AI could add billions to banking and insurance in 2024
In recent years, AI has made significant progress in the banking and insurance industries, driving efficiency, improving customer experience, reducing cost, and enabling data-driven decision-making. Going into 2024, this trend will likely evolve with key areas of growth including customer service and support, risk assessment, fraud detection and prevention, personalization, and automation.
Josh Builta, Senior Director of Research, Applied Intelligence, at Omdia, explains that AI in the banking and insurance industries is “aiding in tasks such as claim management and insurance underwriting” and “powering personal financial advisory services.”
According to McKinsey, banking could benefit greatly from Generative AI (GAI), with the technology projected to add between $200 billion and $340 billion to the industry annually. The insurance industry could see $50 billion to $70 billion added annually.
Builta notes that the most noticeable and immediate influence could be via GAI-enhanced chatbots and virtual assistants, “which have the potential to enable human-like interactions and free-flowing conversations that deliver clients more personalized, enjoyable, and productive customer service.”
Deborah Yao, Editor of AI Business, says Generative AI is “poised to transform the banking and insurance industries in multiple ways, the most common of which is by super-charging the user experience, whether it is to roll out smarter robo-advisors in wealth management, improving the capabilities of consumer-facing chatbots or delivering personalized offerings to clients.”
“It can also transform operations by accelerating document searches, automating reports and claims processing, and generating insights from troves of data to aid in decision-making or forecasting,” she says.
Sreya Francis, Head of Technical Innovation at Farm Mutual Re, says that 2024 will unveil a “tapestry of cutting-edge AI trends.”
Francis adds: “The market outlook is a dynamic canvas where AI not only forecasts trends but actively shapes them, offering real-time risk assessment through advanced deep learning networks and redefining investment paradigms through algorithmic trading and portfolio optimization.”
According to Omdia’s AI Market Maturity Report, 62% of financial services companies have an AI budget of over $1 million, and 38% have an AI data management and governance program in place.
Andrew Brosnan, Principal Analyst, Applied Intelligence, at Omdia, explains that the adoption of AI in financial services is “really picking up.”
“The sector has leveraged AI for quite some time for use cases such as algorithmic trading,” he says, “but now, with the advent of GAI, we see the role of AI in finance broadening out over the next five years.”
Brosnan concludes that AI and GAI will continue to bring further transformation to the financial services sector through enhanced customer experience and risk mitigation in various banking activities, as well as further automation of financial operations.
Reflecting this, 45% of financial services companies say they are confident AI will deliver positive results towards business goals within 12–24 months, according to the Omdia AI Market Maturity Report.
With great power comes great responsibility
However, with exciting growth comes several challenges, including data privacy concerns, regulatory compliance, and the need for robust cybersecurity measures. Customer trust and transparency are critical factors for the successful adoption of AI in banking and insurance.
Francis says that navigating this future “necessitates overcoming the intricate challenges of data privacy preservation via technologies like federated learning, ethical AI governance, and staying ahead of regulatory compliance in the AI-driven era.”
“Amidst these technical hurdles, there lie vast opportunities for those who harness AI's transformative potential to reimagine finance, setting new benchmarks for innovation, security, and profitability.”
Rohan Doctor, Founder and CEO of Louisa.AI, explains that, while popular GAIs like ChatGPT can use publicly available information online as a model for responses, within businesses most of the intelligence base sits in the mind of employees.
“Ask any question of your company, and there is a colleague with expertise that can answer it. Now all we need is an AI-powered expertise map,” he adds.
Yao argues that the banking and insurance industries must ensure that generative AI’s risks – hallucinations, breach of privacy, increased cybersecurity risks – are well managed.
She concludes: “While techniques are being developed to combat these harms, a foolproof solution is not yet available. However, such known risks have not stopped innovation in banking and insurance, where companies continue to experiment with generative AI.”
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