Published on September 14, 2023 by Gabriel Alonso Zuniga Cedeno
We have witnessed an unprecedented phenomenon in recent years – the growing presence of artificial intelligence (AI) in the world of finance. This technological revolution is here to stay and has started to transform the way we conceive of and execute financial operations. We believe AI adoption in finance is not simply a passing trend, but a necessary and promising evolution to optimise and empower the future of financial institutions.
AI has proven its ability to process massive amounts of data at astonishing speed, and this has revolutionised data analysis and market forecasting. Advanced algorithms can detect hidden patterns and trends in financial markets, giving investors and analysts an invaluable competitive advantage to make more informed and accurate strategic decisions.
AI has also been an indispensable ally in risk management and fraud detection. Through real-time analysis of transactional data and behaviour patterns, AI is able to identify potential suspicious activity, protecting both financial institutions and their customers. This ability to detect accurately is essential for strengthening confidence in the financial system and ensuring its integrity.
We are excited by the idea of how AI has improved customer service in the financial sector. AI-powered chatbots can provide quick and accurate responses to customer inquiries, significantly improving their experience and streamlining service processes. This not only encourages greater customer satisfaction, but also frees up time and resources so finance professionals can focus on more strategic, higher-value tasks.
Likewise, process automation has been an extraordinary achievement thanks to AI. Tedious and repetitive tasks, such as invoice processing or payment management, can now be performed accurately and quickly by algorithms, reducing error and increasing operational efficiency. Such automation boosts productivity and enables more effective and agile financial management.
1. Data analysis and market prediction:
AI makes it possible to analyse large volumes of financial data quickly and accurately. Algorithms can identify hidden patterns and trends in financial markets, helping investors and analysts make more informed decisions. Gartner expects 75% of financial companies to implement AI in their data analysis processes by end-2023.
2. Risk management and fraud detection:
AI is able to evaluate large amounts of data in order to discover potential financial risks more accurately and in real time. Algorithms can analyse credit history, transaction data and behaviour patterns to identify potential fraud or suspicious activity. According to a PricewaterhouseCoopers study, 52% of financial institutions use AI to detect and prevent fraud.
3. Improved customer support services:
AI has transformed the way customer service is provided in the financial sector. AI-powered chatbots can provide quick and accurate responses to common queries, improve the customer experience and reduce operating costs. Juniper Research expects AI-based chatbots to save financial institutions more than USD8bn annually by end-2023.
4. Process automation:
AI can automate manual and repetitive tasks in finance such as invoice processing, payment management and account reconciliation.
“According to our analysis of more than 2,000 work activities in 800 professions, close to half of the activities for which salaries equivalent to $15 trillion are paid in the global economy have the potential to be automated if proven technologies are adopted” – A future that works: Automation, employment and productivity, by McKinsey & Company
This technology not only improves efficiency and accuracy, but also allows financial professionals to focus on higher-value activities. AI-powered automation can reduce accounts payable processing costs by 30%, according to a McKinsey report.
5. Personalised financial advice:
While caution is required when investing with the advent of AI, virtual financial advisors are gaining popularity. These virtual assistants have shown in some cases to provide good quality, personalised investment recommendations tailored to a client’s individual needs and goals.
AI is transforming the financial sector on multiple fronts. From data analysis and market forecasting to risk management and improved customer service, AI offers a wide range of benefits for financial institutions. With statistics supporting its effectiveness and continued growth in adoption, AI is emerging as an indispensable tool in the financial world. The combination of human effort and AI promises to optimise the future of finance and pave the way for greater efficiency and business success.
In short, AI has become a fundamental pillar in offering personalised financial advice to clients. Virtual assistants and specialised algorithms can understand the individual needs of clients and provide highly personalised investment recommendations. This opens up new opportunities for clients to make sound financial decisions and find investment strategies tailored to their goals and risk tolerance.
AI has radically changed the financial landscape, and its importance would only continue to grow in the years to come. Its ability to process data, identify patterns, manage risk and provide more personalised services has led to an unprecedented evolution in the financial space. We believe harnessing the power of AI in finance will not only provide a competitive advantage, but also guarantee excellence and continued progress in this dynamic field.
