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Systems of Record are Required for Systems of Intelligence

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Businesses need systems of record. Only when we have systems of record can we have systems of intelligence. And business leaders who develop systems of intelligence within their organizations will define the next frontier in their sector.

Let’s look at financial crime.

Systems of record at a bank or fund services firm can allow teams to learn about and then store info on a particular financial scam or scheme. When a bad actor attempts to repeat that scheme, the system of record recognizes it from its databank and can tell systems or people to shut down that bad actor.

But financial criminals know how banks and other institutions work. They are constantly changing their methods and schemes. It’s not enough for bankers or fund administrators to defend against the same types of crime. They must look for the same repeating patterns in their data. They need to defend against the crimes of the future. These crimes may look nothing like previous digital heists or fraudulent transactions.

This foresight requires a system of intelligence. AI tools should power it. These tools can run perpetual analyses on incoming data. They identify known dangers and flag suspicious “unknown unknowns.” These may indicate criminal activity. This kind of smart system helps bankers or other business leaders make breakthroughs. They do this based on the data that’s been collected. They provide foresight for what might come next using probabilities based on the system of record.

Systems of intelligence – a term coined by author Geoffrey Moore in 2017 – look deeper into transactional data to uncover the most well-hidden risks lurking within an organization. The feedback loop of finding new crimes then helps create new rules, keeping pace with the criminals while maintaining an expanding archive of their schemes.

It’s never been more important for financial firms to show they are serious about financial crime. The cost of financial crime compliance in the United States was predicted to hit almost $46 billion in 2022, up from more than $26 billion in 2019. Global financial crime costs banks north of $2 trillion annually.

Finance and investing firms need systems that are agile enough to confront the compliance challenges of tomorrow and take on the ever-expanding amount of work involved in financial crime and transaction monitoring. Only AI-powered solutions at this stage can deliver this level of efficiency and security.

As the Wall Street Journal’s Richard Vanderford reported, customers and regulations increasingly expect banks, funds, and others to deploy financial-crime-detecting AI systems. There’s no other way to scour billions of transactions while money launderers, human traffickers, drug dealers, and other criminals grow more sophisticated and tech-savvy daily. Vanderford cited AI proponents, saying, “AI can do the job better, require less staff, and enable continuous check-ups on customers and transactions for money-laundering issues and sanctions violations.”

To understand the power of AI-driven systems of intelligence in confronting these myriad challenges, it’s worth looking at how similar tools are revolutionizing health care – specifically preventing heart attacks.

The Semmelweis University Heart and Vascular Center in Hungary has treated thousands of patients with heart disease. They collected troves of data and images to create a patient similarity network. In short, they had a potentially powerful system of record. However unlocking the system’s potential required deploying an AI platform. The platform found patterns and delivered insights. This was achieved through a combination of topological data analysis and supervised and unsupervised learning.

The Center created a system of intelligence that is now detecting cardiovascular risk sooner, predicting patient outcomes more accurately — and saving lives.

This example shows how a system of record is only the first step in deploying data to improve outcomes. Taking the next step allows organizations to identify recurring problems. And they do it far more effectively. They start looking ahead constantly to identify risk. During a time of staff shortages and rising demands across sectors, AI crucially allows companies to increase efficiency without increasing head counts.

More than three in four financial executives see AI-enabled risk detection driving improvements in fraud prevention over the next year, according to a recent survey. More than half see it driving advancements in credit decisions and cost savings.

Firms with a system of intelligence stand to see significant reductions on two fronts. They significantly cut costs. And they avoid the potentially crushing blow of attacks or missed opportunities.

Featured Image Credit: Provided by the Author; Thank you!

Chris Gale

Founder

Chris is the founder of enterprise technology advisory and communications firm Gale Strategies. He’s an integrated communications marketer helping growing businesses and multinationals manage critical issues and tell their story to investors, customers, and consumers.

Politics

Fintech Kennek raises $12.5M seed round to digitize lending

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London-based fintech startup Kennek has raised $12.5 million in seed funding to expand its lending operating system.

According to an Oct. 10 tech.eu report, the round was led by HV Capital and included participation from Dutch Founders Fund, AlbionVC, FFVC, Plug & Play Ventures, and Syndicate One. Kennek offers software-as-a-service tools to help non-bank lenders streamline their operations using open banking, open finance, and payments.

The platform aims to automate time-consuming manual tasks and consolidate fragmented data to simplify lending. Xavier De Pauw, founder of Kennek said:

“Until kennek, lenders had to devote countless hours to menial operational tasks and deal with jumbled and hard-coded data – which makes every other part of lending a headache. As former lenders ourselves, we lived and breathed these frustrations, and built kennek to make them a thing of the past.”

The company said the latest funding round was oversubscribed and closed quickly despite the challenging fundraising environment. The new capital will be used to expand Kennek’s engineering team and strengthen its market position in the UK while exploring expansion into other European markets. Barbod Namini, Partner at lead investor HV Capital, commented on the investment:

“Kennek has developed an ambitious and genuinely unique proposition which we think can be the foundation of the entire alternative lending space. […] It is a complicated market and a solution that brings together all information and stakeholders onto a single platform is highly compelling for both lenders & the ecosystem as a whole.”

