Why Machine Learning Has Huge Potential in Fintech

The skyrocketing growth of e-commerce data volumes means that fintechs face unprecedented challenges in processing, analyzing and tuning this data in the fastest and most efficient way. With a large number of new companies and partnerships taking up the challenge, there is an area of ​​innovation that offers huge potential for the fintech sector.

the amount of data worldwide is expected to reach 175 zettabytes by 2025, up from an estimated 44 zettabytes by 2020 (one zettabyte equals a thousand exabytes, a billion terabytes, or a trillion gigabytes). As a data processing industry that has experienced rapid growth in recent years, many UK fintechs have already adopted solutions to increase accuracy, efficiency and adaptability within data reporting and reconciliation processes.

Simply put, these core business processes can make or break a company’s growth and affect a company’s efficiency: poor data reporting and inaccurate reconciliation can cost significant amounts of money, waste resources and result in a lack of regulatory compliance. With traditional Excel spreadsheets that leave a lot to be desired, with little audit trail and a lot of room for human error in manual processes, data reporting and reconciliation should not only be automated; it should also be integrated into as many data formats and sources as possible. As transaction data emerges from an ever-expanding number of payment channels, devices and touchpoints, the quest for intelligent automation and improved reconciliation has never been more urgent and sought after.

According to recent research by the Global Fintech SeriesTwo-thirds (66%) of financial services firms expect solutions to automate manual processes to be one of their top investment focuses in the next three years, while 68% plan to fully automate their reconciliation within the next five years year† By automating these processes as much as possible, fintechs can accelerate their decision-making much more accurately.

The current challenges for fintechs in data reporting

Payment and fintech companies often have multiple processor relationships, card scheme relationships, and issuance relationships, making them responsible for large amounts of data coming from multiple third parties and in different formats. But with data volumes escalating rapidly and the increasing needs and expectations of the fintech industry requiring new ways to handle the intensive demands of data collection, analysis and tuning, even automated processes need to make strides to keep pace with the sector.

As 2022 begins and the UK fintech sector seeks further innovation, expansion and investment, certain trends will further disrupt data reporting and reconciliation to meet demand. With 86% of respondents in PWC’s Payments 2025 & Beyond Report If we can agree that in the future traditional payment providers will partner with fintechs and technology providers as one of their main sources of innovation, the possibilities (and expectations) for the sector are huge.

With a clear need for new innovations and partnerships to support the complex demands of the ever-changing fintech sector, we are entering a new era of companies with solutions that fit together: the fintechs for fintechs. Kani Payments is one such company: we launched a SaaS reconciliation and reporting platform specifically designed to reduce complexity for financial services providers. Be it other ambitious fintechs, challenger banks, acquirers or payment companies, the conditions are ideal for new partnerships that enable the fintech industry to scale faster.

New capabilities for intelligent data reconciliation

The need for improved business operations, driven by rising data volumes and high levels of remote working, will be a key strategic priority for fintech companies in 2022 and beyond. Building on the need to further optimize data reporting, processing and reconciliation, machine learning will be the next level of automation innovation for fintechs in the UK.

The use of machine learning in any industry, in whole or in part, has the main goal of eliminating human controls, increasing accuracy and reducing the scope for manual errors. In fact, machine learning has already been identified as a key business technology trend for 2022 and beyond: Analytics Insight estimates that machine learning will reach $80.3 billion in revenue by 2023a figure that will only grow massively as machine learning expands into use cases within the fintech sector.

Even before the pandemic, payment companies struggled to manage complex data reconciliations that involved time-consuming manual processes. As the pandemic-driven shift to digital payments worldwide has led fintechs everywhere to seek greater clarity from their data, it is innovations such as machine learning that can help them keep up with demand.

For the data reconciliation process, machine learning can help companies make increasingly accurate decisions at lightning speed, leaving more room to inform business strategies, steer new service developments with faster go-to-market times, and help meet stringent regulatory requirements reporting and audit trail requirements.

Innovation from the UK Alternative Fintech Hub

To date, Kani Payments has reconciled more than €10 billion of processed payment volume with our automated reconciliation and reporting platform and is committed to supporting and accelerating even more innovation in data reporting and reconciliation, with new geographies on our roster and a suite of services designed to take fintechs to the next level.

Kani recognizes that accurate and verifiable payment data reconciliation and reporting is critical for payment and fintech companies to mine valuable business insights and scale to meet customer demand, and has recently invested in building of new AI and machine learning functionality.

Our investment, which is currently unique in the fintech market, was initiated through a collaborative project with the Mathematics Department of the University of Newcastle and the National Innovation Center for Data, which explored how we could strengthen our record Matching solutions for machine learning and integrate. With positive results, we are excited to see how our work can help UK fintechs continue to thrive in 2022 and beyond.

Named as an emerging fintech hub in the 2021 Kalifa Review of UK FintechNewcastle is fast becoming one of the most exciting and attractive locations for dynamic financial services firms and fintech players, a place Kani Payments is proud to call home. Our investment in and research into machine learning for the fintech data reconciliation process will not only help solidify Newcastle and the Northeast as a thriving data science and fintech hub, but will empower fintechs themselves to be global tech pioneers in a rapidly changing environment. sector.

Leave a Comment

Your email address will not be published.