Hi Steve, welcome to the AiThority Interview Series in 2023. Please tell us about your two decades of tech experience so far. How did you arrive at Mastercard?

My career has had several phases. For the first 10 years or so after graduating, I worked at various – mostly small – independent, software companies and consultancies. My position evolved over the years; I started as a developer before advancing to the role of a software engineering manager and then eventually becoming a CTO.

Next, I worked for Science Foundation Ireland (SF), Ireland’s national science funding agency, where I led our investments in topics such as computer science, data science, software engineering, and artificial intelligence.

In 2014 I started at Mastercard, which is where I still currently work today. Initially, I supported and grew a team called Start Path, an engagement program for innovative startups in the fintech space. A few years later, I joined Mastercard Foundry, the innovation and R&D arm within the company, leading research and development for AI, ML, and now also quantum computing. This July, I was appointed to Mastercard’s first class of Distinguished Engineers, a recognition for select Senior Vice President technical experts as part of the company’s continuing commitment to technology, innovation, and career growth. With this distinction, I continue my work with a focus on artificial intelligence and quantum computing. 

You are in charge of Mastercard R&D’s strategy and execution of AI and ML in new product development efforts. What is the biggest challenge to Digital Transformation in the market you cater to?

Of the many years that I’ve worked in technology – this current period is distinct for the speed and scale of innovation taking place. This dynamism is exciting because we’ve only just scratched the surface of what is possible for businesses and consumers, but with it also comes new challenges for enterprises.

For one – leveraging emerging technologies to build new products and services.

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Part of the equation is to understand and introduce technologies like web3, spatial computing, PETs, and AI/ML, while also maintaining and upgrading legacy systems, and aligning with ever-evolving legislation and regulation governing their application.

AI specifically has been top of mind for our market, especially following the fairly recent explosion of generative AI.  Mastercard has been putting AI to work for years, particularly in our products and solutions across open banking, routing, personalization, and fraud that enhance the safety and security of the payments ecosystem.  Although the step change between AI and generative AI is exponential in terms of what you can do with it, our deep roots in AI have afforded us the capabilities, talent, framework, and partnerships to keep a pulse and execute on emerging technologies.  

As a leader in the payments space, and as with any nascent technology, Mastercard has a responsibility to set the precedent for exploring generative AI responsibly.  We developed an AI governance program and guidelines for our data scientists to minimize risks in AI and best serve our customers, invested in partnerships with key institutions like RIT In Dubai and Howard University, and actively encouraged our employees to safety test and learn. 

What technologies within AI and computing are you interested in?

The idea of being able to control a computer system and anything connected to it through programming has fascinated me since I was a teenager.

Today I’m looking at how AI, mixed reality, spatial computing, and web3 have unlocked an entirely new frontier in technology. We’re likely to see several key trends, such as the rapid increase in computational power, both at the edge and in the cloud, and the tokenization of assets to start to coalesce around some of these new computing paradigms.

For AI, the incredible advances born from generative AI and Large Language Models (LLMs) are also contributing to the transformative period we’re in.

Currently, Mastercard is engaging in test-and-learn with generative AI applications to enhance operational efficiency and improve data quality, aggregation, entity resolution, and categorization.

We’re also using ML for certain models that support our open banking solutions, such as credit scoring, financial management insights, account opening, and payments. It enables us to extract, identify, and classify data quickly and more efficiently than rules-based models alone.

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In the longer term, I’m paying close attention to both quantum computing and AGI. With quantum, I’m tracking developments in both hardware and software, to understand how these new devices will help us to solve ever more complex computational problems, and what use cases will arise in our industry. With AGI, at some stage, we may be looking at the prospect of human-like machines that can solve a wide range of complex tasks at scale. 

In the current analysis, it is reported the global quantum computing (QC) market will be at $900 million. How do you see QC disrupting the digital market in the next couple of years? 

At $900m, quantum computing is still a very small part of the overall computing market.

Over the next few years, we’ll see quantum computers – inclusive of quantum annealers – get progressively more performant, capable, and reliable.

Currently, our best guess is that the earliest use cases in banking and payments will most likely be in the optimization space, with other applications such as machine learning coming later.

Rather than a disruption, it’s more probable that we’ll see quantum technology adopted gradually, across industries and companies, as the technology continues to improve, becomes more usable, and its primary use cases become more evident. 

What steps can young technology professionals take to enhance their proficiency in collaborating effectively with Cloud, Automation, and AI-based tools? 

Nothing beats getting “hands-on-keyboard” experience using these technologies.  One of the amazing benefits that all young tech professionals have today is readily available online learning materials. There are tutorials on YouTube for just about every emerging technology imaginable, and through cloud computing, there’s also access to the resources required to explore those areas. Many cloud and tech companies also offer cheap or free trial accounts to help young developers learn their technologies at little or no cost.

On the Mastercard Developers platform, for example, you’ll find a quick start guide that will walk you through how to create a new project using Mastercard’s APIs, and gain access to the Sandbox environment. So, armed with nothing more than a laptop and an internet connection, people can get access to all the technology they could imagine, even quantum computers!

One of the tried and tested ways to build skills in these areas has been through the open-source community – whether it’s contributing to an existing project that you find interesting or relevant, or starting a personal project that scratches your own itch. 

What are your predictions for AI/ML and other smart technologies heading beyond 2024?

As machine and deep learning evolve, so too will their role within our sector. This past year has been about experimentation. In 2024, we expect generative AI to continue to gradually integrate into business operations and products.

Companies are currently focused on internal generative AI applications, like software development co-pilots, knowledge bots and operational efficiency drivers that are serving as testbeds and laying the groundwork for what’s to come. This phase is likely to continue throughout the year, as companies start building the foundations for implementation. As challenges like data privacy, information accuracy and bias are addressed, we anticipate that the range of use cases will expand to include more ambitious and public-facing deployments.

