Risk Reducing AI Use Cases for Financial Institutions

In capital markets, GenAI is revolutionizing trading, risk management and compliance. Financial institutions are exploring the potential of generative AI to enhance their operations while navigating a regulatory landscape that emphasizes caution and due diligence. Regulatory bodies are concerned with the ethical implications, transparency, and accountability of AI systems. As such, financial institutions must balance innovation with regulatory compliance, ensuring that AI applications are transparent, auditable, consistent, and align with existing legal frameworks. The current atmosphere reflects a cautious optimism, with institutions actively seeking ways to harness AI’s benefits while mitigating potential risks.

GlobalData finds that 70% of insiders believe that Generative AI will have a positive impact on the banking industry in the next three years. Having developed a greater understanding of AI since its rapid emergence over the past few years, banks are increasingly finding valuable use cases for the technology, most notably improving customer experiences and fraud detection. This acknowledgment of AI’s limitations dovetails with the broader landscape of challenges that banks face, including cultural resistance and strategic alignment.

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For example, GenAI has the potential to support the hyper-personalization of offerings, which helps drive customer satisfaction and retention, and higher levels of confidence. Acquisitions and joint venture opportunities can help banks build new or enhance existing GenAI-focused ecosystems and deliver new products and solutions more quickly. The business case for such deals should be based on a careful assessment of capabilities and with results from initial use cases. Given the newness of GenAI and the limited tech capabilities of many banks, acquisitions or partnerships may be necessary to access the necessary skills and resources. GenAI’s ability to work with unstructured data makes it easier to connect and share data with third parties via ecosystems. Half (51%) of banks said they prefer partnerships as their go-to-market approach for GenAI use cases, as opposed to in-house development.

In addition, building “knowledge graphs” from existing institutional expertise will allow GenAI to extract valuable insight. Over time, banks should develop a comprehensive vision for the business, incorporating the full innovation portfolio and be ready to pivot in an agile way as AI technology continues to evolve rapidly. The aged, heavily-customized technology architectures in place at many banks today, with all their workarounds and poor data flows, are a barrier to AI implementation.

The dual nature of AI in cybersecurity, the ethical dilemmas posed by AI-driven decisions, and the imperative for data privacy underscore the need for a balanced approach. By investing in talent development, fostering research and innovation, and cultivating strategic partnerships, the banking sector can mitigate generative ai use cases in banking these challenges and seize the moment to redefine financial services. In consumer banking, it elevates service delivery and customer interaction, investment banking sees more streamlined research and financial modeling, while corporate and SMB banking benefits from enhanced business lending and risk management.

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In addition, references should be provided to the material that was used for producing outputs. Financial institutions face a complex regulatory environment that demands robust compliance mechanisms. The integration of generative AI, particularly LLMs, offers transformative potential to automate compliance processes, detect anomalies, and provide comprehensive insights into regulatory requirements. TUATARA also helped leading cooperative bank BS Brodnica continue to challenge the status quo in customer service. The organization, which was one of the first cooperative banks in Poland to offer digital banking services, looked to harness AI automation to give its customers access to instant, high-quality support.

• “It enables executives to get information in a comprehensive way faster, which allows you to make your decisions faster and quickly move toward execution,” Donahue said.
• These are the puzzles that chief information officers, chief technology officers, and data leaders who oversee their firms’ AI strategies are expected to solve.
• Schumer emphasized that the regulations should focus on protecting workers, national security, copyright issues and protection from doomsday scenarios.
• Among the use cases for gen AI at Bank of America outlined by Bajwa is improving developer efficiency and productivity within the bank’s large engineering organization of more than 10,000 developers.
• Similarly, many banks have been pursuing industry verticalization and deposit retention strategies, as well as seeking new and diversified revenue streams.
• This is a significant departure from traditional methods of drug development, which are often slow, expensive, and fraught with failure.

Editors would then need to write additional content to flesh out the articles, pushing the search for unique sources of information lower on their list of priorities. In past automation-fueled labor fears, machines would automate tedious, repetitive work. GenAI is different in that it automates creative tasks such as writing, coding and even music making. For example, musician Paul McCartney used AI to partially generate his late bandmate John Lennon’s voice to create a posthumous Beatles song. In this case, mimicking a voice worked to the musician’s benefit, but that might not always be the case. Member firms of the KPMG network of independent firms are affiliated with KPMG International.

