Business
The Promise of AI in Financial Services in 2023
Source: Finance Derivatives
By Kevin Levitt, Global Industry Business Development, Financial Services, NVIDIA
As we enter the new year, many are left in a continued state of uncertainty from the unprecedented financial challenges 2022 posed. With high inflation and rising interest rates, financial institutions are more inclined than ever to turn to innovation to address top opportunities: leveraging AI to deliver more value, create relevant customer experiences and drive operational efficiency.
Artificial intelligence (AI) has long been a hot topic of interest in the financial sector, but now as firms are beginning to see its concrete value, it is moving from experiments in the research labs to production deployments across lines of business. AI’s value to financial enterprises will accelerate in 2023, solidifying its well-deserved spot in the technology toolbox of financial institutions.
Real-Time Risk Management
This year’s sudden collapse of cryptocurrency exchange FTX serves as a great example of the speed at which unknown risks can manifest for businesses. Financial firms will advance AI for risk management in 2023 as the importance of real-time risk calculations is more evident than ever. We live in a volatile financial climate where more accurate and immediate asset and risk values are needed to make gametime decisions. Increasingly, firms will turn to accelerated computing to speed price discovery, risk calculations and back testing.
The simulation techniques used to value risk in derivatives trading are computationally intensive and typically consume large swaths of data center space, power and cooling. In 2023, what used to run all night on traditional compute will run over a lunch break or faster on accelerated compute. A real-time value of sensitivities will enable firms to better manage risk and improve the value they deliver to their investors. Firms need to adopt AI and accelerated compute or run the risk of being left behind.
This technology won’t just be used for the capital markets sides of global banks. It will also apply to hedge funds, who will use accelerated compute to train algorithms to discover signals and produce more accurate predictions. They will deploy increasingly larger and complex models in production to capture the market opportunity and improve investor returns.
Cloud-First for Financial Services
In 2023, banks will have a new imperative: get agile fast. Facing increasing competition from non-traditional financial institutions, changing customer expectations rising from their experiences in other industries, and saddled with legacy infrastructure and economic headwinds, banks and other financial institutions will embrace a cloud-first AI approach.
But in the highly regulated financial services industry, some data can’t move to the cloud due to compliance requirements, data sovereignty laws or other international regulations. Banks are also finding some workloads to be cost prohibitive in the cloud, including training Large Language Models (LLMs) that form the foundation of many of a bank’s most important AI applications, from virtual assistants and chatbots to sentiment analysis of earnings calls and monitoring for trading floor compliance.
The industry requires operational resiliency, a term that means your systems can absorb and survive shocks (like a pandemic). To this end, in 2023 banks will look for open, portable, hardened, hybrid solutions – including AI software that operates across on-prem and cloud environments to offer a single pane of glass through which they may manage data science experiments and infrastructure utilization. As more AI applications are deployed into production, banks will be obligated to purchase support agreements for their AI software rather than rely on community-supported, open-source solutions.
Banking on Generative AI
This year, the world witnessed the sensation of ChatGPT from OpenAI, which showcases the power of LLMs and generative AI for a variety of use cases from story writing to writing software code. In 2023, banks will ride this wave to enable a range of applications with LLMs. Generative AI can be used to write emails personalized to an individual customer’s profile or lifestage, help software engineers improve their code, and help marketers create better cross-sell messaging.
As stated earlier, banks will not be able to rely on open-source solutions trained on uncurated corpuses of data like the one used in ChatGPT. They will need reliable frameworks for building, training, and fine-tuning GPU-accelerated speech and natural language understanding (NLU) models. LLMs are also transformer-based, requiring massive compute and data sets to train. Without accelerated computing, banks will incur surprisingly high unbudgeted costs and longer times to value.
Putting a Face to Digital Banking
The chatbot has been a mainstay in the customer service experience across the financial services industry for many years. However, many customers express frustrations with this experience as it can feel cold and disconnected. The problem is that chatbots aren’t empathetic. In 2023, banks will invest further in digital avatars to improve customer experience.
Digital avatars go beyond chatbots and rules to bring eye contact, gestures, and audio to face to customer service interactions. They also leverage LLMs, so the number of questions and tasks they can manage is not limited to pre-written scripts, but still bound by the guardrails dictated by the data scientists use for fine-tuning the models. Digital avatars will change how virtual assistants look and feel, ultimately building trust with bank customers.
