Making sense of unstructured data.
REDEFINING INTELLIGENT LENDING
Muhammad Hejvani on the Future of Data-Driven Finance in the Agentic AI Age at MOGOPLUS
As the financial services industry continues its rapid evolution, MOGOPLUS stands at the forefront of innovation, transforming how banks and lenders leverage transactional data to make smarter, faster, and more accurate decisions. Leading this transformation is Muhammad Hejvani, Chief Data & Technology Officer, whose two-decade career spans Asia Pacific and the Middle East. In this Executive Insight, Muhammad shares how his team is pioneering the use of AI-powered unstructured data analytics, building an internal Agentic AI Factory, and ensuring robust data privacy and regulatory compliance. With a firm belief in prioritising real-world problems over buzzword driven solutions, Muhammad offers a refreshingly pragmatic take on the future of AI in finance, the challenges of open banking, and the essential skills tomorrow’s leaders will need to thrive in a data first world.
Career Journey
Can you share your career journey and what led you to your role as Chief Data & Technology Officer at MOGOPLUS? What key experiences have shaped your approach to leadership in data and technology?
For the past two decades, I’ve had the privilege of working with some of the most talented professionals across Asia Pacific and the Middle East, primarily serving clients in Financial Services, Telecommunications, Retail, and Public Services. While my titles evolved, my core focus remained constant: I’m a solutionist at heart, leveraging data and technology to address business challenges for clients and their customers.
A few key lessons stand out from my leadership journey. First, understanding the real business problem, analysing data objectively (without bias), and selecting the right technology for implementation are the key ingredients for successful solutions. Many technology projects fail when solutions are “desired” rather than “suitable.” For example, today’s demand for AI often overlooks whether it’s genuinely the most effective tool for the task.
Second, I’ve learned the vital importance of cognitive diversity within teams. Encouraging varied perspectives and diverse thinking, often undervalued, significantly enhances problem solving and drives innovation.
Leveraging Data for Smarter Financial Decisions
MOGOPLUS focuses on data driven insights for financial services. How does your team harness data to help businesses make smarter lending decisions?
At MOGOPLUS, we harness data to enable smarter lending decisions by tackling one of the most valuable yet underutilised datasets: bank transaction data. While rich in insight, this data is often difficult to analyse due to its volume, inconsistent descriptions, and privacy considerations.
Our core strength lies in unstructured data analytics specifically, our proprietary Categorisation Engine, which has been meticulously developed over a decade. This engine accurately classifies complex transaction data, consistently achieving industry leading benchmarks in both confidence and accuracy. It transforms messy, raw data into structured, actionable insights.
By providing lenders with this high quality, categorised data, we empower them to make more informed, reliable, and ultimately smarter lending decisions, accelerating their digital transformation. Looking ahead, we’re integrating AI agents to further support the credit decisioning process while maintaining full regulatory compliance.
The Role of AI and Machine Learning
How is MOGOPLUS utilising artificial intelligence and machine learning to enhance data analysis, risk assessment, and customer insights? What recent advancements have had the most significant impact?
Great question! Since early 2023, we’ve been modernising our Categorisation Engine with the support of Machine Learning (ML) and Artificial Intelligence (AI). A key initiative has focused on using ML/AI to augment our existing rules-based engine, improving the accuracy and reliability of enriched data. This leads to deeper customer insights derived from transaction data and enables more robust risk and affordability assessments for our clients.
We’ve also developed several AI Agent prototypes, leveraging state of the art AI technologies. These initially focused on streamlining the complex task of maintaining the engine’s rules, boosting their efficiency and consistency, critical for reliable analysis.
Responding to the rapid pace of AI innovation, our most significant recent advancement is strategic: the establishment of an “Agentic AI Factory.” This internal framework accelerates the creation and deployment of specialised AI Agents. These Agents are designed to perform advanced data analysis, enhance risk and affordability models, and uncover richer customer insights, at scale and speed. We’re currently testing some of these Agents with one of our partners in the Middle East.