There is no question that generative AI will disrupt many banking processes and how banks interact with their customers. However, if the technology is deployed in smart ways, it will allow banks to serve customers better while also improving their economics. A recent Bain & Company survey of banks indicated that over 80% of respondents plan to upgrade their data architecture in the next three years.

“These are big legacy organizations that have a lot of data, a wide range of potential use cases and money to spend on compute power,” Mousavizadeh said. AI is transforming customer service through chatbots and virtual assistants, providing personalized and efficient client engagement. These AI systems can handle a wide array of queries, from account information to complex financial advice. Model benchmarking provides a standardized approach to evaluating AI performance, ensuring that models meet regulatory and operational standards. Documentation involves maintaining detailed records of model development, training, validation, and deployment processes. LLMs like Granite from IBM, GPT-4 from OpenAI, are designed to intake and generate human-like text based on large datasets.

At BBVA, we want to further promote our role as pioneers when it comes to innovating in financial services and we are therefore firmly committed to exploring the potential of this technology. We believe that generative AI, when used safely and responsibly, is a game-changer in how we support our customers in their decisions and offer personalized services. It also happens to stimulate creativity among our employees,” explains Ricardo Martín Manjón, Global Head of Data at BBVA. Data and technology are the key levers of transformation at BBVA, which for over a decade has been running specific development centers for advanced analytics and artificial intelligence, now known as AI Factories, in Spain, Mexico and Türkiye.

Information technology

Financial institutions have been pushing forward a more general level of digitisation across functions, apart from cutting-edge technology developments such as AI. At the same time, he also noted that as timing and pace of a rate cut remain uncertain, banks should plan their strategies accordingly. Treasury outlook from the Oversea-Chinese Banking Corporation (OCBC) pointed out that as recent inflation readings had boosted the Fed’s confidence on bringing down inflation, rate-cut odds shifted to the dovish side. Bank of America (BofA) is forecasting a first rate cut in December, despite a growing possibility of an additional one in September.

These include tokenization, virtual products and digital wallets, electronic transactions, straight-through transaction processing and product accounting, as well as sophisticated cloud-based risk and financial crime detection models. As the banking industry increasingly moves towards digitisation, the adoption of advanced AI technologies becomes crucial. GenAI, with its ability to synthesise and generate content, offers unparalleled opportunities to automate complex processes, provide ChatGPT personalised customer experiences, and strengthen security measures. It’s where the productivity gains get to a point where you can start to do things you never thought possible. With genAI and a host of other complementary technologies applied, one could theoretically start to run a continuous close. Hook some visualization tools up to that data, and CEOs and decision-makers could tap into a real-time dashboard of key financial, compliance, risk and cost metrics, for example.

Artificial intelligence (AI) will undoubtedly be the most transformative technological force for businesses in the coming years. Bank of America‘s virtual financial assistance service, Erica, has seen considerable use since its launch in 2018. The service has recorded over 2 billion interactions, assisting ChatGPT App 42 million customers. The first billion interactions took four years, but the second billion were achieved in just 18 months, indicating a significant increase in client engagement. Erica has handled over 800 million enquiries, providing personalised insights and guidance over 1.2 billion times.

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In cases like this, where generative AI is taking on repetitive, boring tasks, banks could get productivity gains of around 20%, Abbott estimates. “You can take the Fannie and Freddie mortgage underwriting policies and tell a large language model to act like a loan underwriter and look for all the red flags against the policies that might be in a loan,” he said. “It’ll take in all the documentation from the loan, the policy, and start looking for those red flags. There’s still a human in the loop, because you have to be assured from a model risk management perspective that you’re doing the right thing.” The report noted that call center agents are typically treated rudely by irritated customers. “Top workers are generally not paid for their contributions to the training data that AI systems use to capture and disseminate their skills,” the report noted. “Yet, without these contributions, AI systems may be less effective in learning to resolve new problems. Our work therefore raises questions about how workers should be compensated for the data they provide to AI systems.”

