Long gone are the days when you needed to visit a bank to complete a simple transfer. From the advent of credit cards and the introduction of Automated Teller Machines (ATMs) to the mobile banking revolution, the financial services industry stands out as one of the sectors most profoundly affected by the rapid pace of technological advancement.
The emergence of Artificial Intelligence (AI) technologies has opened the door to numerous opportunities for transformative change in various domains. As anticipated, the financial services industry is yet again poised to embrace the revolutionary shifts spurred by this technological progress.
In this article, we’ll explore the ways artificial intelligence is positioned to reshape the financial services industry, and then provide insights on some use-cases of artificial intelligence for the financial services industry.
How Artificial Intelligence (AI) is Transforming Financial Services
The impact of Artificial Intelligence (AI) in financial services encompasses numerous aspects that are revolutionizing the industry:
1. Reduced Cost & Workload:
As highlighted in Nvidia’s State of AI in Financial Services 2023 report, a survey of global financial professionals revealed that 36% of respondents managed to reduce annual costs by over 10% through the use of AI applications. The ongoing pursuit of greater operational efficiency in customer service motivates financial service providers to continuously optimize their business operations. The reduction of costs and the streamlining of workload related to servicing a substantial customer base are key for financial service companies to improve their processes. The automation of repetitive manual tasks, such as data entry, can contribute to significant cost savings and enhanced operational efficiency.
2. Better Customer Service:
The average financial service company strives to achieve efficient and responsive customer service at all times. Through the integration of artificial intelligence technology, AI-powered chatbots and virtual assistants have the capability to enhance customer interactions by providing instant support and prompt responses to customer inquiries. According to the report by Nvidia, 46% of financial service companies had an improvement in customer experience from the utilization of AI applications like chatbots. This significantly contributes in improving customer satisfaction and enabling businesses to offer personalized services to their customers, thereby leading to a reduction in customer complaints.
3. Enhanced Security:
Given the ever-evolving tactics of fraud tactics of cyber-criminals, financial service companies need to seek ways to enhance security for themselves and their customers. Artificial intelligence (AI) can play a very pivotal role in enhancing security measures within the financial sector by helping financial providers leverage datasets and algorithms for detecting and mitigating potential threats that might escape human detection. Artificial intelligence models recognize suspicious activity and help to cut the costs of investigating the fraud schemes. For instance, American Express, fraud algorithms to continually monitor every transaction on their platform in real-time for more than $1.2 trillion spent annually. By leveraging deep-learning based models, the financial giant detects fraudulent activities and makes split-second decisions to counteract them.
Use-Cases of Artificial Intelligence (AI) in Finance
Some of the most impressive use-cases of artificial intelligence (AI) in finance include:
1. Credit Scoring: Artificial intelligence models, such as Machine Learning algorithms, can be utilized for credit scoring to analyze the creditworthiness of individuals requesting credit. This eliminates the biases and fallibilities inherent in human-led assessments. Machine learning models for credit scoring are built using both linear, complex, and non-linear models, which utilize a broad range of data points. African money lending institutions and banks can leverage AI-based solutions to efficiently assign credit scores to loan applicants, ensuring a robust evaluation of their creditworthiness.
2. Virtual Assistants and Chatbots: Chatbots and virtual assistants have evolved beyond robotic cold-responses. By harnessing the capabilities of artificial intelligence, chatbots are now capable of offering intelligent and tailored answers to customer queries. This personalization transforms customer interactions, empowering them to efficiently manage their financial objectives and expenditure patterns. An exemplar case can be observed in Square, a leading fintech specializing in financial services and digital payments. Square employs conversational AI to empower its virtual assistant, which effectively addresses 75% of customer inquiries. By utilizing a combination of NLP models, Square aims to further expand its AI capabilities to cover an even broader spectrum of tasks.
3. Insider Fraud Prevention: Insider fraud remains a challenge for numerous retail enterprises. It is a type of financial fraud that is conducted from within by the staff of an organization. AI models allow organizations to track and prevent illicit diversion of finances by staff members.
4. Transaction Monitoring: The importance of transaction security cannot be overstated, particularly in light of the escalating financial fraud cases. In Q1 2023, Nigerian banks reported a staggering $2.3 million in fraud incidents through mobile and web channels. This underscores the pressing need for fortified security measures. Artificial intelligence-driven models, tailored for real-time fraud detection and assessment, empower financial service providers to proactively oversee platform transactions, effectively thwarting potential fraudulent activities. In an interview, the Vice President of Risk Management at American Express highlighted that their AI system diligently monitors the entirety of transactions, delivering an impressive 8 billion credit and fraud risk decisions in real time.
5. Prediction of Exchange Rate Fluctuations: Another use case of artificial intelligence in finance involves forecasting currency exchange rates fluctuations within the market. With a machine learning approach, financial providers can leverage multiple patterns and data points to help users predict fluctuations of the exchange rate over time. This capability finds particular relevance in Nigerian fintech trading apps, as it can be extremely useful in empowering forex traders to utilize AI-assisted predictions for fluctuations in the Nigerian naira.
Final Thoughts
The effective implementation of artificial intelligence into the business processes of financial service providers presents tremendous benefits that can enhance efficiency and curb unnecessary expenses. The use of this technology not only enables the business to operate more effectively, but also elevates the customer experience by providing personalized services. As the financial services industry increasingly becomes highly competitive, customers demand financial solutions that are extremely proactive. As a result, the implementation of artificial intelligence becomes extremely crucial for financial service providers—in essence, neglecting advancements in AI technology could prove costlier in the long run.