The fintech lending space has grown rapidly in recent years, but many lenders still rely on legacy systems and manual processes that limit efficiency and scalability. Kennek aims to leverage open banking and data integration to provide lenders with a more streamlined, automated lending experience.

The seed funding will allow the London-based startup to continue developing its platform and expanding its team to meet demand from non-bank lenders looking to digitize operations. Kennek’s focus on the UK and Europe also comes amid rising adoption of open banking and open finance in the regions.

Featured Image Credit: Photo from Kennek.io; Thank you!

Radek Zielinski

Radek Zielinski is an experienced technology and financial journalist with a passion for cybersecurity and futurology.

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Politics

Fortune 500’s race for generative AI breakthroughs

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Deanna Ritchie


As excitement around generative AI grows, Fortune 500 companies, including Goldman Sachs, are carefully examining the possible applications of this technology. A recent survey of U.S. executives indicated that 60% believe generative AI will substantially impact their businesses in the long term. However, they anticipate a one to two-year timeframe before implementing their initial solutions. This optimism stems from the potential of generative AI to revolutionize various aspects of businesses, from enhancing customer experiences to optimizing internal processes. In the short term, companies will likely focus on pilot projects and experimentation, gradually integrating generative AI into their operations as they witness its positive influence on efficiency and profitability.

Goldman Sachs’ Cautious Approach to Implementing Generative AI

In a recent interview, Goldman Sachs CIO Marco Argenti revealed that the firm has not yet implemented any generative AI use cases. Instead, the company focuses on experimentation and setting high standards before adopting the technology. Argenti recognized the desire for outcomes in areas like developer and operational efficiency but emphasized ensuring precision before putting experimental AI use cases into production.

According to Argenti, striking the right balance between driving innovation and maintaining accuracy is crucial for successfully integrating generative AI within the firm. Goldman Sachs intends to continue exploring this emerging technology’s potential benefits and applications while diligently assessing risks to ensure it meets the company’s stringent quality standards.

One possible application for Goldman Sachs is in software development, where the company has observed a 20-40% productivity increase during its trials. The goal is for 1,000 developers to utilize generative AI tools by year’s end. However, Argenti emphasized that a well-defined expectation of return on investment is necessary before fully integrating generative AI into production.

To achieve this, the company plans to implement a systematic and strategic approach to adopting generative AI, ensuring that it complements and enhances the skills of its developers. Additionally, Goldman Sachs intends to evaluate the long-term impact of generative AI on their software development processes and the overall quality of the applications being developed.

Goldman Sachs’ approach to AI implementation goes beyond merely executing models. The firm has created a platform encompassing technical, legal, and compliance assessments to filter out improper content and keep track of all interactions. This comprehensive system ensures seamless integration of artificial intelligence in operations while adhering to regulatory standards and maintaining client confidentiality. Moreover, the platform continuously improves and adapts its algorithms, allowing Goldman Sachs to stay at the forefront of technology and offer its clients the most efficient and secure services.

Featured Image Credit: Photo by Google DeepMind; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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Politics

UK seizes web3 opportunity simplifying crypto regulations

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Deanna Ritchie


As Web3 companies increasingly consider leaving the United States due to regulatory ambiguity, the United Kingdom must simplify its cryptocurrency regulations to attract these businesses. The conservative think tank Policy Exchange recently released a report detailing ten suggestions for improving Web3 regulation in the country. Among the recommendations are reducing liability for token holders in decentralized autonomous organizations (DAOs) and encouraging the Financial Conduct Authority (FCA) to adopt alternative Know Your Customer (KYC) methodologies, such as digital identities and blockchain analytics tools. These suggestions aim to position the UK as a hub for Web3 innovation and attract blockchain-based businesses looking for a more conducive regulatory environment.

Streamlining Cryptocurrency Regulations for Innovation

To make it easier for emerging Web3 companies to navigate existing legal frameworks and contribute to the UK’s digital economy growth, the government must streamline cryptocurrency regulations and adopt forward-looking approaches. By making the regulatory landscape clear and straightforward, the UK can create an environment that fosters innovation, growth, and competitiveness in the global fintech industry.

The Policy Exchange report also recommends not weakening self-hosted wallets or treating proof-of-stake (PoS) services as financial services. This approach aims to protect the fundamental principles of decentralization and user autonomy while strongly emphasizing security and regulatory compliance. By doing so, the UK can nurture an environment that encourages innovation and the continued growth of blockchain technology.

Despite recent strict measures by UK authorities, such as His Majesty’s Treasury and the FCA, toward the digital assets sector, the proposed changes in the Policy Exchange report strive to make the UK a more attractive location for Web3 enterprises. By adopting these suggestions, the UK can demonstrate its commitment to fostering innovation in the rapidly evolving blockchain and cryptocurrency industries while ensuring a robust and transparent regulatory environment.

The ongoing uncertainty surrounding cryptocurrency regulations in various countries has prompted Web3 companies to explore alternative jurisdictions with more precise legal frameworks. As the United States grapples with regulatory ambiguity, the United Kingdom can position itself as a hub for Web3 innovation by simplifying and streamlining its cryptocurrency regulations.

Featured Image Credit: Photo by Jonathan Borba; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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