Swamy and Jermyn are two of the thought leaders on the AI 100 list, which was curated by data scientists at H2O.ai (an AI software company) and Evident (an AI research firm). An emerging challenge for Wall Street firms now is closing the gap between the staff and the technology, and some firms are finding a “bit of friction” with adoption, Accenture’s Smith said. It’s a “lack of available use cases rather than a deliberate decision not to,” a fundamental analyst at one of the world’s biggest hedge funds told BI.

Ensuring that their AI systems do not violate privacy, prevent bias from creeping in, and remain secure keeps enterprise CXOs awake at night. The new Generative AI solutions from Temenos enable users to perform natural language queries, generating unique insights and reports swiftly. The technology is transparent and explainable, ensuring that users and regulators can easily verify the results produced. With a robust security framework, these solutions are set to transform banking efficiency, operations, and product management.

They automate routine tasks such as processing documents and verifying information. AI co-pilots – Co-pilots that work alongside employees will streamline workflows and provide new insights, leading to significant productivity improvements. Citizens Bank for example, expects to see up to 20% efficiency gains through gen AI as it automates activities like coding, customer service and fraud detection. In the future, these co-pilots could tailor investment strategies in real-time or predict market trends, helping to fortify FS firms’ competitive edge and deliver differentiated client outcomes. This strategic realignment encompasses not just consumer-centric services but also aims to bolster risk management frameworks, optimize compliance procedures, and drive innovation in product development and financial advisory offerings.

Greater scrutiny demands that banks align themselves with responsible AI practices. While proofs of concept might work initially, the widespread application of use cases requires enhancements consistent with a larger scale, echoing DevOps principles. Generative AI also introduces novel requirements, from API management to vector databases to application hosting. As a result, an ecosystem of vendors tailored to address specific elements of the tech stack enabling AI and machine learning (ML) operations is taking shape. AI operating models can vary by the degree of centralization, particularly when prioritizing use cases and setting ethical standards (see Figure 4).

This ability enables accurate risk assessments, aiding banks in making more informed decisions regarding loan applications, investments and other financial operations. These AI capabilities help banks optimize their financial strategies and protect themselves and their clients. However, as we embrace AI’s opportunities, we must also navigate its challenges with foresight and responsibility.

At Man Group, a machine-learning tool can send brokers trades that could offer the best pricing on a specific stock or security based on historical execution data. Bank of America spent $3.8 billion on new technologies last year and is keeping pace this year as it progresses towards its goals of data hygiene for AI. Discover has also taken a measured approach to generative AI, ensuring safeguards are present and training is offered to employees. The development of GenAI extends NLP’s ability to process language content by being able to create new content. “GenAI represents a transformative leap in innovation, particularly in content creation,” he said. AI may be adopted faster by digitally native, cloud-based firms, such as FinTechs and BigTechs, with agile incumbent banks following fast.

In three months, Piotr hit the ground running, taking part in 1,000 conversations over two months. So far, the virtual assistant has achieved a 90% accuracy rate for satisfying support inquiries; a figure that’s expected to rise thanks to built-in learning capabilities. Natarajan says Capital One’s approach is to first understand the various use cases the company can explore with generative AI, then determine what data it can control that goes into the models. From there, Capital One figures out what it can construct to test and learn, as well as mitigate any unforeseen outcomes. To improve productivity and the claims experience, insurers will need to scale up the most promising initiatives.

Addressing the talent issue goes beyond merely employing AI specialists to identifying the groups that will be most affected by this shift and encouraging behavioral changes. Mobilizing change agents at all levels of the organization will help establish a “sponsorship spine” to promote behaviors aligned with the bank’s AI strategy. Recurring costs constitute a greater proportion of the total outlay for simpler setups, whereas more complex deployments require substantial upfront investments that may dwarf ongoing expenditures. Irrespective of the exact use-case scenario, maintenance, including continued LLM API usage, accounts for a significant portion of the cost. Nevertheless, European banks are trying to close the gap on AI adoption, including the sort of generative AI used by ChatGPT. Data-synthesising Gen AI solutions could promise advice unencumbered by emotions or wishful thinking.

