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Following the launch of ChatGPT in November 2022, Artificial Intelligence (AI) has drawn significant attention and mainstream awareness with conversations about how it could reshape the modus operandi of different industries. This is particularly evident in digital finance, where thought leaders, innovators, entrepreneurs, and governments throughout 2023 shared numerous perspectives on AI and its implications on financial services.
While AI is no stranger to financial services, recent discussions have been centered on the emerging use cases, benefits, and potential threats of AI going forward. And financial institutions have shown immense interest. Statistics indicate that inquiries about AI from banks increased five-fold in the first quarter of 2023 – compared to the same period in 2022. Further research shows that banks are increasingly investing in Artificial Intelligence and are projected to spend $4.9 billion on AI platforms by 2024, a 21.8% compounded annual growth from 2019.
Given the numerous manual processes that traditional financial institutions struggle with every day, artificial intelligence presents a lasting solution that allows them to automate processes for better efficiency, security, and customer satisfaction. In this blog, we discuss the various ways that artificial intelligence (AI) is expected to reshape the financial services landscape in 2024, and how financial institutions are channeling the power of automation through AI for continued growth.
Personalization of Financial Services
Offering customized investment advice
Personalized financial planning with AI
AI in Insurance
A case in point is Ant Financial, a Chinese FinTech company that devised a solution called Ding Sun Bao, targeting the auto insurance industry. This innovative system employs machine vision to analyze vehicle damage and swiftly generates a comprehensive report for users. The report includes details on the damaged parts, a suggested repair plan, and insights into how the accident might impact the user’s premiums in the subsequent years. According to Ant Financial, this system is capable of assessing damages and processing claims in a mere six seconds. In contrast, human claims adjusters reportedly took six minutes and 48 seconds to reach their conclusions.
Personalization in lending
Statistics show that 62% of banks are already using AI in lending. Traditionally, credit involved a lengthy manual process right from application, through underwriting, to loan issuance and servicing. However, this has already been replaced in the age of Credit 3.0, where the entire credit lifecycle is automated. Going forward, more innovation is anticipated around the customization of loan terms, interest terms, and repayment schedules, personalized to align with individual financial capabilities and preferences without putting the lender at risk. Many financial institutions have already begun implementing AI-based credit decisioning and loan approval software, minimizing the time wastage and long approval times required when applications are reviewed manually.
Customer service
Generative AI is expected to further reshape the customer service segment through chatbots and automated virtual assistants. These tools are integral in providing real-time, all-round customer support in answering customer queries and offering personalized recommendations. Available 24/7 with a wide array of features, chatbots have been increasingly commonplace as part of a typical banking experience, especially with neobanks, challengers, and digital-first players. A human customer service representative is usually available should the customer wish to speak to them, but the first AI chatbot layer allows for most issues to be solved without human intervention.
Typical examples of AI in customer support include Fatema, Ila Bank‘s digital assistant; RAKBANK ChatBanking from the National Bank of Ras Al Khaimah; Falcon of Abu Dhabi Commercial Bank; Emirates NBD’s EVA, and Amy by HSBC. Leveraging learning language models (LLMs) in chatbots will be a key contributor in enhancing customer experience, boosting operational efficiency, and lowering costs as the effectiveness of chatbots continues to improve.
Risk Management and Fraud Mitigation through AI
AI has been seen as a significant player in risk management and prevention of fraudulent activities, not only in finance but across other industries. According to statistics, the AI trust, risk, and security management market was worth $1.7 billion in 2022 and is expected to cross $7.4 billion by 2032, growing at a CAGR of 16.2%. Financial institutions are widely integrating AI into different domains to create fortified defense systems against various financial crimes through:
Real-time AI analytics
Real-time analysis through AI enables swift identification and analysis of data from diverse sources like ATMs, internet banking, and vendor channels. This technology seamlessly integrates anti-financial crime measures, breaking down data points for predictive insights into patterns and links between transactions. Criminals exploiting various locations and channels can be countered effectively, ensuring the institution’s financial systems remain secure. Machine learning capabilities also enable real-time transaction data collection to predict both apparent and hidden links and patterns in financial transactions.