 

One of the most compelling use cases for generative AI in the financial services industry is in open banking. With the aid of fine-tuned LLMs, generative AI can enable the cleaning and categorization of data at a significantly higher through-put and with more accuracy than previously available.

In line with informed data consent protocols, generative AI could streamline personal financial management, for example, by acting as a personal wealth manager to create an encompassed view of an individual’s financial well-being, help formulate college savings plans, procure loans and implement financial strategies – empowering people to navigate their financial lives more adeptly.

Thank you, Steve! That was fun and we hope to see you back on AiThority.com soon.

• About Steve
• About Mastercard

About Steve

Steve is an IT professional with more than 25 years of industry experience in payments, government, and academia. He is currently responsible for leading Mastercard Foundry’s R&D initiatives in emerging technologies, including artificial intelligence, machine learning, quantum computing, 5G and Web3. In this role, Steve leads a team of talented data scientists, data engineers and software engineers to bring new products and services to market.

About Mastercard

Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments and businesses realize their greatest potential. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.

The post AiThority Interview with Steve Flinter, Distinguished Engineer, Artificial Intelligence & Quantum Computing, Mastercard Foundry R&D appeared first on AiThority.

Advanced supplemental group life insurance underwriting solution offers quicker, more accurate risk profiles to help individuals seeking additional life insurance coverage.

LexisNexis Risk Solutions, a leading data, analytics and technology provider, announced the availability of LexisNexis Risk Classifier for the supplemental group life insurance market. The advanced solution optimizes the supplemental group life underwriting process, providing insurers with a risk score that corresponds to an insured’s risk profile rather than invasive requirements, making the application process easier and faster to help ensure more consumers can access the life insurance they need.

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LexisNexis Risk Classifier aggregates long-standing data sources, including motor vehicle records, public records and credit attributes, to provide added insights to assist underwriters in making confident and swifter decisions based on mortality risk. In addition to providing a single score in real time, the predictive model provides the critical context and reason codes behind the score. In today’s world where data privacy is so critical, LexisNexis Risk Solutions maintains as our utmost priority data privacy standards and the responsible use of information, such as following the governance of the Fair Credit Reporting Act (FCRA), helping ensure consumers have the transparency they need into their personal information.

Underwriters can use Risk Classifier to make a more accurate risk assessment and eliminate the need for an applicant to undergo traditional underwriting requirements such as medical testing, helping to lessen applicant frustration and decreasing the dropout rate. According to Due.com, up to 20% of applicants are known to disengage from the process when underwriters request additional requirements and expand decision timelines.

“With employees often choosing supplemental life insurance benefits to provide their families with the right coverage for their personal needs, group life insurance carriers need a more accurate risk assessment based on predictive and valuable data, and an optimized underwriting process to help deliver the best experience,” said Debra Gangelhoff, vice president and general manager, life insurance, LexisNexis Risk Solutions. “LexisNexis Risk Classifier helps equip insurers with better risk differentiation and allows consumers to navigate the supplemental life insurance enrollment more easily.”

Key features of LexisNexis Risk Classifier include industry-leading data sets, a streamlined and advanced model to reduce the need for lengthy initial interviews, and configurable segmentation options and reason codes to determine risk classes. LexisNexis Risk Classifier is a multivariate model that uses different attributes associated to an applicant that are both good and bad for mortality to calculate the risk score. When looking at the attributes one at a time, the solution shows relative risk mortality decreases, for instance, by 39% if an individual owns one or more properties or the risk is more than 2.5 times higher when an individual has a DUIⁱ.

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“With year-end signaling the start of the busy open enrollment season that includes significant responsibilities into January 2024 for human resource professionals, health insurance representatives, and group life underwriters and actuaries, life insurers can improve their workflow with one streamlined and integrated model,” said Gangelhoff. “This can give life insurers confidence in their decisions as technological advancements continue to usher in change across the industry.”

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[To share your insights with us, please write to sghosh@martechseries.com]

The post LexisNexis Risk Classifier Available for Supplemental Group Life Insurance Market appeared first on AiThority.

After extensive research of more than 25 hours, this is the best of the best list I could have ever prepared.

Well here is a complete well-researched list of the Top 50 Fintech Influencers. Below is the name list along with their LinkedIn profiles by which you can directly follow/connect with them. The following list has been prepared in descending order of their followers on LinkedIn. The Top 10 among them have been discussed in depth with a snapshot of their career and interest in the fintech domain.

Introduction

The financial technology sector has been expanding rapidly during the past 12 months. People who have shared their insights to improve the Fintech and Digital Finance Ecosystem are the driving force behind the Industry.

These people have recognized the pandemic as a chance to broaden their collaborations with other financial institutions and promote the widespread use of digital technologies. Their goal is to set the tone for the entire ecosystem.

Marketing, money, and even the best way to shoot a selfie with your brand new smartphone—all of these topics and more are being driven by influencers. They are the ones pushing for change and facilitating investment in the technologies and fields that produce desirable outcomes.

Top 50 financial technology thought leaders to follow.

These influencers rely heavily on social media to spread their message. Then there is the influence-providing backbone of blogs, podcasts, newsletters, speaking engagements, and the like, which spreads the word far and wide.

Discuss the Top 10 Movers and Shakers with me!

1. Ankur Warikoo

With a fan base of over 20 million Ankur has developed a strong online community. With more than 15 years under his belt, he has established himself as an entrepreneur, best-selling author, online instructor, and content developer. Inspiring millions of people to go after their dreams, his books have topped the Nielsen bestsellers list in India. He also started Webveda, a website where more than 350,000 people globally can take courses on topics like business management and personal development.

When it comes to personal finance, startups, careers, and education, he is a prolific content creator who has amassed a following of over 9 million people across multiple social media platforms.  Additionally, he is a mentor to and investor in early-stage companies, particularly consumer online firms. He is drawn to teams with a high tolerance for risk, a thirst for knowledge, and a willingness to try new things.  His goal is to educate the public so that they may make decisions in life based on information rather than guesswork.

