The Impact of AI on Banking and Financial Services: Opportunities and Risks in ASEAN and Global Markets

AI and Emerging Risks to Banking and Financial Services in ASEAN and other frontline markets

This blog is based on an article co-authored along with Matthew Lamons, CEO of The Intelligence Factory and is an edited version of the same article. As a matter of introduction and context, we work closely together to enable strategic decisioning and risk mitigation through AI. We felt that the current global risk situation requires far more attention as to how AI and related data science capabilities can help reduce risks to banking in this part of the world. Since we wrote the original article(https://open.substack.com/pub/kaustuv/p/confronting-the-emerging-risks-to?r=9c5n&utm_campaign=post&utm_medium=web), Nikkei has published about the matter, validating our views. Here is a link to the Nikkei article, but you may need to subscribe and get beyond the paywall. Indonesian cyberattack signals growing threat in Southeast Asia - Nikkei Asia. Recent cyberattacks on Indonesia by the Lock Bit group are mentioned as is the lack of cyber readiness in the wider region. Data back-up is a key concern. We see proactive signalling, end-point security and scenario simulation as key requirements. Emerging Risks to Banking in a Strategic Region The digital age has transformed the banking sector, bringing both unprecedented convenience and equally unprecedented risks. As financial institutions increasingly rely on technology to manage transactions, store data, and engage with customers, they also become prime targets for cyberattacks. Recent high-profile incidents, such as the ransomware attack on Evolve Bank & Trust by the Russian hacker group Lock Bit, underscore the growing sophistication and frequency of these threats. It is natural for payment infrastructure services and providers of advanced AI-based cybersecurity providers to align and help secure the transactional economy. ASEAN is at the heart of the Indo-Pacific region. It has a GDP of $3.6 Trillion(2022 estimates, last available in January 2024) and a population in excess of 670 Million. It straddles a key part of the world, sitting between India, China and Australia. The Northernmost part of ASEAN is very close to the Nicobar Islands of India while the Southernmost part is not far away from Australia's Northern Territory and shares the same landmass with the country of Papua New Guinea. The Straits of Malacca is a major shipping channel. The eyes of the world are upon this region. Against this backdrop, it is not surprising that cyber-attacks and cyber espionage constitute a particular concern for governments, industry and people. In this piece, however, we look only at the specific issue of cyber attacks on banking and financial services. The Synapse Incident: A Wake-Up Call The attack on Evolve Bank & Trust, which serves numerous high-profile fintech partners including Mercury, Stripe, and Affirm, has been a stark reminder of the vulnerabilities that even the most advanced financial institutions face. The hackers claimed to have exfiltrated 33 terabytes of sensitive data, including end user Personally Identifiable Information (PII) such as Social Security Numbers, card Primary Account Numbers (PANs), wire transfer details, and settlement files. The breach not only exposed critical data but also highlighted significant deficiencies in Evolve's IT security practices, which had already attracted regulatory scrutiny from the Federal Reserve Board. This incident, coupled with the collapse of Synapse, a once-prominent fintech partner of Evolve, serves as a potent illustration of the cascading risks that can ensue from a single security failure. As banks and their fintech partners are intricately linked, a breach in one entity can reverberate across the entire ecosystem, compromising the integrity and trust upon which financial services depend. The Rise of Real-Time Payments and Open Banking: A Double-Edged Sword The advent of real-time payments and open banking has revolutionized the financial landscape, offering consumers faster and more flexible access to financial services. However, these advancements also introduce new vectors for cyber threats: The Consent Framework in Open Banking and Attendant Risk A consent framework is key to Open Banking being truly what it is called. The interplay between third party service providers, banks and account holders is central to Open Banking. The implications go much deeper than just the transaction itself. A robust framework in practice means that consumers will be able to access multiple service brands from one app, including one bank service app or fintech app. In addition, merchants and service providers will no longer need to go looking for time-consuming tie-ups with multiple banks. APIs will be sufficient for all players within a permitted band of activities and compliance checklists to access a large, universal base of users. The risk intensity is particular when a consumer seeks to use a third-party provider and that provider approaches the consumer's bank for data. This is where particularly sophisticated levels of fraud can play out. It is possible for the permissioning process between the bank and the consumer to be strong and secure. But there needs to be place a process-and tools-that are always able to sense if a third player is a bad actor. Further, it is also possible that another party may be able to take over a session and capture data for it's own purposes. Emerging Online Risks to Financial Institutions The Evolve Bank & Trust incident is just one example in a broader landscape of emerging online risks facing financial institutions. Some of the most pressing threats include: How AI is Transforming Cybersecurity for Financial Institutions To combat these sophisticated threats, financial institutions are increasingly turning to Artificial Intelligence (AI) and Machine Learning (ML). These technologies offer several advantages in enhancing cybersecurity: Practical Applications of AI in Financial Cybersecurity AI-driven cybersecurity solutions are already being implemented across the financial sector, providing tangible benefits: AI-led real-time threat detection, historical trend analysis, and comprehensive compliance reporting are key steps in this matter. By analyzing log files and monitoring user behavior, it is possible to identify and respond to threats quickly and effectively. Complementing this, an immersive 3D visualization and dynamic simulations enable financial institutions to visualize potential threats, simulate various scenarios, and make informed decisions to enhance their security posture. A configurable framework platform that delivers a full digital infrastructure to banks and other financial institutions, inclusive of the above, helps these institutions safeguard their digital assets, maintain regulatory compliance, and build trust with their customers. Leveraging the power of AI and advanced analytics, financial institutions can stay one step ahead of cybercriminals. The recent ransomware attack on Evolve Bank & Trust serves as a stark reminder of the importance of robust cybersecurity measures. In an era where cyber threats are continually evolving, proactive and intelligent cybersecurity solutions are not just an option -- they are a necessity. Fortifying your defenses and ensuring the security and integrity of your financial operations are key to a resilient economy and society.