How Acuity Knowledge Partners can help
We are a consulting company with experience in technology and innovation, and play a fundamental role in guiding and supporting our clients towards effective implementation of AI in their financial operations. Many of our own analysts are already using our own AI based technology solutions in their day to day jobs in order to provide solutions to our clients.
1. Evaluation and planning:
We first identify key areas where AI can have a significant impact on a client’s financial operations. We conduct a thorough analysis of existing processes and the specific challenges facing the business. Following this, we develop a personalised strategic plan for AI adoption, aligned with the client’s objectives and resources.
2. Selection and customisation of solutions:
The variety of AI technologies and solutions available can be overwhelming. We help clients select the right tools and algorithms and customise these solutions to meet their specific requirements, guaranteeing a smooth integration with existing systems.
3. Implementation and training:
AI implementation requires a careful transition and adequate training. We provide technical support during the integration process, ensuring the AI platforms work optimally and fit into the company's operations. We also offer training programmes for employees to gain the necessary skills to work with these new tools effectively.
4. Monitoring and continued improvement:
We not only implement initial solutions, but also set up a system of ongoing monitoring and evaluation to ensure the AI platforms work effectively and meet the stated goals. We also ensure the technology stays up to date and adapts to changing business needs and challenges.
5. Process optimisation and decision making:
With the necessary AI in place, we collaborate with clients to streamline existing financial processes. Thanks to real-time data analysis and predictive capabilities, they will be able to make more informed and proactive decisions, leading to greater operational efficiency, more accurate risk management and a better understanding of their clients' needs and preferences.
Sources:
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Gartner – ¿En qué se centrará el sector financiero en 2023? – Topaz. (2023, 23 March). Topaz. https://www.topazevolution.com/es/noticias/gartner-en-que-se-centrara-el-sector-financiero-en-2023/
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Mangelsdorf, L. (2023). Inteligencia Artificial en Finanzas: 10 casos de uso que serán más comunes en 2023. Yokoy – Gestión de gastos corporativos impulsada por IA. https://yokoy.io/es/blog/finanzas-ia/
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PricewaterhouseCoopers. (s. f.-b). Prevención y Detección de Fraude. PwC. https://www.pwc.es/es/forensic-services/financial-crime/prevencion-y-deteccion-de-fraude.html
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Armenta, M. H. (2020). La Inteligencia Artificial ayudó a prevenir fraudes financieros por 2,000 mdd en AL. Forbes México. https://www.forbes.com.mx/tecnologia-inteligencia-artificial-prevenir-fraudes-financieros/
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Aunoa. (2022). El Futuro de los Chatbots: IA Conversacional. Aunoa. https://aunoa.ai/futuro-de-los-chatbots-estadisticas-que-demuestran-que-debes-invertir-en-ia/
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Bot de inteligencia artificial: transformando la comunicación con los usuarios. (2023, 23 June). Becas Santander. https://www.becas-santander.com/es/blog/bot-inteligencia-artificial.html
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Shevlin, R., & Shevlin, R. (2023). Por qué 2023 es el año del chatbot en la banca. Forbes España. https://forbes.es/empresas/228944/por-que-2023-es-el-ano-del-chatbot-en-la-banca/3
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Sánchez, C. (2023, 23 June). McKinsey calcula que la inteligencia artificial automatizará la mitad de los empleos. elconfidencial.com. https://www.elconfidencial.com/economia/2023-06-23/mckinsey-calcula-inteligencia-artificial-empleos_3670854/
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McKinsey & Company. (2017, January). UN FUTURO QUE FUNCIONA: AUTOMATIZACIÓN, EMPLEO Y PRODUCTIVIDAD. MCKINSEY GLOBAL INSTITUTE, 1, 4.
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About the Author
I am a professional focused on FP&A, in addition, I have specialized in Big Data & Process Automation focused on the development of financial analysis with intelligent applications to facilitate the analysis and increase its quality, and at the same time generate an impact within the work team and the same company
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