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2) Alex Xu

With almost 5 million fans Alex has won over the minds and hearts of many people. Alex Xu is a novelist and software developer. He has a best-seller on Amazon’s “Distributed Systems & Computing” shelf with System Design Interview.

An Insider’s Guide. As of the end of 2020, translations of his book into seven languages (including Traditional Chinese, Russian, Japanese, Spanish, Polish, Simplified Chinese, and Korean) will have been completed.

3) Linas Beliūnas

Whether you’re interested in digital innovation, the future of technology, or the intersection between artificial intelligence and finance, he’s the man to follow. Linas is an ambitious business developer, sales expert, and FinTech strategist who wants to make a difference. In a positive way. His undergraduate degree is in Economics (with a double emphasis in Economics and Politics), but he has been interested in and/or employed by the Financial Services industry ever since his freshman year.

He was able to get a head start on my career and try my hand at a variety of professions and financial institutions (including Western Union, Danske Bank, and Norne Securities) because of this. He has been in the FinTech industry for over six years now, and he strives to improve and expand his knowledge every day.

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4)Lex Sokolin

With 3,000,000 people rooting for him, Lex still has a long way to go. Before my current role as Chief Economist at ConsenSys, he served as the company’s CMO and Global Fintech Co-Head. He has worked on AI, blockchain, AR, and VR. AdvisorEngine, a financial management platform with roboadvisor DNA, was bought by Franklin Templeton, where he served as COO and drove product design and corporate development.

Additionally, he served as CEO of NestEgg, a roboadvisor that uses algorithms to provide investment advice. He has written for numerous publications like the Wall Street Journal, the Economist, the Financial Times, CNBC, Reuters, American Banker, ThinkAdvisor, Financial-Planning, and Investment News to develop his perspective on Fintech and Futurism. Money2020, LendIt, Techonomy, General Assembly, In|Vest, T3 Enterprise Edition, and the FPA are just a few of the conferences where he has shared his thoughts on the future of technology.

5)Jim Marous

Jim is followed by 2,500,000 people. The #1 retail banking podcast, Banking Transformed, is hosted by Jim Marous, who has been named one of the top five banking influencers for a decade.

We have an insight from Jim himself on a one-on-one interaction-

“The fintech space is as active and dynamic as ever, with changes happening faster than ever. The power of this list of influencers is that people across the world can access insights about the future of fintech simply by following the content created and shared by these leaders.”

Marous is also a sought-after international keynote speaker, co-editor of The Financial Brand, and owner and publisher of the Digital Banking Report. Marous guides all aspects of financial services’ transition to digital. CNBC, BBC, CNN, The Wall Street Journal, The New York Times, The Financial Times,

The Economist, The American Banker, Accenture, Harvard Business Review, and Cheddar have all featured Marous, and he has spoken in front of audiences ranging in size from seven to seven thousand. Jim has also served as a financial policy advisor to the White House.

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6)Efi Pylarinou

Approximately 2 million people follow Efi. Dr. Efi Pylarinou is a veteran of Wall Street and a former academic who is now recognized as a top global thought leader in the fields of fintech and technology.  She is one of Onalytica’s “Who’s Who in AI” top 20 professional influencers for 2021 and one of their “Top 20 Fintech Influencers” for 2021 and 2022. According to Refinitiv for both 2019 and 2020, she is the most influential woman in the world of finance and data.

Awards Magazine also included him in their list of the Top 100 Tech Influencers.  She has a Ph.D. in Finance and is, therefore, an authority in her field; she is also a host, author, and speaker. She is a member of the Faculty of The Fast Future Executive, where she gives presentations on topics related to the future of finance and money.

7)Aakash Gupta

Aakash has more than 1.7 million followers. Chief Product Officer of Apollo. Proven success leading big PM teams at Google, Epic Games, Affirm, and other companies to expansion. Wharton Business School graduate with a background in economics and high school coding competition experience. When there are too many product releases, they don’t affect the right KPIs.

His approach to product management is just the opposite. He is an expert in influencing business results. This holds for both business-to-consumer and business-to-business SaaS offerings, both fundamental and PLG. In addition, he publishes the largest paid newsletter in the world aimed at computer professionals. 

8)Oliver Bussmann

Over a million people are following you. Senior Technology Executive Oliver Bussmann has been a leader in the High Tech and Financial Service industries at UBS, SAP, Allianz, Deutsche Bank, and IBM for more than 30 years. Oliver is a Change Agent who can lead large-scale, cross-cultural, trans-continental transitions that unite people, produce tangible results, and set businesses apart from the competition.

In the fields of financial technology, blockchain, enterprise mobility, and cloud computing, Oliver is a recognized leader. One of the first chief executive officers to recognize the potential of social media to grow his company.

9)Marcel van Oost

Almost a hundred thousand devotees. His life has been full of ups and downs, but now he is a connector in the FinTech industry. He’s a FinTech connector based in Amsterdam.

Not only for himself but for the whole FinTech industry, which presumably includes you and me! He helps us stay on top of the rapidly evolving FinTech industry by providing us with daily material and news updates.

10)Panagiotis Kriaris

Getting closer and closer to a million. He has spent his whole professional life at the intersection of business and technology, holding executive positions in fields as diverse as FinTech, payments, retail, e-commerce, and digital projects.

Having held major positions in Commercial/Corporate/Small/Medium Enterprise Banking, Retail Banking, Payments, and FinTech, among other areas of the financial sector. His focus during the past few years has been on innovation, strategy, business growth, strategic partnerships, and the creation of new enterprises and products.  He is a well-known expert in the field of finance, and as such, he is frequently invited to speak at conferences and other events all around the world.

