FinServ Forecast 2024: SAS unveils 12 key technology & trend predictions
As in other industries, the explosion of generative AI has forced the financial services sector to quickly adapt while riding a wave of regulatory and ethical questions. How will banks, insurers and other financial firms balance the risks and rewards of GenAI and other transformative tech in the year ahead? Experts from AI and analytics leader SAS foresee a mix of successes and failures as the industry sprints to meet consumer and stakeholder expectations.
Bank failures spur a risk management reckoning
“2024 will bring more bank failures, forcing banks to recognize the most important question in risk management: ‘What is our own probability of default?’ And they will deploy tools and technologies to answer that existential question. A recent survey of risk professionals revealed that 80% of firms are eyeing significant improvements to their asset liability management [ALM] functions. Yet less than a third said their firms have fully automated data sharing between ALM and other risk or business functions. It’s time to change that.”
– Donald van Deventer, Managing Director of Risk Research and Quantitative Solutions, SAS
GenAI-induced ‘Dark Age of Fraud’ propels anti-fraud advances
“Even as consumers signal increased fraud vigilance, generative AI and deepfake technology are helping fraudsters hone their multitrillion-dollar craft. Phishing messages are more polished. Imitation websites look stunningly legitimate. A crook can clone a voice with $5 and a few seconds of audio using simple online tools. We are entering the Dark Age of Fraud, where banks and credit unions will scramble to make up for lost time in AI adoption – incentivized, no doubt, by regulatory shifts forcing financial firms to assume greater liability for soaring APP [authorized push payments] scams and other frauds.”
– Stu Bradley, Senior Vice President of Risk, Fraud and Compliance Solutions, SAS
Insurers confront climate risk, aided by AI
“After decades of anticipation, climate change has transformed from speculative menace to genuine threat. Global insured losses from natural disasters surpassed $130 billion in 2022, and insurers worldwide are feeling the squeeze. US insurers, for example, are under scrutiny for raising premiums and withdrawing from hard-hit states like California and Florida, leaving tens of millions of consumers in the lurch. To survive this crisis, insurers will increasingly adopt AI to tap the potential of their immense data stores to shore up liquidity and be competitive. Beyond the gains they realize in dynamic premium pricing and risk assessment, AI will help them automate and enhance claims processing, fraud detection, customer service and more.”
– Troy Haines, Senior Vice President of Risk Research and Quantitative Solutions, SAS
AI transforms financial crimes compliance
“AI will be a game changer for anti-money laundering [AML] programs, as the global cost of compliance reaches $274 billion, 60% of which is labour. As much as $2 trillion is laundered worldwide annually, according to the United Nations. Only 1% of the criminal proceeds are confiscated, and 95% of alerts are false positives. These are alarming figures! Augmenting current AML systems with machine learning and network analytics would improve transaction monitoring dramatically by reducing false-negative and false-positive rates and sending higher-quality alerts downstream to AML investigators and compliance groups.”
– Joan McGowan, Global Banking Industry Advisor, SAS
Deliberate AI deployment makes or breaks insurers
“In 2024, one of the top 100 global insurers will go out of business as a consequence of deploying generative AI too quickly. Right now, insurers are rolling out autonomous systems at breakneck speed, with no tailoring to their business models. They’re hoping that using AI to crunch through claims quickly will offset the last few years of poor business results. But after 2023’s layoffs, remaining staff will be spread too thin to enact the necessary oversight to deploy AI ethically and at scale. The myth of AI as a cure-all will trigger tens of thousands of faulty business decisions that will lead to a corporate collapse, which may irreparably damage consumer and regulator trust.”
– Franklin Manchester, Global Insurance Strategic Advisor, SAS
Central bank digital currencies bring benefits and risks
“Central bank digital currencies [CBDCs], like Nigeria’s eNAIRA, are currently being explored by governments in more than 80 countries. In 2024, they’ll become commonplace, offering citizens secure, government-backed digital payments options with the potential to foster greater financial inclusion. But CBDCs will come with unique fraud and financial crime risks, increasing exposure through financial losses and data compromise, account takeover, and exfiltration through mule accounts.”
– Ian Holmes, Global Lead for Enterprise Fraud Solutions, SAS
Generative AI comes of age
“The hype around large language models [LLM] as a panacea will subside, driven by privacy concerns, the potential for legal action and the sheer cost of building and maintaining these architectures. The focus will shift to monetizing LLMs for certain use cases. A select few vendors will provide foundational ‘conversation models,’ while a larger group will help individual firms tune those for their own purposes.”
– Anthony Mancuso, Head of Risk Modeling and Decisioning, SAS
AI prevents recession – for now
“Advances in artificial intelligence and automation will drive productivity gains. The capital-to-labour ratio will rise, further contributing to increased productivity. This impact will be sufficient for most economies to avoid recession, despite rapidly rising defaults and structural unemployment. The picture will be quite different at a sector level, however, where some segments will experience recession-like conditions.”
– Stas Melnikov, Head of Risk Portfolio, SAS
Risk model recalibration tests firms’ capabilities
“Remember how the COVID-19 pandemic prompted better banks to quickly rebuild and deploy their risk decisioning models, while others spent months just gathering data? In 2024, looming recession risks and higher default rates will require banks to adapt with more relevant models, lending policies and forecasts, putting the speed and agility of their IT infrastructures and broader capabilities to the test.”
– Naeem Siddiqi, Senior Advisor for Risk Research and Quantitative Solutions, SAS
Conversational AI brings customer experience to new heights
“Chatbots are nothing new in financial services – but what if you had a chatbot that better mimicked human-to-human interaction? In 2024, the advance of generative AI technology will bring insurers, banks and businesses in other industries closer to that reality. Such advances in conversational AI will play an important role in streamlining client communication. This will help organizations prioritize human assistance for more complex tasks and scenarios, thereby boosting operational efficiency and cost savings.”
– Oana Avramescu, Global Insurance Lead for Risk Research and Quantitative Solutions, SAS
‘Banklessness’ amid the digital banking revolution sparks AI innovation
“In 2024, savvy banks will endeavour to create a more inclusive customer experience [CX] by examining who the digital banking revolution has best served – and who it has left behind. The sharp decline in the number of branches on main streets and in malls has left swathes of accountholders ‘bankless.’ Those who lack digital confidence are challenged to interact with their financial providers online. On the other hand, a quarter of UK customers said they’ll never set foot in a bank branch again, according to a late 2021 survey. Forward-thinking financial institutions will weave AI-powered digital engagement into an enriched ecosystem of branches to enhance connection and seamless CX as a competitive differentiator.”
– Alex Kwiatkowski, Director of Global Financial Services, SAS
AI ‘explainability’ propels fairness and transparency in insurance decisioning
“Could AI ignite an ethical recalibration of the insurance sector? In 2024, we’ll find out. Actuarially justified risk decisions can unintentionally further inequities in historically marginalized groups. Insurers’ AI and machine learning adoption, however, will require them to understand how their models and algorithms render decisions (in premium pricing or claims, for example). This AI explainability has the potential to establish new standards of transparency and fairness throughout the industry.”
– Alena Tsishchanka, EMEA Insurance Practice Leader, SAS