New technologies like this promise to make 2023 an exciting year of innovation across the industry. But all of these improvements are built on a foundation of data science, which requires data scientists.
The new State of AI in Financial Services survey report to be released in January shows the number-one challenge financial institutions are facing is hiring and retaining data scientists. To attract these top talents, banks will need to provide them with the accelerated compute necessary to perform their best work and deliver on the promise of these innovations in 2023.
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Business
Overcoming intricacies of premium processing in the insurance industry
Source: Finance Derivative
By Piers Williams, Global Insurance Manager at AutoRek
Complexity is an unavoidable reality for the intricate world of insurance. For program administrators, including brokers, managing general agents (MGAs) and managing general underwriters (MGUs), accurate management of insurance premium payments and complex workflows like bulk payments and diverse data sources is essential – there cannot be room for error. Unfortunately, poorly executed and complex processes can lead to costly mistakes. This is especially true for essential financial control processes that directly impact the performance of insurance businesses such as premium payment processes – also commonly known in corporate industries as account receivable and payable processes.
In particular, the traditional, manual management of insurance premium payments is what can often lead to unresolved outstanding debt and large balances of unallocated cash. When you combine this with the 30% growth in delegated/program businesses (over 30%+ in the last 3 years), using Excel sheets and the ever-increasing policy volumes, the approach becomes unsustainable and inefficient.
This article will outline the transformative benefits automation offers and the key actionable strategies that will enable program administrators to optimise the management of insurance premium payments for greater efficiency and effectiveness in their financial operations.
Embracing automation: the future of insurance
The future of insurance lies in automation – this is where premium payment processing comes in. Automation enables businesses not to erode margins through write-offs but accelerate cash flow and protect revenue. The primary goal is to accelerate premium reconciliation and allocation by implementing an automated straight-through process, minimising the need for human intervention to ensure that minutes – not hours – are spent on the reconciliation process.
By leveraging automated systems and advanced data integration, premium payment processing has the potential to offer a more streamlined, accurate and effective insurance ecosystem. Automation minimises the likelihood of human error and delays in transaction times; ensuring that precision is at the forefront of the financial processes. This shift towards automation addresses one of the key challenges faced by the insurance industry – eliminating inefficiencies which can lead to costly mistakes and unnecessary delays.
Producing scalability in a competitive market
Program administrators are confronted with a multitude of pain points in their day-to-day operations. Given that program administrators handle a significant amount of insurance policies across multiple binders/programs in the market, considerable admin effort is required to process a vast number of internal and external data sources as well as payments and policy data. As a result, program administrators risk losing valuable time and resources – giving them less time for value-added tasks, like resolving breaks, addressing downstream issues, and creating better partnerships with insurance partners.
The impact of such operational inefficiencies can impact not only accounts receivable, collections and credit control processes but also business profitability, binder/program performance, competitiveness and reputation to name a few. Without the adoption of more advanced technologies like automation, program administrators are increasingly at threat of not being able to produce scalability in a competitive market.
Whilst automation offers huge efficiency upside for businesses there are also many benefits delivered by simply having a single premium data control platform. One of the most notable challenges with premium payment operations is the often-large numbers of internal and external data sources that must be managed and processed. This data needs to be continuously processed to ensure reporting is up to date and management has a comprehensive view of outstanding premiums, allocated premium and cash positions at any point in time. The management of this data, if not performed within a platform, presents a huge risk from a control perspective, as often premium payments will not be allocated for 30, 60 or 90 days, therefore needing a solution to keep track of all data automatically to ensure efficiency and control to ensure.
Identifying and addressing inefficient processes
Investing in modern technology like automation is often the first step in streamlining operations and eliminating inefficient processes. The goal is to encourage program administrators to focus less on manual administrative tasks that are time-consuming and instead, focus on key business decision making to improve financial gain – automating manual processes does exactly that.
Likewise, the insurance industry is constantly evolving so the adoption of premium payment processing will be crucial in remaining competitive in a shifting market dynamic. With this in mind, legacy systems, once the backbone of insurance operations, must go. These systems are outdated and unable to meet the demands of a data-driven, regulated market, leading businesses to embrace digital transformation and no longer depend on inefficient processes.
Business
Who’s Scared of Embedded Payments?
