Voice of the Industry

The evolution of financial operations and key trends to watch in generative AI for finance

Tuesday 13 February 2024 09:43 CET | Editor: Alin Popa | Voice of the industry

Swapnil Mengawade from Optimus Fintech discusses the evolution of financial operations and the rise of Generative AI, highlighting its transformative potential for efficiency and innovation in managing financial data.


The evolution of financial operations

Financial operations have come a long way from manual ledger systems to modern, fintech-based solutions. This evolution showcases the ongoing intersection of finance and technology, marked by innovation and progress. The shift towards digital transformation, automation, AI, and Generative AI (GenAI) is reshaping how we handle financial transactions, making processes more dynamic and responsive.

The state of finance and payments back-office operations

The current state of finance and payments’ back-office operations reflects a landscape in transition, caught between the inertia of traditional systems and the urgent call for innovation. Many back-office operations depend on legacy systems, marked by the persistence of manual data entry, time-consuming reconciliation processes, and a lack of real-time insights.
  • Nearly 65% of financial professionals spend a significant portion of their work hours on manual data entry and reconciliation tasks (Institute of Finance and Management).

  • More than 70% of financial institutions encounter difficulties in achieving real-time visibility into critical financial information and financial data insights (Accenture).

  • 7 out of 10 businesses encounter scalability and integration challenges with their existing back-office systems (Forrester).

  • Inefficiencies in cross-border payments are known to result in USD 50 billion in excess costs annually (McKinsey).


The rise of Generative AI

Unlike traditional AI, GenAI can analyse data and autonomously create, learn, and adapt, marking the beginning of a new era of efficiency and innovation. Instead of relying only on existing data, GenAI generates content, makes predictions, and creates realistic images, addressing challenges faced by traditional systems, as outlined below.

1. Automated financial operations

GenAI streamlines financial data management and reconciliation by automating extraction, synthesis, and analysis. It efficiently pulls structured and unstructured data, from financial statements to textual documents, organising it for a comprehensive overview. On the reconciliation front, Generative AI serves as a practical AI/ ML-powered suggestion engine, simplifying the investigation and classification of reconciliation breaks. It extracts insights, using string- matching models to match data across various transaction types, addressing complex scenarios. This end-to-end automation boosts processing speed, minimises human error, and improves decision- making for accurate financial insights. We have effectively integrated Generative AI alongside advanced data mining and analytics tools like neural networks and decision trees to enhance real-time analysis for our Fortune 500 clients, eliminating manual tasks and optimising workflows.

2. Advanced reporting and analytics

GenAI enhances reporting in financial operations for merchants, banks, insurance companies, and payment providers. It provides advanced analytics, including trend analysis and predictive reporting. Automation tools driven by GenAI generate regular and customisable financial reports, saving time and resources. This improves decision-making and offers comprehensive operational insights and forecasting for financial performance. The technology streamlines reporting processes, delivering actionable insights and supporting data-driven decisions. Its adaptability to various sectors ensures efficiency in managing and analysing financial data, contributing to informed decision-making and operational optimisation for businesses across the financial landscape.

3. Protection from fraud, chargebacks, and disputes

Generative AI utilises predictive analytics to pinpoint transactions at risk of chargebacks, enabling businesses to identify unusual patterns and proactively address issues. Its ability to analyse patterns and detect anomalies in real time enhances security measures, mitigating the risk of fraudulent activities on merchants, banks, and payment service providers. Automation simplifies chargeback resolution by efficiently categorising and managing disputes, overseeing responses, documentation, and communication – all achieved without manual intervention, ensuring a streamlined and effective process. Automation streamlines chargeback resolution by categorising and managing disputes, handling responses, documentation, and communication without manual intervention.

4. Fees and payouts

GenAI algorithms dynamically compute and adapt transaction fee structures, guaranteeing accuracy for financial institutions, payment service providers, and merchants with diverse fee systems. Automated systems manage payout calculations based on predefined rules, reducing errors, expediting payment processes, and ensuring timely payouts for merchants, insurance companies, and banks.

Key trends to watch out for in Generative AI for finance back-office operations

Experts agree that upcoming trends in GenAI will boost efficiency, improve security, and make finance back-office operations more agile. Here are some key developments to watch:


  • Advanced Natural Language Processing (NLP) will enhance the understanding and generation of more complex financial documents, improving communication and documentation processes.

  • Explainable AI (XAI) for regulatory compliance will enable transparent decision-making processes, aiding compliance efforts in finance.

  • Generative Adversarial Networks (GANs) will aid financial services in creating realistic synthetic data to train fraud detection models.

  • Customisable Generative AI models will allow finance teams to revolutionise real-time decision-making processes and tailor solutions to their specific needs, from addressing unique challenges in data acquisition and ingestion to transaction matching, exceptions and case management, or analytics and reporting.

  • Generative AI will enhance risk management capabilities and automate financial reporting, predicting the impact of various financial scenarios and ensuring accuracy and compliance with reporting standards. This is expected to streamline back-office operations, allowing financial professionals to focus on strategic decision-making.

  • Generative AI-driven personalisation in customer interactions is expected to improve customer satisfaction and loyalty by providing personalised financial recommendations and pre-emptive resolutions.


Looking ahead

Generative AI offers transformative potential by autonomously creating, learning, and adapting, leading to unprecedented efficiency, accuracy, and innovation. Whether through advanced NLP simplifying data ingestion, dynamic scenario simulation for risk management, or real- time decision-making with continuous learning, GenAI challenges traditional financial systems, promoting accessibility and tailoring solutions to unique organisational needs. The potential for increased efficiency, enhanced security, and personalised customer interactions makes it crucial for businesses to position themselves as leaders in the dynamic and intelligent future of finance. The journey begins with boldly integrating Generative AI into the fabric of financial operations.

This editorial piece was first published in The Paypers' Cross-Border Payments and Ecommerce Report 2023–2024, which taps into the fast-growing cross-border market and provides a comprehensive overview of trends and developments that are pivotal in this space, being the ultimate source of information for ecommerce businesses interested in expanding globally. 


About Swapnil Mengawade

Founder and CEO of Optimus Fintech, brings over 15 years in technology management, including over a decade of revolutionising payment back offices for Fortune 500 companies in the retail payments sector. Prior to Optimus Fintech, Swapnil has spearheaded groundbreaking initiatives viz. space payload launches at NASA – and implemented the world’s first robotic supply chain system at Estee Lauder. He holds a B.Eng. in mechanical engineering from Drexel University and an M.Eng. from Cornell University.

About Optimus Fintech 

Optimus Fintech is a financial services technology organisation offering an autonomous cloud platform – Optimus – to optimise payment and finance operations for businesses. The PCI DSS-compliant data platform automates data management, reconciliation, analytics, and reporting, processing billions of secure transactions annually. It democratises data fostering collaboration, enhances scalability, and boosts organisational efficiency and growth.

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Keywords: fintech, operational system, digitalisation, artificial intelligence, real-time payments
Categories: Payments & Commerce
Companies: Optimus Fintech
Countries: World
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