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Conclusion

We have an insight from Jim himself (host of the Banking Transformed podcast) on a one-on-one interaction in which he discussed the role of a fintech influencer and why are they important.

“Fintech influencers play a pivotal role in shaping the perspectives, knowledge, and strategies of leaders in retail banking and the broader financial services industry. Their impact extends across various dimensions:

Acting as thought leaders and evangelists for innovation – They promote awareness and understanding of new fintech developments and trends, and why they matter for the future of banking and financial services.

Providing insights and analysis – Through blogs, videos, podcasts, and other formats, they offer valuable perspectives on the strategic implications of fintech for incumbents. This includes assessing threats, identifying opportunities, and recommending potential responses.

Sparking discussion and debate – As respected voices, they stimulate conversation and examination of fintech issues across the industry through social media, conferences, and advice to mainstream media.

Challenging the status quo – Their outside-in view questions conventional wisdom and pushes banks and financial firms to re-examine assumptions about customers, capabilities, and competitive landscapes.

Highlighting real-world examples – They showcase inspiring case studies of fintech innovation and disruption in action to make the possibilities tangible. Educating on new tech – From blockchain to AI to open banking APIs, their simplified explanations help demystify complex technologies for non-technical executives and professionals.

Providing strategic counsel – Banks, vendors, regulators, and startups leverage their expertise via advisory roles to stress test strategies and transform business and operating models.

Amplifying other voices – By engaging the broader fintech community, highlighting diverse perspectives, and mentoring emerging influencers, they enrich the discussion. In summary, prominent fintech influencers serve a vital role as provocateurs, educators, analysts, and strategists guiding the financial industry to harness new technologies for the digital era.

The goal of most fintech influencers is to help incumbents evolve.”

The post Who Are The Top 50 Fintech Influencers To Follow? appeared first on AiThority.

JCB Contactless will allow cardmembers to tap and go when paying at Worldpay from FIS merchants who use Ingenico terminals in the UK

JCB International Co., Ltd., the international operations subsidiary of JCB Co. announced an extension of its collaboration with global financial technology leader FIS and its merchant solutions business, Worldpay from FIS, to enable JCB Contactless for its UK merchants in the largest JCB contactless deployment in the UK to date.

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In 2023, almost 20% of Worldpay Point of Sale (POS) systems in the UK are now equipped to accept JCB contactless payments. As part of JCB’s mid-term plan, the next stage will see JCB Contactless enabled across on the remaining 80% of Worldpay terminals across the UK, with full rollout expected to be completed by the end of 2024.

JCB Contactless is JCB’s contactless payment system that allows customers to shop by simply holding their JCB Card or JCB-card-enabled smartphone or other devices over the store terminal. JCB Contactless is based on the global chip standard ‘EMV(R),’ offering a high level of security.

The recently published Worldpay from FIS Global Payments Report found cash use continues to decline at POS, with contactless payments in the form of digital wallets and contactless cards on the rise. In the UK, cards and digital wallets combined accounted for 86% of POS spend. As such, more and more merchants in the UK are looking towards a cashless future, with comprehensive contactless payments emerging as a critical function. Enabling JCB Contactless will help Worldpay meet the increased demand for comprehensive contactless acceptance amongst its merchants.

Worldpay’s UK merchants which enable JCB Contactless will be able to further tap into the sales opportunities of JCB’s 154 million cardmember community. The fast, secure and convenient payment process for cardmembers, combined with the higher average transaction value of contactless, will help merchants increase their sales opportunities.

Ray Shinzawa, Managing Director for JCB International (Europe) Ltd., said: “We are delighted to see the next stage of this ambitious project come to fruition, further reinforcing our collaboration with Worldpay. We look forward to continuing to work together in enabling JCB Contactless across the entire Worldpay POS ecosystem.”

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Nick Fisher, General Manager, UK, JCB International (Europe) Ltd., said: “By offering a greater variety of contactless options to their merchants, Worldpay’s merchants will benefit from an enhanced customer experience. The payment preferences of consumers across the region are changing rapidly, and JCB is proud to be working with leaders like Worldpay to enable the future of payments.”

Chris Wood, General Manager for SMB International, Worldpay Merchant Solutions, FIS said: “With our research showing consumers are switching to contactless payments, it’s crucial we provide them with the ability to pay with their preferred payment method whenever and wherever they want. Our collaboration with JCB will enable this, simplifying our merchants’ payments acceptance, and accelerating growth.”

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[To share your insights with us, please write to sghosh@martechseries.com]

The post JCB Extends Collaboration with Worldpay from FIS for Largest Contactless Deployment in the UK appeared first on AiThority.

PaymentComponents Ltd, a pioneer in financial technology, in collaboration with Infosistema, a leader in technology and business consulting, proudly announces its instrumental role in the development of Unicâmbio’s new digital wallet. This innovative solution is powered by the robust and versatile aplonAPIOpen Banking platform.

Unicâmbio, a renowned payment institution, has taken a significant leap forward in digital financial services. With the assistance of PaymentComponents and Infosistema, Unicâmbio’s digital wallet now offers users a seamless experience for depositing funds, viewing transactions, sending money, and more. This enhancement marks a pivotal step in Unicâmbio’s commitment to providing cutting-edge digital services to its customers.

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PaymentComponents has been at the forefront of financial innovation, and their aplonAPI™ is a testament to their expertise in the field. “Our partnership with Infosistema to build Unicâmbio’s digital wallet demonstrates our dedication to advancing the FinTech landscape. We are thrilled to see how our aplonAPI™ has been leveraged to create such a dynamic and user-centric digital wallet,” commented a representative from PaymentComponents Ltd.

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Infosistema, known for its technical prowess and business acumen, played a critical role in the project. “Working with PaymentComponents and Unicâmbio has been a rewarding experience. This project showcases our ability to deliver complex technological solutions that drive the financial sector forward,” remarked a spokesperson from Infosistema.