Our latest 27th Annual CEO Survey indicated that leaders expect technology including GenAI and Machine Learning (ML) to be the centre of optimising costs, creating new revenue streams and improving the customer experience within their organisations. Middle East CEOs are also optimistic about the financial impact of GenAI, with 63% expecting the adoption of it in their organisation to increase revenue, while 62% said it would increase profitability. In the GCC, enthusiasm is even higher with two thirds expecting revenue increases and a similar number expecting profitability increases. While these statistics cover various industries, the banking sector specifically has been heavily reliant on technology since its inception. Now, they see genAI emerging and are asking themselves (and the rest of the business) how this new and disruptive technology might change their world for the better.

You can foun additiona information about ai customer service and artificial intelligence and NLP. As with any new technology, the advent of GenAI brings about a natural sense of curiosity and adjustment for our employees. We are determined to bring our employees along by focusing on the synergy between human and AI capabilities to leverage GenAI as a co-pilot. AI has been used in the financial industry to detect fraud for decades – an AI model can analyze thousands or even millions of transactions at a speed humans could never match. Generative AI is starting to be used to better understand fraud schemes – for instance, JPMorgan Chase uses generative AI to detect business email compromise attacks. A report from Accenture Research found that capital-markets roles are ripe for AI-related job displacement.

By analyzing large volumes of data and detecting patterns, anomalies, and correlations, fraud prevention officers can effectively identify fraudulent activities that may go unnoticed by manual methods. While Hong Kong currently lacks laws or regulations addressing GenAI, the city’s regulators have been trying to keep up with booming adoption of the technology by issuing non-binding guidelines. Using an AI chatbot to respond to employee searches for content in policies or about bank product offerings.

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The small robot must save fellow bots from danger, totaling 300 bots to rescue throughout the game. Reality Blurb was created to bring readers the latest and up to date reality TV news, updates and exclusive interviews. We cover an array of reality shows as well as reality television stars. The Real Housewives of Orange County season 18 airs Thursdays at 9/8c on Bravo.

Lucas, the bot’s creator, charges people £200 (about $256) up front for the right to use the bot, with another £50 subscription fee charged every six months. (Think of it as a sort of Netflix, but purely for buying shoes.) Lucas, however, grants no more than 100 licenses a month, which keeps them a hot commodity. Business logic attacks accounted for 42.6% of attacks on retail sites in the past year, up from 26% the year before. This increase correlates with the growing volume of traffic to retail sites from APIs, which accounted for 45.8% of traffic in the past year, up from 41.6% the year before. Hiding from the clothes websites that you’re using a bot is a bit more complicated; companies will likely ban you if they suspect you’re scraping their website.

These bot shoppers are every sneakerhead’s nightmare

“We are, as humans, biologically built to value stuff that there’s not much of,” he says. I certainly felt that pull, when I was doggedly trying to snag a PS5 by training my brain to hear the Discord sound. Semiconductor manufacturing stalled as lockdowns kept workers off assembly lines, particularly in Taiwan, the global hub of chip production.

It reveals 47% of respondents believe bots have stopped them getting in-demand goods and services online. Many of those affected (58%) were trying to buy tickets for a live event, but buyers of fashion items (35%), consumer goods (39%) and travel (20%) also suspected high levels of interference. You can foun additiona information about ai customer service and artificial intelligence and NLP. State Reps. Mike McFall and Graham Filler today introduced a bipartisan plan to combat the rampant use of automated bots in online ticket sales.

While we have seen celebrities such as Taylor Swift and Ed Sheeran take a stand against scalper bot activity, legislative change is slow and there is a need for businesses to act now. Netacea’s research discovered that 26% of 18 – 35-year-olds admit they have resorted to using a bot in the last year, with a total of 1 in 6 Americans stating that they have used a bot. Criminals utilize the resources and tools available to make a quick buck. Whether that’s buying and selling stolen goods for a vast markup, laundering dirty money, or hacking accounts for their valuable personal information.

Given how inexpensively and easily they can obtain stolen customer accounts online in marketplaces and private Discord and Telegram communities, they can make enormous profits, he explained. Many companies still rely on ineffective anti-bot defenses that cannot detect automated abuse against their customers’ account login,” he said. Bot attackers can also take over consumer accounts on e-commerce sites and create false accounts to send purchases to their own addresses. Jain is familiar with such practices from his time working at eBay validating user identity and handling risk and trust assessments for that commerce platform. The concept of automating online purchases has not gone away, according to Ashish Jain, CPO/CTO at Arkose Labs. Although automating bulk purchases using bots is not illegal [in certain jurisdictions], some attackers use them to obtain consumers’ credentials to carry out fraudulent purchases.

