Easier payments, robot assistants and improved accessibility -- fintech predictions for 2025
The banking and finance sector has already seen some major changes in technology use in recent years. These show no signs of slowing down but newer developments like AI are starting to have an impact too.
Here are some expert views on what may be in store for the fintech sector in the year to come.
Access tokens and service accounts next target for cyberattacks
New research shows 88 percent of security leaders believe machine identities, specifically access tokens and their connected service accounts, are the next big target for attackers.
The survey from Venafi of 800 security and IT decision-makers from large organizations across the US, UK, France and Germany, finds 56 percent have experienced a security incident related to machine identities using service accounts in the last year.
Threats to encryption, security fears and a race to gain a competitive edge -- quantum predictions for 2025
As we approach the end of the year it's time to start wondering what the next one will have in store. As always we'll be running a series of pieces looking at what industry experts think will be key tech industry trends for 2025.
We start with a look at quantum, which is getting ever closer to widespread commercial deployment and could open up great opportunities but is also leading to increasing fears about security.
Consumers resolve to learn AI in 2025
At the dawn of a new year most people plan to make lifestyle changes like losing weight or giving up smoking. But new research commissioned by Tech Show London reveals that over 12 million UK consumers plan to make learning AI a New Year's resolution for 2025.
This growing interest in mastering AI signals a shift towards greater understanding and engagement with the technology that is increasingly shaping our lives. 46 percent of those surveyed agree that AI will fundamentally transform our relationship with technology.
Demand for AI could exceed computing capacity
AI, and generative AI in particular, is expected to greatly enhance productivity within work processes. Some studies estimate that generative AI could contribute between $2.6 trillion and $4.4 trillion annually to the economy.
However, AI infrastructure is costly because the underlying algorithmic problems are extremely computationally intensive and this means there's a potential gap between demand and the capacity needed to meet it.
A quarter of organizations suffer AI-enhanced attacks against APIs or LLMs
A new study finds 25 percent of respondents have encountered AI-enhanced security threats related to APIs or LLMs, with 75 percent of respondents expressing serious concern about AI-enhanced attacks in the future.
The research from API specialist Kong shows that although 85 percent say they're confident in their organization's security capabilities, 55 percent of respondents have experienced an API security incident in the past year, highlighting a notable disconnect.
AI impacts on data storage infrastructure
As we've already seen today organizations are struggling with the increasing demands of data infrastructure. Another new report from MinIO highlights how organizations are leveraging object storage for AI, machine learning (ML), and data-intensive workloads.
The survey of over 650 IT leaders 70 percent of enterprise data is in object storage today and this is expected to grow to 75 percent over the next two years.
The race against AI web scrapers: effective strategies to protect your data [Q&A]
A surge in artificial intelligence (AI), generative AI (GenAI), and machine learning (ML) technologies is creating a massive online appetite for data. These tools are hungry for training data, this has boosted AI web scraping, which sits in a legal gray zone. Sometimes it's legal, sometimes it's not, but what's clear is that it's having ripple effects across online businesses.
We talked to Nick Rieniets, field CTO of Kasada, to learn more about the impact of web scraping and what companies can do to protect their content.
Why it's time for a reset of security metrics [Q&A]
Historically, security metrics have focused on measuring how many attacks are successful and how long it takes for a successful attack to be detected. This is perhaps unsurprising since the bulk of the industry has focused on building tools to detect adversaries.
We spoke to Nicko van Someren, chief technology officer at Absolute Security, to learn why companies focusing purely on defense can create more risk for their organizations, and why instead of focusing on 'time to detection,' it's time to reset security metrics to focus on 'time to recovery.'
Big spend on enterprise AI doesn't always deliver big returns
New research from Digitate reveals that while 92 percent of European organisations have implemented AI and automation, many lack a strategic approach to maximise the impact.
The study, based on a survey of 900 IT decision-makers in enterprises across Europe, finds that organisations have invested on average, €103.4M ($108M) in AI and automation over the last two years, with over half (59 percent) spending up to €295M ($309M). These investments have yielded significant returns, with 86 percent of organizations reporting a ROI averaging €154.7M ($162.4M).
New platform lets developers build more accurate AI apps faster
High-quality retrieval is key to delivering the best user experience in AI search and retrieval-augmented generation (RAG) applications.
Knowledge platform Pinecone has announced new vector database capabilities combined with proprietary AI models to help developers build more accurate AI applications, faster and more easily.
Managing the shift to machine-to-machine communication [Q&A]
As AI continues to evolve, it will enable machines to communicate in new, dynamic, autonomous ways without human intervention.
This machine-to-machine growth has a huge potential to impact industries from smart factories to energy. We spoke to John Kim, CEO of API communication specialist Sendbird, to discuss these changes and how they will affect business.
The crucial role of data pipelines in building strong GenAI apps [Q&A]
For GenAI to live up to its promise reliable flow of data is key. AI models are only as good as the data pipeline connections bringing in quality data.
Outdated connections mean more hallucinations and untrustworthy results with data engineers hopelessly trying to manually integrate hundreds of AI data feeds. We spoke to Rivery co-founder and CEO Itamar Ben Hemo to discuss why good data pipelines are key to success.
Addressing AI challenges for the enterprise [Q&A]
With more and more businesses keen to benefit from the possibilities that AI offers it seems like everyone is jumping on the bandwagon. But this raises a number of implementation and management challenges, especially now as enterprise AI workloads begin to scale.
We spoke to Tzvika Zaiffer, solutions director at Spot by NetApp, to discuss how these challenges can be addressed and the best practices that are emerging to ensure that implementations go smoothly.
Google calls the AI fuzz to find vulnerabilities
Not familiar with 'fuzzing'? It's a software testing technique that involves feeding invalid, unexpected, or random data into a program to detect coding errors and security vulnerabilities.
Back in August 2023, Google introduced AI-Powered Fuzzing, using large language models (LLM) to improve fuzzing coverage to find more vulnerabilities automatically -- before malicious attackers could exploit them.
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