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[To share your insights with us, please write to sghosh@martechseries.com]

The post PaymentComponents and Infosistema Facilitate Unicâmbio in Launching an Advanced Digital Wallet Using Aplonapi appeared first on AiThority.

The financial fund platform HedgeFundBank planned to become a global strategic partner with major commercial banks, establishing a financial fund platform service alliance to promote global industry development and provide high-quality service solutions to customers. This initiative marks the exploration of a new model in fund investment by international financial institutions, potentially leading to significant changes in the investment methods of these institutions.

As an industry leader, HedgeFundBank has been providing world-class services since its establishment in 2017, attracting attention from the market and media. It has been rated as investment-grade BBB by Standard & Poor’s. The company serves more than 200 banks and securities dealers, and over 400 financial intermediary institutions in over 80 countries and regions, offering trading investment services and solutions. It has processed an annual cumulative transaction volume exceeding one hundred billion, establishing a convenient, stable, and practical brand image among institutional investors.

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To date, HedgeFundBank has signed distribution agreements with brand funds in various global partner regions, selecting the best from online financial products, and collaborating with globally renowned investment research, rating, and consulting organizations to recommend the most authoritative data and analysis reports to the most suitable investors. Meanwhile, several stable banks in the international market serve as the supervisory banks for HedgeFundBank’s fund sales, ensuring safe and stable transactions for investors.

If HedgeFundBank successfully establishes global strategic partnerships with major commercial banks, it will provide a new one-stop investment advisory service for a wide range of financial institution clients. HedgeFundBank has already launched various composite strategies on its platform, such as wealth management alternatives, to meet the diverse risk preferences and investment horizons of financial institutions. The Market Department Manager of HedgeFundBank stated that besides the strategies already launched, HedgeFundBank can also offer customized strategies based on the needs of institutional clients.

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HedgeFundBank’s specialty lies in helping investors choose suitable wealth management products and providing professional investment and wealth management services. The company is fully committed to building a leading global wealth management O2O model, promoting an upgrade of the original business model. Investing in wealth management on online financial platforms, ordinary people can not only receive professional investment advisory guidance but also enjoy the convenience of one-stop wealth management, realizing functions like online reservation, transaction, and payment of funds and other financial products, achieving stable wealth appreciation.

It is reported that on the first day HedgeFundBank announced its cooperative strategy, bank clients signed contracts and transferred funds, operating the system smoothly and efficiently. In light of this, HedgeFundBank will establish alliances with more partners, enhancing market competitiveness, providing customers with more choices, and striving to become the most trusted financial assistant for investors.

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[To share your insights with us, please write to sghosh@martechseries.com]

The post HedgeFundBank and Major Commercial Banks’ Global Alliance, Expected to Lead a Transformation in the Financial Services Industry appeared first on AiThority.

Stampli, the AI-powered Accounts Payable automation solution, released new research shedding light on the state of AI adoption among finance professionals. Stampli partnered with Probolsky Research, a leading market and opinion research firm, to survey attitudes around AI among different job titles within finance. The survey results indicate that while AI holds significant promise for improving Accounts Payable (AP) processes, effectively scaling the use of AI requires solving barriers at points across financial organizations.

The Stampli Accounts Payable Survey finds that widespread interest in AI integration is tempered by notable differences in enthusiasm for the technology as well as the perceived risks and benefits. Senior decision-makers are the most interested in AI, while human oversight and data security issues stand out as the principal roadblocks to adoption. The respondents represent AP stakeholders in financial services as well as industries like professional services and manufacturing, with job titles ranging from AP team members to senior finance managers and Chief Financial Officer-level positions.

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“AP processes are among the most manual in business. They can drag efficiency and increase the likelihood of incorrect or late payments, reducing cash flow visibility. This, in turn, creates a risk to vendor relationships and hinders strategic cash flow management,” said Eyal Feldman, CEO and Co-Founder of Stampli. “AI is much better suited to this work, with substantial efficiency and cost benefits to an organization. CFOs who see the value should understand why people in the organization are hesitant and address those concerns head on.”

• The C-suite embraces AI: Respondents in company leadership are the most interested in adopting AI for AP processes, like document capture, coding, and fraud detection, with C-suite (92%) and senior-level management (85%) saying they are interested. Although they largely embrace the potential of AI across the board, management-level respondents still named concerns around privacy and data security (44%) and technical learning curves (32%) as adoption barriers.
• Less buy-in across the organization: The survey found an enthusiasm gap between senior management and accounts payable team members. Overall, 68% of AP team members surveyed were very or somewhat interested in the potential of AI for their function, with only 18% of respondents choosing the most positive response. This could be attributed to their uncertainties related to the benefits and job impacts, indicating a need for more proactive education and outreach on AI from company leadership.
• Leaders are eager for efficiency gains: Perceptions of the benefits of AI in AP also varied according to job title. Approximately 55% of both C-Suite and senior management cited improving accuracy as the top benefit, followed by improved processing speeds and fraud detection. AP team members, however, viewed improving processing speeds as the key benefit (48%), followed by improving financial system efficiency and refocusing humans on more valuable tasks. This reflects the day-to-day operations and efficiency priorities among AP team members, while managers tend to see more holistic benefits with AI.
• The need for a human in the loop: AP team members were much more likely to express a hesitancy towards full automation than C-suite and senior-level managers (64% vs. 32% and 41%, respectively). However, 63% of AP team members surveyed were more inclined to embrace AI if decisions were subject to human approval. Integrating human decision-making into AI systems could solve adoption barriers among AP teams, but this will likely require additional education for financial leadership on how AI systems and human oversight can work together.

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The research results parallel the broader conversation on enterprise AI integration while providing in-depth insights into the evolving role of AI in finance functions. The findings also demonstrate a growing demand for innovative Accounts Payable solutions, like Stampli, that can help integrate AI capabilities while also mitigating employee concerns, knowledge gaps, and adoption pain points.

