Particularly since the release of OpenAI‘s ChatGPT at the back-end of 2022, the world has sat up and taken notice of the potential of artificial intelligence (AI) to disrupt all industries in countless ways. To kick off 2024, The Fintech Times is exploring how the world of AI may continue to impact the fintech industry and beyond throughout the coming year.
The potential of AI is a topic that dominated discussion throughout 2023. Practically everyone in finance agrees that AI can impact every aspect of business, whether it be improving customer experience or streamlining operations.
But, with the concept still fairly fresh, how much are fintechs really using AI? Are they embracing it, or taking a backseat to see how it is used by others? To find out, we asked a range of representatives from fintech firms how AI has directly impacted their business.
Increasing productivity
As Ylva Oertengren, COO at Simply Asset Finance, explains, AI can be used to free up time to focus on other areas of business and innovation: “So far, our focus is to deliver business benefits behind the scenes.
“Our strategy is to primarily increase productivity within our operations and finance teams to deliver business efficiencies that mean we’re able to focus more on our customer engagement.
“The capacity thus created is being re-invested in continuing to establish a new level of service in SME lending and accelerate the build of our technology that is tailored to business lending. In other words, AI is not altering our goals, but it also accelerates our journey to get there.”
‘AI is the cornerstone of our operations’
For Tensorflight, a property platform reducing risk, waste, as well as cost in an increasingly competitive environment, AI is used across all aspects of its operations. Its co-founder and chief product officer, Robert Kozikowski, explains: “In our AI-centric startup, AI is the cornerstone of our operations, not just a transformative element.
“Our business revolves around maximising diverse AI models for a range of applications. This includes computer vision models for interpreting various types of imagery of buildings, models for analysing building permits, and others for processing tax records and property data.
“A key component of our AI suite is our GPT-based assistant, ‘TensorAssist,’ tailored for underwriters. This tool, along with our other AI applications, is helping to transform the insurance sector, dramatically improving the efficiency of underwriting processes, minimising errors, and ensuring more precise pricing, leading to a significant reduction in unexpected claims. With these tools, a single underwriter can now do the work that used to take five underwriters.
“Our business model, which integrates AI-generated data and tools, is designed to offer comprehensive solutions. AI’s role in our business is foundational, influencing every aspect of what we do and enabling us to provide advanced, efficient services to the fintech industry.”
Processing large volumes of data
Peter Wood, a three-time tech founder and CTO at Spectrum Search, also reveals how AI has ‘transformed’ business: “AI has fundamentally transformed my fintech business.
“It has enabled us to process large volumes of data for better decision-making, automate key processes, and deliver personalised experiences to clients.
“Particularly, the integration of AI in our recruitment agency has revolutionised how we match candidates with opportunities, enhancing both efficiency and success rates. As someone deeply involved in AI and ML innovation, I’ve witnessed firsthand how AI can redefine business models, while creating new value propositions in fintech.”
‘AI has been a game-changer’
Tomas Navickas, CTO and co-founder of digital banking platform myTU, also added: “AI has been a game-changer for our fintech business, going beyond what traditional machine learning offers. The most striking impact for myTU? As for now, it’s the transformation of our customer due diligence process.
“Gone are the days of laboriously sifting through documents for hours. Now, our AI whizzes through and summarises all essential materials in just seconds. In a short month, we integrated AI into our platform, enabling it to pull insights from user profiles, like deducing political exposure from job titles.
“This shift to AI-driven processes has supercharged our efficiency, especially in tasks like scrutinising customer records, and it perfectly aligns with our vision of automating a large chunk of our digital banking operations.
“At myTU, our lean towards automation and AI isn’t just about being tech-savvy; it’s strategic. Our entire IT operations are managed by just three to five dedicated professionals. Yet, they have the capacity to seamlessly serve up to half a million clients without a hitch.”
‘AI fits seamlessly into our story’
Finally, Gil Cross, AI product manager at Xceptor, reveals how it is supporting other business users to adopt AI models: “Xceptor’s mission has always been to empower business and operations users to automate their business challenges. AI fits seamlessly into our story.
“What’s changed are the kinds of solutions we can offer customers and the speed at which these solutions can be delivered. Interpreting the intent of unformatted conversational emails or deciphering a 100-page loan agreement document are unsolvable challenges using only rules and logic. With AI capabilities embedded within a data automation platform such as Xceptor, these challenges can be solved by non-technical people with clicks in a user interface.
“Our customers receive thousands of tax documents a day and processing them can take hours. With recent developments, cross-jurisdiction/cross-asset class documents can be processed automatically, removing hundreds of hours of effort. AI has opened the door to solving a vast set of previously unsolvable challenges.
“We put business and operations in control of data automation back when only complex, technical ETL tools were available, and now we’re doing it with AI. We’re empowering business users to adopt AI models and bring them into production, providing operational teams with the tools needed so tasks can be performed reliably and in a way that satisfies risk and governance concerns.”
