand, only 12% of the participants, with the exception of those who marked "I don't know", say that AI does not contribute to revenue growth.


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AI can also improve the bottom line of financial services institutions by reducing costs. Banks, insurance companies and investment managers, for example, already carry out their daily operations more efficiently thanks to technologies such as conversational AI, robotic process automation, optical character recognition and other machine learning and deep learning applications. These AI services optimize time and reduce expenses by automating the processing of claims communications, assisting call center operators with automated speech recognition for transcribing calls and performing other tasks that require manual labor.

Advantages of AI to customers

Survey participants also claim that AI has helped companies in three main areas: generating more accurate models (42%), ensuring competitive advantage (41%) and creating products (34%) .Using technology to create models more accurate results generate better results for banks and customers, especially in protecting against fraud and maximizing returns on investments. These benefits provide a competitive advantage that generally guarantees greater market share and offers more value to shareholders. The new AI products bring cross-selling opportunities, as they allow for greater personalization, which improves customer retention.

Reaching AI goals

There is no denying the advantages of using Artificial Intelligence in financial services, but in the path from research to business-scale production of AI models for banks, insurance companies and investment managers, there are possible difficulties and challenges. The research identified these obstacles , starting with the biggest challenges to achieve the companies' AI goals. The three main points pointed out by the participants were the scarcity of data scientists (38%), an insufficient technology infrastructure (35%) and the lack of data (35%).

Challenges

To overcome these challenges, executives are investing in the company's specialization in Artificial Intelligence. Of the executives, 60% responded that the main focus from now on is to identify other use cases for the technology. One in two participating executives pointed out that the company also plans to hire more AI specialists to fill the scarcity of data scientists. These results open space for further exploration, especially in the context of new AI frameworks and platforms for smarter banking transactions.

Main uses of AI in financial services

Survey participants working in financial and investment technology companies say that currently, portfolio optimization and investment robots are the main uses of AI prioritized by companies. This data is in line with maximizing customer return on investments. Participants working in commercial and retail banks say companies are investing in AI primarily to detect fraud through payments, transactions and preventing money laundering. . These results show that the primary focus is on protecting customers' sensitive financial data.

Future of the banking sector with business AI

With these main uses of AI in financial services and so many others available to banks, insurance companies and investment managers, it makes sense that the sector wants to invest more in AI. Except for the survey participants who scored "I don't know", 62% said their company should invest more in Artificial Intelligence applications. With the identification of new use cases and the increasing presence of AI in organizations, the next challenge for executives and IT leadership is to create enterprise AI platforms that deliver the productivity, scalability and return on investment needed to help the company's diverse AI teams.

Scientists

Instead of starting from scratch, data scientists who create models for various use cases can use containers from NGC, NVIDIA's GPU-optimized software hub. Some of them are NVIDIA Jarvis, for automated speech recognition and speech-to-text conversion for call center transcriptions, and NVIDIA Merlin, for recommendation systems application frameworks. To learn more about AI in the future of financial services , you can access the web page or download the full survey report. To obtain the survey data above, NVIDIA Enterprise talked to 200 industry professionals around the world. Just click here if you are already an investor. .

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