One example of AI that has been successfully embraced by AP organizations is Stampli’s Billy the Bot™, which performs otherwise manual tasks such as capturing information on invoices, allocating costs to the correct cost centers, identifying approval workflows, detecting fraud, and more. Two key elements of Billy’s design have proven crucial in customer acceptance: humanizing and personifying the technology, and ensuring that humans retain full control over validating the AI’s decisions. Stampli customers often described Billy as a member of the team.

“CFOs can rest assured that AI is not a replacement for human oversight; it’s an amplifier,” stated Anthony Fernandes, Financial Controller at Alden Group Renewable Energy. “Without AI, I would require five full-time Accounts Payable specialists. Instead, a single person handles this workload, dedicating just 20% of their time. That’s a 25-fold efficiency boost, directly impacting company profitability. By automating routine tasks, AI frees up my team’s valuable time to focus on edge cases, where their expertise is truly needed.”

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In Q1 2024, Bloomberg Beta and Stampli are hosting a series of invite-only think tank sessions to help CFOs balance the incredible pace of AI innovation against the more deliberate speed of Finance. Attendance is strictly limited to a small number of forward-thinking finance leaders who want to accelerate their AI strategies years ahead of their competition.

[To share your insights with us, please write to sghosh@martechseries.com]

The post Stampli Identifies the Barriers Holding Back Adoption of AI in Finance Teams appeared first on AiThority.

The EIB Group is joining Mission Innovation primarily to facilitate access to finance for innovative projects across a wide array of sectors and geographic regions

The European Investment Bank (EIB) Group, which consists of the European Investment Bank and the European Investment Fund, and Mission Innovation are joining forces to support clean energy innovation worldwide. The announcement of the new partnership was made at a joint event at the United Nations Climate Change Conference COP28 in Dubai. Building new public-private partnerships to accelerate the development of innovative clean energy technologies is one of the priorities at COP28 to meet the Paris climate goals.

The EIB Group is joining Mission Innovation, which already includes a coalition of 23 governments and the European Commission, primarily to facilitate access to finance for innovative projects across a wide array of sectors and geographic regions. In addition, the EIB Group will share its expertise on financial instruments that help to mobilise the much-needed private finance to support game-changing technologies that can put economies on track towards a net-zero future. The new EIB Group partnership with Mission Innovation builds on the fruitful cooperation with the European Commission’s Directorate-General for Research and Innovation over the years.

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EIB Vice-President Ambroise Fayolle said: “Financing the technologies of tomorrow is key to reaching global climate goals, supporting economies’ competitiveness and creating new jobs. The involvement of public multilateral development banks at the earliest stage is crucial here. That’s why the EIB Group is proud to join Mission Innovation to play our part and accelerate clean energy solutions for all. We can bring our technical and financial expertise to build dynamic public-private partnerships for game-changing technologies that will power us all towards a net-zero future.”

European Commission Executive Vice-President Maroš Šefčovič said: “I am very pleased to see the European Investment Group joining Mission Innovation, our coalition together with 23 governments catalysing a decade of action and investment in research, development and demonstration to make clean energy affordable, attractive and accessible for all. Mission innovation will now benefit from the European Investment bank’s to help innovative companies develop and grow, which will strengthen the mission’s already significant contribution towards the Paris Agreement goals and climate neutrality.”

Head of Secretariat for Mission Innovation Eleanor Webster said: “The partnership between Mission Innovation and the European Investment Bank Group aligns perfectly with our shared commitment to driving clean energy innovation and achieving the objectives set out in the Paris Agreement. By combining our expertise and resources, we can increase our impact and accelerate the development and demonstration of innovative solutions.”

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The EIB Group has extensive experience in building public-private partnerships. It works closely with the European Commission and the private sector to share risks that private investors alone are not willing to take — especially at the earliest stages. Twenty years ago, the EIB helped to establish offshore wind as a competitive and reliable source of energy. Today, the EIB Group is playing an instrumental and central role in scaling up innovation in sectors that are hard to decarbonise, such as steel and shipping.

At the same time, Mission Innovation is rolling out a number of high-ambition missions, which mobilise the international action needed to reach tipping points in the cost and scale of clean energy solutions by the end of this decade. This alliance between the EIB Group and Mission Innovation is testament to the importance of early-stage investment in clean energy technologies and is a critical part of the pathway for these missions to achieve their goals.

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[To share your insights with us, please write to sghosh@martechseries.com]

The post European Investment Bank Group and Mission Innovation Team Up to Accelerate Clean Energy Innovation appeared first on AiThority.

Inflation, interest rates on the rise, and the specter of a recession hanging over us all. High turnover and workforce shortages. Supply chains that simply can’t catch a break. Even though some opportunities have arrived in 2023 like the rise of generative AI, this year has still been a challenging one for most companies.

As we look to 2024, many of us finance leaders and business leaders are experiencing a combination of hope that things will be better and dread that these challenges could continue. How can we use our FP&A (financial planning & analysis) tools and strategies to mitigate new challenges while capitalizing on any opportunities that may arise?

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If finance and business leaders have their people, technologies, and processes in a good position they will be able to react swiftly to the good and the bad whenever they arise.

The Right People

Without a solid personnel foundation, the next two areas won’t matter—the best technology in the world won’t get you far if there isn’t someone to utilize it and troubleshoot, and processes are nothing without the right people to execute them.

If your current staff doesn’t have the right skills to reach your business goals, determine whether training can bridge that divide or if hiring is your solution. Teams both large and small have their own strengths and weaknesses; ascertaining what those are with a team review is a necessary first step to finance success in 2024.

Foundational Technology

Oftentimes, small and midsize businesses (SMBs) use Excel and Google Sheets because they aren’t aware that there are solutions that fit the mid-market space. Excel inhibits the ability to be agile, makes it harder to do things faster, and is error-prone. FP&A tools, on the other hand, have removed barriers for SMBs, making it easier for them to plan at the speed of business.