Source: Finance Derivative
Johannes Kolbeinsson, CEO at PAYSTRAX
Embedded payments have been swiftly integrated into the e-commerce ecosystem, showcasing their transformative potential in reshaping how we make transactions. There is a bright future for embedded payments, but we must emphasise the significant untapped potential within the space as it currently stands, as the user experience still isn’t quite seamless, and third-party payment processors still present a fraud risk to companies.
A Rapidly Expanding Market
The growth of embedded payments is undeniable. Driven by the rise of digital wallets and one-click checkout systems, the global market for embedded finance as a whole is projected to grow from $92 billion to $228 billion between 2024 and 2028. Recent shifts in consumer behaviour, especially toward frictionless digital experiences, have been accelerating the adoption of these solutions across sectors. Embedded payments offer that seamless one system approach, not only quickly processing payments on app, but building a one app relationship with consumers that develops brand loyalty.
This trend directly mirrors the business strategies of the major players in the tech world. Companies such as Apple, with its mobile wallet and credit card ventures, and Shopify, combining e-commerce with embedded payments, have demonstrated that blending payments directly into platforms can drive user engagement and boost conversions. The logic is plain and simple: by keeping consumers within the app, businesses streamline the purchasing process, increasing the likelihood of finalising transactions, and building brand and customer loyalty.
The Embedded Payments Boom
Embedded payments have become the latest hot topic in fintech. In fact, just a few years ago, in 2020, embedded finance payments were generating around $16 billion in revenue. Looking ahead to next year, forecasts suggest that number will skyrocket to over $140 billion. The success of platforms like Uber with one-click payments and the buy-now-pay-later (BNPL) models from companies like Klarna are clear indicators of this shift. Consumers increasingly seek ease and convenience, and embedded payments are meeting those demands head-on.
However, for all the excitement, embedded payments still face challenges in adoption. Fraud prevention, authentication, and user experience remain key barriers that need to be addressed on an industry wide level to truly deliver the seamless, instant payments these systems promise consumers.
Addressing the Friction
While the promise of embedded payments is enticing, friction remains. One of the most critical challenges for businesses adopting embedded payments is ensuring robust risk management. Creating an online experience that feels as secure as an in-store transaction should be a top priority, especially as financial fraud becomes more prevalent.
Currently, many companies are jumping into embedded payments without fully understanding the complexities involved. The lack of in-house expertise in building the necessary infrastructure across digital services, transaction processing, and enablement layers can lead to implementation issues and security vulnerabilities. Businesses need to conduct proper due diligence to avoid potential pitfalls, as hasty implementations can compromise both functionality and security.
User experience is another key factor in determining the success of embedded payments. Historically, we’ve seen how PayPal revolutionised online payments with its email-and-password system, setting a new standard. Embedded payments, while advanced, are still evolving to achieve a truly frictionless experience. Authentication processes frequently occur outside of the platform or app, and the range of payment options can be limited. To fully realise the potential of embedded payments, businesses must balance security, usability, and convenience.
Trust and Security Concerns
Security and trust are paramount when it comes to anything finance related, and these are areas where embedded payments must improve to gain widespread consumer adoption. With growing concerns about data privacy and the rise in online fraud (40% of all reported crime in the UK last year were fraud), it’s clear that consumers need reassurance before embracing embedded payments.
While embedded payment systems offer unparalleled convenience, their inherent vulnerabilities could make them a prime target for cybercriminals. The lack of standardisation and regulation in the sector, coupled with a general shortage of expertise that comes with a new industry, poses significant risks for users. Nevertheless, history suggests that consumers are willing to trust new technologies over time. Just a decade ago, saving card details online was met with hesitation; today, it’s commonplace. Similarly, as security concerns are addressed, embedded payments will likely gain traction as consumer trust grows.
The Path Ahead for Embedded Payments
Despite the array of payment methods available today, the potential for embedded payments to dominate the future of finance is undeniable. Their speed, ease, and ability to facilitate in-app purchases with a simple click make them an attractive option for both consumers and businesses.
Yet, for embedded payments to live up to their promise, key challenges remain. User experience and authentication are the primary obstacles. Truly embedded payments should enable users to complete transactions within the app, without being redirected elsewhere for authentication. As instant payments become the norm, any requirement to leave an app to verify a purchase could deter adoption. Addressing these issues will be critical to the future success of embedded payments as they continue to evolve and reshape the digital landscape.
In the coming years, as innovations like AI-driven fraud detection and biometric authentication become more integrated, the potential for embedded payments to achieve a truly seamless experience will grow. This could be the defining shift that cements embedded payments as the default mode of financial transactions in our increasingly digital world.