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So observed John Breyault, the vice president of public policy, telecommunications, and fraud at the consumer advocacy-focused National Consumers League, over email. In many cases, bots are built by former sneakerheads and self-taught developers who make a killing from their products. Insider has spoken to three different developers who have created popular sneaker bots in the market, all without formal coding experience. State lawmakers want to crack down on individuals using automated software programs, or bots, to snag concert tickets and drive prices for highly sought-after performers.

Lockdowns also kept people inside, where they needed things like

laptops

and monitors to work, or took time to order

refrigerators

and freezers to stock up on food. According to the new study by researchers at Ohio State University, ChatGPT consumers don’t always want to talk to a real person when they’re shopping online. A 12-month program focused on applying the tools of modern data science, optimization and machine learning to solve real-world business problems.

For example, “data center”proxies make it appear as though the user is accessing the website from a large company or corporation while a “residential proxy” is traced back to an alternate home address. Whichever type you use, proxies are an important part of setting up a bot. In some cases, like when a website has very strong anti-botting software, it is better not to even use a bot at all. While bots are relatively widespread among the sneaker reselling community, they are not simple to use by any means. Insider spoke to teen reseller Leon Chen who has purchased four bots. He outlined the basics of using bots to grow a reselling business.

• Belugas are a specific colorway of the Yeezy 350 Boost from Adidas, one of the most sought after sneakers today.
• The sale price for a new pair of vintage “Chicago OG” Air Jordan 1s from 1985 went from $3,000 in 2017 to $7,500 in May 2020 to $19,000 in February, according to StockX.
• Built on a vast network of API connections and third-party dependencies, online retailers are increasingly vulnerable to business logic abuse and client-side attacks.
• But, of course, it’s not just T-shirts; it’s keychains, Mophie battery packs, New York City Metro­Cards, ramen noodle bowls, sleeping bags, even 18-inch steel crowbars with “Shit happens” etched on the handle.

In our first 24 hours we had over 500 checkouts of Switches,” a representative for Phantom told Motherboard in an email. Admins for Scottbot and Swift did not respond to a request for comment. There’s hundreds of people with bots that are running for Switches, Oculus, and Webcams,” one moderator of the community said in the Discord group chat. Adidas America brand director Simon Atkins told me it’s a constant struggle to keep bots out of the company’s systems. New bots are developed constantly and can often be found on dedicated subreddits, Twitter, online sneaker forums, and YouTube. But Alex says his biggest competition are the manufacturers themselves.

Desperate consumers are driven to unofficial secondary marketplaces to buy the desired ticket, clothes or consoles for a sum that vastly exceeds RRP, despite 91% of people fearing that their payment details may be stolen when doing so. So, if you’re having problems landing a PS5 or Xbox Series X, blaming bots is not as conspiratorial ChatGPT App as you might imagine. They are real, they are legion and they are getting consoles before you. Sometimes for real, desperate customers who are fighting fire with fire to get a unit for themselves, but often for resellers looking to make a profit, which is why 3,500 PS5s can land in the lap of a single scalper group.

The people behind the technology

This, in turn, damages the brand reputation and customer loyalty, and contributes to a negative perception of the industry. Customers with negative experiences with online ticket purchasing and ticket scalping are less likely to attend future events, reducing repeat business and long-term loyalty. For instance, one Twitter account called @Table_of_Chefs sells memberships to participate in bot purchases of PS5s and other popular products. These software programs are coded to purchase in-demand products as soon as they go on sale, completing the transaction far faster than is physically possible for a human. Bots have long been prevalent in the sneaker industry, given the high resale value of coveted shoe releases, but programmers have been expanding to target other products and services. That includes tech releases and even grocery delivery slots for services like Instacart — a serious issue given the surge in demand for food deliveries amid the ongoing coronavirus pandemic.