Though the technology we rely on to budget and forecast is advancing all the time, that doesn’t mean each new product is necessarily a fit for your department. Especially given how complex the software landscape has become, more care should be taken in building or choosing a platform to work from.

It’s better to assess any new technology by the following criteria: does it fit into one of the key pillars of FP&A technology?

Those pillars are what all finance departments are built on, and include data management, reporting and dashboards for visibility, financial modeling and budgeting, and workflow tools to better enhance collaboration. AI and machine learning are quickly becoming an essential pillars in their own right.

If a new technology would improve any of these foundational pillars of your finance department, it’s worth a close look. If it’s not making a meaningful addition to your technology suite, it’s likely more of a distraction and can be avoided.

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Perfect Processes

Now that you have the right people and the right tools, it’s time to put the machinery in motion. Evaluate the way your people work.

Are they properly utilizing the technology you have put in place?

If not, something is amiss and you either need to replace the tools or do some training so that your team knows how and why to use them.

In almost every department there are processes that could be improved.

Finance leaders should focus on building efficiency, removing redundancies, and building a comprehensive strategy. Innovation is necessary, but people can naturally be resistant to change, especially when the goal isn’t clear from the outset. Be sure to recognize good work, reward innovative thinking, and use KPIs (key performance indicators) to allow process improvements to take hold in your department.

[To share your insights with us, please write to sghosh@martechseries.com]

The post Where To Focus Your 2024 Financial Planning appeared first on AiThority.

With a CAGR of 32.6% between 2021 and 2030, the worldwide AI in the banking market is expected to expand from its 2020 valuation of $3.88 billion to a total of $64.03 billion.

Introduction to AI and its potential in the Banking and Finance industry

Artificial Intelligence has drastically changed banking and finance. Recently, AI technologies like machine learning and natural language processing have helped banks automate procedures, generate insights, and enhance client experiences.

Fraud detection and prevention are significant AI applications in banking and finance. AI systems can swiftly detect fraud in big transaction volumes. AI can also identify suspicious trends and abnormalities that may indicate fraud.

Customer service is another AI-powered banking application. AI-powered chatbots and virtual assistants may answer client questions and make data-driven suggestions. This helps banks enhance customer service and cut expenses.

AI enhances banking risk management. Banks may anticipate and manage risks by examining consumer behavior, market trends, and economic indicators.

The banking and financial services sector has been drastically altered by the advent of AI. Automating procedures, gaining insights, and improving overall customer services are just some of the ways that banks and financial institutions have benefited from the development of artificial intelligence (AI) in recent years. AI has several uses in the banking and financial services industry, but one of the most important is its application in the identification and prevention of different types of fraud. AI systems can swiftly examine enormous numbers of transactions and identify fraudulent behavior. A further use for AI is in the detection of anomalies and out-of-the-ordinary patterns that might be suggestive of fraud.

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Customer service is another key area where AI has proven useful in the banking industry. Chatbots and virtual assistants powered by AI may answer customers’ questions and provide tailored suggestions based on their information. Financial firms may use this to boost customer satisfaction and cut expenses. Banking risk management is another area where AI is being put to good use. By examining data from different sources, including customer behavior, market trends, and economic indicators, banks may detect possible hazards and take proactive efforts to reduce them.

Overall, banking and financial services are just scratching the surface of what can be done using artificial intelligence. As its development proceeds, we anticipate increasingly sophisticated uses of AI in areas such as portfolio management, credit analysis, and regulatory compliance. AI in banking and financial services is still developing, with numerous prospects for innovation and development. As AI advances, investment management, loan underwriting, and compliance will become more advanced.

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What is ML in Finance?

Machine learning (ML) is a branch of AI that allows computers to teach themselves new skills via the use of neural networks and deep learning without being given any specific instructions. It allows financial institutions to utilize the data to train models to address specific problems with ML algorithms – and give insights on how to improve them over time. The chart below has been picked up from the Deloitte source to add up the required spice.

10 AI ML In Banking And Finances Trends To Look Out For In 2024

Trend 1-Detect anomalies

Companies’ asset-serving divisions struggle most with anomaly identification. Anomalies might originate from ordinary accidents or system defects. Fintech anomalies may be linked to illegal operations like account takeover, fraud, network infiltration, or money laundering, which might have unintended consequences. Anomaly detection may be solved via machine learning. Financial machine-learning anti-fraud systems can spot tiny user behavior patterns and correlations. It can analyze enormous databases and compare variables in real-time to detect fraudulent transactions.

The use of RPA (Robotic Process Automation) enables AI to analyze and improve business procedures. This allows for the automation of around 80% of repetitive job procedures, freeing up time for knowledge workers to focus on value-add operations that demand a high degree of human engagement.

Trend 2-Portfolio Management Robo-Advisors

Online robo-advisors provide automated financial guidance. Their algorithms and data-driven portfolio management services develop and maintain clients’ investment portfolios.

Some people find investing scary, but internet investment platforms make it easier. These services are also much cheaper than financial advisors. Many have low or no account minimums. Online investing businesses Betterment and Wealthfront offer portfolio management and financial advice through their robo-advisors or mobile apps. Online financial advisers help consumers manage their finances using technology. Betterment recommends asset allocations to investors using algorithms. Investor responses to “How do you plan to use the money?” and “What is your timeline? This conclusion is drawn.

Technology’s impersonality helps Wealthfront offer investing services. Its program executes proven investing techniques, automatically finds better investments, and maintains the appropriate investment mix. Nutmeg is a leading UK digital wealth manager. Based on financial goals and risk tolerance, the Nutmeg robo-advisor invests in a balanced portfolio.

