Why Machine Learning has huge potential in Fintech

The skyrocketing growth of ecommerce data volumes means fintechs are faced with unprecedented challenges in how to handle, analyse and reconcile this data in the quickest and most efficient way. With a host of new companies and partnerships rising to the challenge, there is one area of innovation that holds vast potential for the fintech sector. 

The amount of data globally is expected to reach 175 zettabytes by 2025, increasing from an estimated 44 zettabytes in 2020 (one zettabyte is equal to a thousand exabytes, a billion terabytes, or a trillion gigabytes). As a sector which handles large amounts of data and has seen rapid growth in recent years, many UK fintechs have already adopted solutions to increase accuracy, efficiency and adaptability within data reporting and reconciliation processes. 

Put simply, these core business processes can make or break company growth and impact a company’s efficiency: poor data reporting and inaccurate reconciliation can cost significant amounts of money, waste resources, and result in a lack of compliance with regulations. With traditional Excel spreadsheets leaving much to be desired, with little audit trail and considerable room for human error in manual processes, data reporting, and reconciliation not only needs to be automated; it also needs to be integrated into as many data formats and sources as possible. Given that transaction data is springing up from an ever-increasing array of payment channels, devices, and touchpoints, the quest for intelligent automation and enhanced reconciliation have never been more urgent and in demand. 

According to recent research by the Global Fintech Series, two-thirds (66%) of financial service organisations expect solutions that automate manual processes to be one of their top investment focuses over the next three years, whilst 68% plan to have fully automated their reconciliation within the next five years. By automating these processes as much as possible, fintechs can accelerate their decision-making with much greater accuracy.

The current challenges facing fintechs in data reporting

Payments and fintech companies often have multiple processor relationships, card scheme relationships, and issuing relationships, leaving them responsible for large amounts of data originating from multiple third parties and in different formats. But with rapidly escalating data volumes, and the increasing needs and expectations of the fintech sector which demand new ways to shoulder the intensive demands of collating, analysing and reconciling data, even automated processes need to advance to keep up with the sector.  

As 2022 commences and the UK fintech sector strives for further innovation, expansion and investment, certain trends are set to disrupt data reporting and reconciliation even further to match demand. With 86% of respondents in PWC’s Payments 2025 & Beyond report agreeing that traditional payments providers will collaborate with fintechs and technology providers as one of their main sources of innovation in the future, the possibilities (and expectations) are huge for the sector. 

With a clear need for new innovations and partnerships to support the complex demands of the ever-changing fintech sector, a new age of companies are stepping in with solutions to match – the fintechs for fintechs. Kani Payments is one such company: we’ve launched a reconciliation and reporting SaaS platform specifically designed to reduce complexity for financial services businesses. Whether it be other ambitious fintechs, challenger banks, acquirers or payments companies, the conditions are ideal for new partnerships which enable the fintech industry to scale faster. 

New possibilities for intelligent data reconciliation 

The need for improved business operations, driven by soaring data volumes, and high levels of remote working, will be a defining strategic priority for fintech businesses in 2022 and beyond. Building on the need to further optimise data reporting, handling, and reconciliation, the next level of automation innovation for fintechs across the UK will be machine learning. 

Either completely or in part, utilising machine learning within any sector has the primary objective of eliminating a need for human checking, thus increasing accuracy and removing room for manual error. In fact, machine learning has already been pegged as a major business technology trend for 2022 and beyond: Analytics Insight estimates machine learning to reach US$80.3 billion in revenue by the year 2023, a figure that’s only going to grow massively as machine learning expands in usage cases within the fintech sector.

Even before the pandemic, payments businesses struggled to manage complex data reconciliations which involved time-consuming manual processes. Now that the pandemic-driven shift to digital payments worldwide has led fintechs everywhere to scramble for more clarity from their data, it’s innovations such as machine learning that can help them keep up with demand.

For the data reconciliation process, machine learning can help businesses to make increasingly accurate decisions at lightning speed, allowing more space for informing business strategies, directing new service developments with quicker go-to-market times, and helping to meet stringent regulatory reporting and audit trail requirements.

Innovation from the UK’s Alternative Fintech Hub

Having already reconciled over €10 billion in processed payments volume to-date with our automated reconciliation and reporting platform, Kani Payments is committed to supporting and accelerating even greater 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.

Recognising that accurate and verifiable reconciliation and reporting of payments data is mission-critical for payments and fintech companies to mine valuable business insights, and to scale up to meet customer demand, Kani have recently invested in building new AI and machine learning functionality. 

Currently unique in the fintech market, our investment was initiated by a partnership project with Newcastle University’s Mathematics Department and the National Innovation Centre for Data, which explored how to solidify and integrate our machine learning Record Matching solutions. Yielding positive results, we are excited to see how our work can continue to help UK fintechs thrive in 2022 and beyond. 

Named as an emerging fintech hub in the 2021 Kalifa Review of UK Fintech, Newcastle is fast becoming one of the most exciting and appealing locations for dynamic financial services and fintech players, a place Kani Payments is proud to call home. Our investment 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 also empower fintechs themselves to be global tech pioneers in an fast-changing sector.

About the author: Aaron Holmes is CEO and Founder at Kani Payments. Aaron founded Kani following roles at Flex-e-card as General Manager, Global Processing Services as Chief Innovation Officer (CINO) and Chief Operating Officer (COO), and NBS Card Solutions (now Wirecard) as Senior Implementation Manager. Building on issuing, program management, and transaction processing roles, Aaron now leads the Kani business from its Newcastle upon Tyne head office.

About Kani Payments: Established in 2018 in Newcastle, UK, Kani Payments is a reconciliation and reporting platform specifically designed to reduce complexity for financial services businesses.  

Named ‘Europe’s Leading Financial Services or Payments Start-up’ by the Emerging Payments Association in 2019, Kani’s clients include fintechs, challenger banks, established banks, electronic money issuers, and gift card providers.