Business
The need for speed: Why fintechs must supercharge background checks to stay competitive
Source: Finance Derivative
By Luke Shipley, Chief Executive Officer and co-founder at Zinc
In the fast-paced world of finance, and particularly where finance and technology intersect, hiring candidates with the right skills is crucial for staying ahead of the competition. For fintech firms, conducting fast yet thorough background checks is key to balancing regulatory compliance with the need for speed.
However, financial regulations in the UK demand rigorous oversight to safeguard consumer data, prevent fraud, and maintain financial stability. As part of these regulations, fintech companies must conduct thorough background checks to ensure new hires align with compliance standards, mitigating risks to both the company and its customers. These checks involve verifying critical information such as financial history, credit reports, criminal records and employment history, which are essential for determining the suitability of candidates handling sensitive financial data. These checks are both time-consuming and resource-intensive, slowing down the hiring process.
Fintech firms can sustain rapid growth and meet regulatory obligations without sacrificing operational efficiency by streamlining this crucial part of the hiring process with the right tools. This also enables HR teams to focus on creating a positive experience for new hires, rather than burdening them with additional administrative tasks. Implementing efficient systems that reduce these checks from weeks to days allows companies to swiftly onboard talent, maintain customer trust, and stay competitive.
Challenges of traditional background checks
Traditional background checks in the fintech industry are complex and time-consuming due to the stringent regulatory requirements that financial organisations must follow. Verifying candidates’ financial history, running credit reports, conducting Disclosure and Barring Service (DBS) checks, and confirming employment history for the past several years are all critical tasks. These checks are not only meticulous but also require coordination with external agencies, which often slows down the process.
Manual handling of these background checks can extend the hiring timeline by weeks or even months, creating operational inefficiencies for fintech companies that need to scale quickly in a competitive industry. Prolonged hiring cycles can also lead to delays in onboarding vital talent, putting added pressure on already stretched teams.
For HR departments, managing these extensive checks manually places a heavy administrative burden. The time spent gathering documentation, verifying information, and coordinating with third parties diverts HR professionals from focusing on more strategic initiatives, such as talent acquisition and improving the candidate experience. As a result, the manual process not only hinders recruitment efficiency but also affects the company’s ability to attract top talent in a timely manner.
Role of technology in streamlining background checks
Here, technology plays a crucial role as it revolutionises the background check process in fintech by reducing manual interventions and simplifying time-consuming tasks. Automated platform systems now handle complex steps like identity verification, credit checks, and employment history validations far more efficiently than traditional methods. These technologies not only speed up the process but also provide one centralised place for employee documentation and improve accuracy by reducing the risk of human error in verifying critical information.
Automation also allows fintech companies to complete thorough background checks in a fraction of the time, continuing to ensure global compliance without delaying the hiring process. HR teams are freed from the burden of manual data gathering by automating repetitive tasks and reminder emails so they can focus on higher-value activities, such as candidate engagement and talent strategy.
Moreover, integrating background check platforms with existing HR systems streamlines recruitment workflows. This integration ensures a seamless transfer of data, and provides real-time updates on the status of each candidate’s background check. The result is a faster, more efficient hiring process that allows fintech firms to onboard new employees quickly, creating a positive reflection of their brand at every stage of the onboarding process.
Improved candidate experience
Technology in recruitment not only benefits HR teams but also significantly enhances the candidate experience. Automated systems cut down lengthy waiting periods, helping candidates move through the hiring process more swiftly.
From digital applications to real-time status updates, candidates enjoy a seamless, transparent process, which minimises stress and uncertainty. This streamlined approach improves communication and ensures that candidates are informed at every stage of their check progress, fostering trust and keeping them engaged. Additionally, modern tools like AI-driven assessments or automated interview scheduling save time, allowing candidates to focus on showcasing their skills rather than dealing with logistical hassles. Fintech companies can improve their overall employer branding by providing a more efficient and organised hiring process, attracting top talent who appreciate a modern and tech-forward experience.
It is why speeding up background checks is crucial for fintech companies aiming to stay competitive. By leveraging modern technology, these companies can benefit from greater efficiency, regulatory adherence, and an enhanced candidate experience. Fintech firms should embrace tech-driven solutions to balance speed and regulatory requirements, ensuring a smooth, transparent, and efficient hiring process.