Driving our exponential growth is a dynamic partnership strategy centred on the integration of our solutions within our partners’ ecosystems. This powerful synergy is exemplified by our recently announced alliance with Provenir, a progressive global software company delivering a comprehensive AI Decisioning Platform for Credit Risk, Fraud, and Compliance across the entire customer journey, perfectly complementing our own strengths.
Data Privacy and Security in Financial Services
With increasing concerns around data privacy and cybersecurity, how does MOGOPLUS ensure the protection of sensitive financial data while maintaining compliance with global regulations?
Data privacy and security are top priorities at MOGOPLUS. We are ISO 27001:2022 certified, ensuring that our processes and products meet the latest international standards for information security management systems (ISMS).
Security is embedded from the outset, we follow privacy by design and security by design principles, supported by a zero-trust architecture. Our authentication and authorisation mechanisms are developed in-house, aligned with Financial grade API (FAPI) specifications to enable secure data exchange. All sensitive data is encrypted both at rest and in transit. We also enforce the principle of least privilege (PoLP) and apply Role Based Access Control (RBAC) across all teams.
We rigorously test our security posture through annual Disaster Recovery and Business Continuity (DR/BC) drills and partner with third party vendors for regular penetration testing, meeting the stringent requirements of our tier 1 bank clients in Australia.
Additionally, as we advance initiatives such as our Agentic AI Factory, we’ve established a dedicated security and compliance team to proactively manage evolving threats and maintain strong governance.
Challenges in Implementing Open Banking Solutions
Open banking is reshaping financial services. What are some of the biggest challenges in implementing open banking solutions, and how is MOGOPLUS addressing them?
While Open Banking (OB) holds immense potential to reshape financial services, its adoption faces several significant hurdles. In my experience, particularly in Australia, a key challenge is that some institutions still view Open Banking and the Consumer Data Right (CDR) primarily as regulatory obligations, rather than as strategic opportunities to deepen customer insights.
Other major obstacles include navigating complex multi-party consent processes, managing systemic integration challenges across the ecosystem (banks, data recipients, service providers), and ensuring consistent data quality throughout.
As an Outsourced Service Provider (OSP), MOGOPLUS tackles these integration challenges head on. Following significant platform modernisation, our modular architecture enables rapid integration with Accredited Data Recipients (ADRs), reducing typical connection times from weeks to hours.
Additionally, our Google Cloud Marketplace solution allows users to bring their own data (BYO) and access our insight reports within minutes, drastically simplifying how lenders and ADRs can leverage Open Banking data for valuable decision-making insights.
Balancing Innovation and Regulatory Compliance
How do you balance the need for rapid innovation in financial technology with the strict regulatory requirements that govern the industry?
Regulatory frameworks are essential for safeguarding consumer rights and ensuring long term stability, but their implementation must evolve to remain relevant in the age of AI. Innovation is equally critical for the continued relevance and competitiveness of the banking and finance industry. We should leverage technology, particularly the reasoning capabilities of AI Agents, to enhance and streamline compliance efforts.
I anticipate the emergence of practical Compliance Agents in the near future, moving beyond controlled lab environments into real world applications. A key step in this transition will be expert human collaboration to build comprehensive knowledge bases that capture potential compliance issues and regulatory concerns. These will serve as foundational learning material for the Agents, allowing them to adapt and evolve.
While historical data is still valuable, the ability to detect novel patterns and emerging fraud risks is becoming increasingly important, especially as financial ecosystems grow more complex.
Proactive adaptation of audit and compliance mechanisms is essential to keep pace with the rapid advancements in multi agent AI systems. This is how we will ensure innovation and regulation can move forward hand in hand.
The Future of Data Driven Decision Making in Finance
As financial institutions become more data driven, what key trends do you see shaping the future of data analytics in banking and lending?
I see several key trends emerging as data analytics transforms the financial industry in the post GenAI era. First, there’s a shift from traditional decision support dashboards towards AI-powered Assisting Agents that augment human expertise in complex credit application scenarios. These agents will not only provide insights but also guide analysts through intricate metrics, regulatory frameworks, and risk assessments, leading to more informed and consistent decision making. That said, human input will still be crucial in defining key metrics and performance measures.