Trend 3-Algorithmic Trading

Algorithmic trading allows large transactions by regularly sending “child orders” to the market. Hedge fund managers employ automated trading techniques and machine learning in finance. Traders might automate particular procedures to stay competitive. The technology also allows cross-market trade, improving possibilities. Machine learning algorithms’ real-time learning and response provide banking organizations with a competitive edge.

Trend 4-Chatbots and VAS

Consumers demand more conversational bank interactions. They want Amazon, Netflix, and Uber-like customer service. This is achievable in banking thanks to chatbots and virtual assistants. Consumers want better customer service from banks as well as other sectors. AI-powered chatbots and virtual assistants may advise users on bank account balances and other transactions 24/7. They can also allow conversational money transfers.

AI-powered chatbots merged with Natural Language Processing (NLP), connect and communicate with clients 24/7 and enhance online discussions. Chatbots may now do more than just respond to common client inquiries about their accounts; they can also assist with tasks like creating new accounts and routing complaints to the proper departments.

Trend 5-Underwriting based on ML

If a consumer has no bank credit history, it might not be very reassuring to assess their creditworthiness. Big data and ML examine 10,000+ data points to determine creditworthiness. It allows pre-approval of loans for a wide range of consumers, including students and self-employed people.

In corporate lending, AI-based underwriting may simplify the complicated process, assess market patterns, detect loan risks, future behavior, fraud likelihood, etc.

This brief movie introduces HALO, our AI/ML analytics platform for data-driven automated credit decisions for banks and financial organizations. Lenders can save credit costs by enhancing loan disbursals with HALO. Explore HALO, the realm of AI-powered lending.

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Trend 6- Personalized Banking

Personalization is AI and Machine Learning’s largest value. Based on spending patterns, savings and investment objectives, health insurance portfolios, and other characteristics, a future bank should deliver insights, alerts, and suggestions suited to an individual’s financial goals. AI is still developing and being implemented in banking. Some banks use predictive analytics to estimate consumer financial demands.

Before offering personalized services, banks must know how clients want to be addressed. Lots of work is needed. Banks need plenty of fragmented data from several systems and divisions. AI must be used to mine this data and provide customers with relevant insights and guidance.

Trend 7- Cybersecurity and AML

Innovative AI and machine learning integration into banking will improve security in the future. The financial services industry can improve cybersecurity and anti-money laundering with AI and ML. Many banks use AI and ML to detect suspicious or anomalous money laundering transactions. In the approaching years, AI and ML will be used more. Integrating these technologies will streamline service, saving time, money, and personnel. It will also assist banks, corporations, and people in upgrading their security systems to avoid cyberattacks on their institutions, networks, and accounts.

By analyzing historical data on assaults and picking up correlations between seemingly unrelated indications, AI has the potential to greatly enhance the efficiency of cybersecurity systems. In addition to mitigating external risks, AI may also monitor internal threats or breaches and recommend remedial steps, resulting in the avoidance of data theft or misuse.

Trend 8- Credit Score

Credit scoring may be ML’s biggest banking application. It determines a customer’s ability to pay and debt repayment intentions. Credit scoring solutions are needed since billions of people are unbanked and barely half qualify for credit. Work experience, income, transaction analysis, and credit history are some of the factors used in machine learning scoring.

This mathematical model uses statistical and accounting principles. Machine learning algorithms can create more accurate, sensitive, and personalized credit score evaluations, enabling more individuals to get credit. Human scorers cannot objectively rate debtors like machine learning algorithms. With machine learning in banking, organizations may eradicate gender, racial, and other conscious or unconscious prejudices and serve more people.

Since ML in credit scoring has several benefits, including the opportunity for users to request loans in a few clicks from home, Document Processing, and Onboarding Document processing has traditionally been laborious. Machine learning accelerates document classification, tagging, and processing. OCR must be performed to copies before machine learning algorithms can analyze scanned documents’ text to establish context. This data helps the machine learning model classify and index everything for future use. Machine learning on paper forms can help traditional banks enroll new clients.

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Trend 9- Better Investment Assessment

Investment valuation requires many complex calculations. The strategy involves collaborating with investment asset management teams, product specialists, and portfolio managers. These teams should consider investment options. ML can solve this problem by processing vast amounts of data from several sources in real-time and learning risk tolerance, investment, and time horizon biases.

Trend 10- Customer Sentiment Analysis

Big data and machine learning have made client sentiment analysis a significant AI application for banks. Banks have a lot of unstructured consumer data, which computers can’t grasp. AI can interpret this data and get new insights. When a consumer phones the help desk with an issue, an AI system may detect their emotions in real-time. This helps banks assess their staff’s problem-solving skills and take action if consumers aren’t satisfied. These technologies can analyze client feedback and social media remarks. Banks may use AI to forecast consumer reactions to events like the debut of a new product or service or market developments by recognizing trends in online customer reviews.

What’s next for AI in banking and finance?

The chart below has been taken from The Economist which gives an overview of the successful adoption of AI and ML in organizations.

The development of the financial sector will be aided by AI. Many businesses now use digital methods, which have allowed them to increase sales, streamline operations, and concentrate on data. They’ll have to build up the level of individualization in their relationship-based client interaction going forward. Customized replies, safer and more responsible product and service suggestions, and expanding concierge services accessible at consumers’ beck and call all benefit greatly from AI’s involvement.

In addition, banks will have to create distinctive digital customer profiles based on customers’ permissions, although the information they require may be isolated in other databases. Financial institutions can scale effectively and meet the individualized demands of their consumers by eliminating silos, layering on AI, and employing human involvement seamlessly.

Although AI and ML are still in their infancy in banking, we may aspire for increased usage. Fortunately, financial institutions are recognizing the implications of AI and ML technology. However, most banks have restrictive systems that make technological transformation difficult. Banks must trust and utilize these technologies to overcome this.

The post 10 AI ML In Banking And Finances Trends To Look Out For In 2024 appeared first on AiThority.