Banking on GenAI: The artificially intelligent future of finance

Top Indian banks like SBI, HDFC, and Axis adopt GenAI for better services. BFSI forecasts $13.2B IT spending in 2024. Setu, AdvaRisk, Velocity, and Gnani.ai assist in AI-led innovations like fraud detection, chatbots, and Microsoft partnerships. Prioritizing ethical AI, productivity, and human involvement ensures accuracy. Emphasizing UPI digitization enhances overall efficiency.India's large lenders are rewiring through GenAI to improve their customer interface and get a leg up on their younger, disruptive competitors, report Beena Parmar & Annapurna Roy A slew of banks, including the country's largest lender, State Bank of India (SBI), as well as its private sector peers HDFC Bank, Axis Bank and IndusInd Bank, are turning to generative artificial intelligence (GenAI) to radically change the way their services are consumed, leading to ease of use and better engagement with customers. The banking, financial services and insurance (BFSI) sector has been one of the fastest adopters of technology. Large banks and financial institutions are, however, being challenged by smaller players and fintechs. In such a scenario, integrating the front-end as well as the back end may help legacy institutions get a leg up on their younger, disruptive competitors, said experts. "GenAI is a very good tool if it can be used to assist people with knowledge, for productivity or having more meaningful, insightful conversations with customers," said Nitin Chugh, SBI's head of digital banking and transformation. SBI is looking at long-term capabilities while testing use cases in the short-term, starting with assistance. As a first step, it is focusing on doing so internally among its employees. While some banks are deploying customer-facing bots, SBI would probably consider that at a later stage, said Chugh. Overall, IT spending by India's BFSI firms in 2024 is estimated at $13.2 billion, up 12.2% from $11.8 billion in 2023, according to June data from Gartner. Spending on software is projected to increase a record 18.5% year-on-year, a significant jump from 9.6% in 2023 and above the global average, it said. Today, 80% of Indian banking is digitised, making it among the most digitised banking ecosystems in the world given advancements such as Unified Payments Interface (UPI) and 24x7 payments. In May, fintech company Setu, part of the Pine Labs Group, unveiled Sesame, India's first large language model (LLM) specifically designed for the BFSI sector, in collaboration with indigenous AI research firm Sarvam AI. LLMs are AI-based programs trained by huge datasets to understand text and human language. Setu's co-founder Nikhil Kumar called it a "ChatGPT moment" in financial services. Similarly, fintech players such as financial fraud detection startup AdvaRisk, funded by ICICI Bank and other investors; four-year old cash flow-based financing platform Velocity, financed by Peter Thiel's Valar Ventures; and Samsung-backed customer service automation startup Gnani.ai, are helping banks improve core business with the help of data. "Broadly, I see financial institutions working on proof of concepts, small pilots using fine-tuned open source LLMs in their owned infrastructure and work towards industrialising these solutions," Ramesh Lakshminarayanan, chief information officer, HDFC Bank, told ET. HDFC Bank, India's largest private bank by revenue, currently has a proof of concept to help coders code faster. It is also looking to use LLMs to interpret key data repositories like statements and provide meaningful analysis to relationship managers, phone agents and other sales and service professionals. Technology firm Microsoft is working with Axis Bank and Aditya Birla Capital, among others, to deploy processes using GenAI to transform contact centres, boost sales and overhaul claims and underwriting processes. "GenAI is reshaping the way we operate," said Sonali Kulkarni, BFSI lead, Microsoft India. Building on GenAI Companies are increasingly using chatbots and data to improve their customer service calls. They are also relying on the new-age technology to speed up resolution, analyse statements and balance sheets, read or interpret spending patterns, and to help cross-sell products and services. AI, which has been in use for more than a decade, and GenAI-based systems are also aiding better predictive analysis and efficient decision-making based on data beyond human comprehension. Bank frauds can be spotted within seconds. In customer service, GenAI is helping reduce call volumes, classify complaints, automate and summarise content, train virtual financial consultants and streamline credit approval processes to improve day-to-day activities. Some banks are using in-house data science teams to build use cases or functionalities with existing open-source models, conditioned to their requirements. Newer multimodal models, which are showing much more promise than the text-based LLMs are being explored, said multiple bankers. These models will be the next progression in the coming year which could lead to more cost efficiencies in the next few years, said Avinash Raghavendra, head of IT at Axis Bank. "Pricing and cost models are evolving as well and while still expensive, there are commercial models being made available which makes it more feasible than they were last year. We expect this trend to continue in the coming year... then the need for privately hosted LLMs as a cost reducer might fade," he said. Yet, human intervention will continue for now, said executives. SBI's Chugh said their ethical and responsible AI frameworks would ensure near 100% accuracy in use cases, that they are free of bias and are explainable with a human in the loop. Axis Bank has rolled out chatbots for about 60,000 employees, helping them resolve customer queries within seconds rather than days. Raghavendra said that unlike say a retail company which can put out 90% accurate data, banking needs to be 100% accurate all the time. Training models with correct data is key, and Axis Bank has a dedicated team for this which works on re-documenting information such that the required accuracy is achieved, he said. Guardrails There is no hesitation in the banking sector when it comes to adopting GenAI, whether in private sector, public sector or global banks, Chugh said, even as there are conversations around guardrails and protecting customers. Vivek Bajpeyi, chief risk officer at IndusInd Bank, said that while digitisation and GenAI have enhanced convenience, they come with attendant risks, besides hallucinations and inaccuracies. "Risks elements have changed. Now cybersecurity is also a big challenge. The ability to defraud has increased even as technology is also helping uncover frauds," he said.