Intelligent fraud detection
Mastercard, for instance, is introducing an innovative generative AI model called Decision Intelligence Pro, aimed at empowering banks with real-time assessment capabilities for suspicious transactions on the Mastercard network. The model, trained on approximately 125 billion annual transactions processed through the Mastercard network, specifically focuses on understanding relationships between merchants to swiftly and effectively identify potential fraudulent activities. According to Mastercard, Decision Intelligence Pro has the potential to enhance fraud detection rates for financial institutions by an average of 20%, with some notable cases reporting improvements of up to 300%. What’s more, this process only happens in just 50 milliseconds!
Effective risk assessment and reporting
AI ensures effective risk assessment by constantly evaluating compliance with local and international financial reporting standards to prevent fraudulent reporting in financial statements. AI protocols check transactions against authorized limits and data access and suggest corrective measures ahead of time. This proactive approach enables the presentation of accurate financial statements. Fraud risk assessments, linked to real-time data, inform mitigation strategies and emergency preparedness.
Automating Manual Processes with AI
Efficiency is a major factor in banking and finance. It could span from how efficiently customers can access banking services to operational efficiency, cost efficiency, growth efficiency, and more. Through automation, AI is finding extensive use cases in enhancing efficiency in financial institutions. NVIDIA conducted a survey in 2023 on 500 financial services professionals from across the world, aiming to pick their minds on the trends, challenges, and opportunities in computing, AI, and Machine Learning. In the report, “State of AI in Financial Services“, NVIDIA finds the results as shown in Figure 1 below. These metrics are expected to grow even higher in 2024.
- Enhanced customer experience: Automation allows financial institutions to offer quicker and more efficient services to their customers. Tasks such as account verification, transaction processing, and customer support can be expedited, leading to a more seamless and satisfying experience for clients.
- Operational efficiencies: AI streamlines internal workflows by doing away with the manual processes that are time–consuming, draining, and challenging for humans. Automating such routine tasks not only accelerates processes but also enhances overall internal efficiency in financial institutions.
- Cost efficiency: AI technologies can automate repetitive and time-consuming manual tasks, reducing the need for human intervention. This can lead to significant cost savings for financial institutions by optimizing resource allocation and minimizing labor expenses.
- Efficiency in adapting to market changes: Data-intensive aspects of financial services that are traditionally challenging can be automated using AI to identify market dynamics, such as changes in customer behavior, investment, and financial trends. These insights enable swift and accurate decision-making as they respond to market changes.
- Accuracy and integrity: Financial institutions are leveraging AI and ML to create sophisticated algorithms that are used to identify patterns and outliers in financial data. These metrics help improve the quality of data by identifying missing values, duplicate records, or suspicious activities.
- Competitive advantage: By leveraging AI for automation, financial institutions gain a competitive advantage through improved efficiency, faster services, and enhanced customer satisfaction, positioning them ahead in the market.
- Market expansion: Efficiency, driven by AI automation, provides financial institutions with the scalability needed for market expansion. Streamlined processes allow for better resource allocation and responsiveness, supporting growth and penetration into new markets.
Final Thoughts
Considering the wide range of Artificial Intelligence use cases in digital finance, the road ahead promises continued adoption and usage of AI in enhancing financial services in 2024. Banks and financial institutions have already witnessed first-hand how integrating AI into their various business models can streamline service delivery, enhance internal efficiencies, and foster customer relationships while lowering operational costs.
Going forward, financial institutions are expected to embrace AI-driven solutions that not only meet current demands but also pave the way for a more intelligent and responsive financial future.
Tagged:
- AI, digital banking, global
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Omar Mansur, Managing Director APAC
Tech focused and savvy disruptive strategy expert with a strong passion for exploring innovation and making a difference. Having an extensive history working with various Tier 1 and 2 financial, government and fortune 500 institutions across the GCC, Africa, ASEAN and South Asian region whilst delivering game changing and revolutionary initiatives to change the world. Always on the lookout for the "next big thing", currently looking to invest in startups and ideas that aim to change the world and impact lives.