I also anticipate the adoption of Automated Decisioning Agents for simpler, non-complex credit applications. However, widespread implementation will depend on how well we address compliance and regulatory concerns. These AI-driven systems will be able to autonomously process applications based on predefined rules and risk parameters, allowing human analysts to focus on more nuanced cases and boosting overall efficiency.
Finally, the increasing importance of regulatory compliance will drive the rise of Audit and Compliance Agents. These systems will continuously monitor transactions, flag potential compliance breaches, and generate audit trails, helping institutions stay aligned with evolving regulations and mitigate operational risks.
Together, these trends are set to reshape the future of data analytics, enabling greater automation, enhanced efficiency, and improved accuracy across banking and lending.
Enhancing Customer Experience with Technology
How is MOGOPLUS using technology to improve customer experience and engagement in the financial sector?
MOGOPLUS, as a B2B provider, enhances the customer experience in the financial sector by streamlining credit decisioning for lending institutions. Our advanced analytics process diverse data sources, equipping credit officers with key metrics to assess affordability and serviceability. This reduces decision times from hours to minutes, resulting in faster, more efficient loan application processing for consumers, ultimately improving their competitiveness in the market.
Looking ahead, our Agentic AI Factory is set to further revolutionise this experience. These smart, assisting AI Agents will provide real time support to credit officers, helping ensure consistent, unbiased lending decisions and a more personalised application process. By identifying individual customer needs and suggesting tailored solutions, these AI Agents enable our clients to deliver a more efficient, accurate, and transparent experience, fostering greater trust and satisfaction across the board.
“Looking ahead, our Agentic AI Factory is set to further revolutionise customer experience”
Collaboration with Financial Institutions
How does MOGOPLUS collaborate with banks and financial service providers to integrate data driven solutions into their existing frameworks?
MOGOPLUS’ solutions are specifically architected for seamless integration, particularly to support financial institutions pursuing a best of breed technology strategy.
At the core of our solution architecture is an API-centric approach, enabling smooth, standardised data exchange between our capabilities and clients’ diverse platforms, avoiding the complexities associated with traditional, tightly coupled integrations.
This is further supported by a modular, microservices architecture. This design allows for the efficient creation of data pipelines, ingesting data from various endpoints into existing client workflows, and enables our components to integrate flexibly as part of a broader client solution.
Ultimately, these technical foundations minimise disruption and reduce integration timelines. They empower banks and financial service providers to rapidly adopt our data driven insights within their existing frameworks, making collaboration with MOGOPLUS both straightforward and efficient.
Advice for Aspiring Leaders in Data and Technology
For professionals looking to build a career in data analytics, financial technology, and artificial intelligence, what skills and experiences do you believe are most valuable?
Rather than listing clichés or favourite tools, let me share what has truly helped me stand out in my career.
First, a strong blend of technical expertise and business acumen is perhaps the most valuable asset. It enables you to effectively translate business needs into technical requirements, challenge assumptions critically, and seek diverse perspectives to uncover the real problem beneath the surface.
Second, always prioritise the problem over the technology. Don’t chase trends blindly. Instead, focus on understanding the ‘why’ behind a technology and objectively choose the most suitable tool for the specific challenge at hand.
Third, cultivate the ability to navigate ambiguity while maintaining thoroughness. It’s essential to deeply understand requirements before committing to, or prematurely finalising, a solution.
Lastly, stay hands-on and be a fast learner. Technology evolves rapidly. The most effective leaders stay relevant, aren’t afraid to get their hands dirty with code or tools, regardless of seniority, and lead by example through sharp, up to date skills.
MOGOPLUS is an Australian fintech company specializing in transforming unstructured financial data into actionable insights to support smarter lending and credit decisions. Founded in 2012 and headquartered in Sydney, MOGOPLUS operates across Australia and the UK, partnering with banks, credit unions, and digital lenders to enhance decision-making through datadriven solutions.
Muhammad Hejvani Chief Data & Technology Officer