It’s been typical to see bots target big shopping events like Black Friday. Before the pandemic, they were growing in popularity as a result of the retail industry’s increasing reliance on hype and limited stocks. “We are seeing more and more hard sales recently, with limited stock,” says Benjamin Fabre, CTO of DataDome, a cybersecurity company.

Sierra Greenslade was one of the anxious fans watching the ticket debacle unfold on social media while her friend waited in the ticket queue. After several hours of waiting, they managed to get tickets to one of the Arlington shows. “In the past, these bots would be bots for purchasing online in the hands of specific hackers that know their stuff,” Zioni said. “But now it’s a prolific business to release it or sell it for others to use.” And — surprise — during the same month, the people at Akamai saw one of the year’s highest rates of bot activity.

The 2020 law — passed after roughly six years of debate — repealed a state ban that was rarely enforced and left the door open to bad actor ticket scalpers who never had a ticket in the first place. At first, he created Bird Bot for him and his friends to purchase Nintendo Switch consoles during the quarantine shortage. But then he put it on GitHub, where software developers upload and share each other’s creations.

Lansing — Michigan lawmakers on Wednesday introduced bills to crack down on the use of automated software programs snarling concert ticket sales and driving up prices for big name performers. When most people think of bots, they think of sophisticated programmers working behind the scenes with a custom bot designed to bypass Ticketmaster’s bot checks. The reality is that Bots as a Service (BaaS) means you can buy a Ticketmaster bot for as little as $50 that allows you reserve multiple tickets and potentially bypassing household limits.

Shoppers beware: ‘Grinch bots’ are a holiday shopping problem

Since July, bad bot attacks on retail sites have increased 14% with most attacks occurring on US-based ecommerce sites, followed by sites in France. The rise of automated attacks are likely to continue through Black Friday and Cyber Monday. Grinch bots could again be involved in the disruption of holiday sales events and limited product launches. The eCommerce industry remains a lucrative target for cybercriminals due to its vast network of API connections and third-party dependencies. Cybercriminals are motivated to compromise user accounts for personal data and payment information and a successful security incident can lead to higher infrastructure and support costs, degraded online services, and customer churn. Although these security risks are persistent throughout the year, attacks often peak during the holiday shopping season when there is greater online traffic.

According to Hansen, scalping is a profitable business that has existed since the 1800s. As more online scalpers transition to using automated tools, the scope of the problem is growing. Scalping bots are cheap, easy to run and customize, and provide a high return on investment for scalpers.

Queuing for ticket sales, online or in person, would seem like a fair way to sell high-demand tickets to fans. “Many retailers are working very hard to allow their loyal customers to buy these limited inventory items as opposed to have bot operators hoover them all up and resell on third-party marketplaces,” Sullivan of Akamai added. Bird Bot fits into this space, performing many of the same tasks as a sneaker bot, but for Switches from Walmart and Best Buy.

“I tweeted it out, got a bunch of likes and retweets, made a Discord group for it,” Nate said. Ahead of a special release, the New Balance 990v3 to celebrate Bodega’s 15th anniversary, the boutique and Shopify had devised a few obstacles to slow the bots down. The first was to place the product on a brand-new website with an unguessable address — analogwebsitewrittenonpaper.com. “While they have to act like they’re trying to stop bots, it’s making them a huge profit,” he said.

At about $300, AIY Solutions bots are among the most expensive consumer sneaker bots. Comparable bots like NikeSlayer and Better Nike Bot start at $150 and $200, respectively. Half of New Yorkers plan to spend under $500 for their holiday shopping, and 70 percent said they plan to do at least some shopping online, the poll found. There’s no real way to directly prevent the groups from skirting purchasing limits.

That seems to be the thinking of a coalition of U.S. lawmakers who, on Monday, reintroduced proposed legislation seeking to prevent automated bot accounts from dominating online sales. Dubbed the Stopping Grinch Bots Act, the measure aims to prevent what are in effect scalpers for physical goods ahead of the holiday season. When sneakers are released in limited quantities, it’s often a race to see which sneakerheads can input their credit card information on a website or app the fastest in order to checkout before the product sells out. Bots are specifically designed to make this process instantaneous, offering users a leg-up over other buyers looking to complete transactions manually.