An In-Depth Interview with Hosne Ara Mohna : How Industry Is Being Reshaped by Accounting Analytics, AI, and Data-Driven Decision Systems

Staff Correspondent : Introduction : In an era where accounting is no longer confined to balance sheets and compliance reports, Hosne Ara Mohna emerges as a researcher whose work speaks directly to industry transformation. Educated in accounting at Dhaka City College under the National University of Bangladesh, she represents a new generation of scholars who see accounting as an analytical, predictive, and governance-oriented discipline. Her research spans AI-driven credit decision automation, predictive risk analytics, enterprise data visualization, cloud-based data engineering pipelines, and public-sector financial reform. What makes Mohna’s work particularly relevant to industry is its focus on adoption, how banks,...

114

Staff Correspondent :
Introduction : In an era where accounting is no longer confined to balance sheets and compliance reports, Hosne Ara Mohna emerges as a researcher whose work speaks directly to industry transformation. Educated in accounting at Dhaka City College under the National University of Bangladesh, she represents a new generation of scholars who see accounting as an analytical, predictive, and governance-oriented discipline. Her research spans AI-driven credit decision automation, predictive risk analytics, enterprise data visualization, cloud-based data engineering pipelines, and public-sector financial reform. What makes Mohna’s work particularly relevant to industry is its focus on adoption, how banks, corporations, and institutions can realistically implement advanced analytics without undermining transparency, regulatory compliance, or professional judgment. As industries across South Asia and beyond confront digital disruption, regulatory pressure, and rising competition, her research offers structured pathways for turning accounting into a strategic engine rather than a back-office function.

Interview
Q1: Ms. Mohna, from an industry standpoint, how do you see the role of accounting evolving in today’s organizations?
Hosne Ara Mohna: From an industry perspective, accounting has moved decisively beyond its traditional role as a record-keeping and compliance mechanism. Today, organizations expect accounting systems to actively inform strategy, manage risk, and support real-time decision-making. In banking, for example, accounting data feeds into credit risk models, capital adequacy assessments, and regulatory reporting. In corporate environments, it informs performance dashboards, cost optimization initiatives, and investment planning. My research reflects this evolution by examining how accounting integrates with analytics, AI, and digital infrastructure. Industry leaders increasingly view accounting not as a retrospective function, but as a forward-looking system that helps anticipate risks, allocate resources efficiently, and respond to uncertainty.

Q2: AI-driven credit decision automation is a major theme in your work. Why is this particularly critical for the banking and financial services industry?
Hosne Ara Mohna: Credit decision-making lies at the heart of banking profitability and stability. Traditional credit assessment approaches rely heavily on financial ratios, collateral valuation, and manual judgment, which can be inconsistent and slow. With rising loan volumes, digital banking platforms, and competitive pressure, these methods are no longer sufficient. My research explores how AI-driven predictive analytics can enhance credit decisions by incorporating broader data sources—transaction behavior, repayment patterns, and behavioral indicators—into structured decision frameworks. For banks, this means faster approvals, improved risk classification, and reduced non-performing loans. However, I consistently emphasize that automation must be transparent and explainable, especially in regulated environments. Industry adoption depends not just on performance gains, but on trust and accountability.

Q3: How have industry professionals, particularly bankers, responded to the ideas presented in your research?
Hosne Ara Mohna: Industry response has been cautious but increasingly receptive. Bankers and risk managers recognize the limitations of purely traditional models, especially in volatile economic environments. At the same time, they are rightly concerned about regulatory scrutiny and reputational risk. What I have observed is that industry professionals are far more receptive to research that addresses implementation realities—such as data governance, explainability, and auditability, rather than focusing solely on algorithmic accuracy. When research acknowledges regulatory constraints and professional judgment, acceptance grows. This is why my work consistently emphasizes governance frameworks alongside technical models.

Q4: You frequently discuss behavioral indicators in credit risk. How does this help industry practitioners make better decisions?
Hosne Ara Mohna: Behavioral indicators add a critical layer of insight that traditional financial metrics often miss. Borrower behavior, how individuals or firms manage cash flows, respond to stress, or interact with financial institutions, can provide early warning signals of risk. For industry practitioners, incorporating behavioral data improves early intervention strategies. Banks can identify at-risk accounts sooner and apply corrective measures such as restructuring or targeted monitoring. In highly competitive markets, this approach also supports responsible lending by aligning credit decisions with real borrower behavior rather than static assumptions.

Q5: Data engineering and cloud-based architectures are recurring topics in your research. Why are these issues so important for industry adoption?
Hosne Ara Mohna: In industry, analytics initiatives often fail not because of poor models, but because of weak data infrastructure. Fragmented systems, inconsistent data definitions, and manual processes undermine even the most sophisticated analytics. My research on AI-ready data engineering pipelines focuses on how organizations can structure data flows to ensure reliability, scalability, and auditability. For industry, this translates into faster reporting cycles, stronger internal controls, and more confident decision-making. Cloud-based architectures further enable organizations to scale analytics capabilities without excessive capital investment, which is particularly important for banks and enterprises in emerging economies.

Q6: Enterprise reporting and dashboards are another area you emphasize. Why are these tools so valuable for executives and managers?
Hosne Ara Mohna: Executives operate under time pressure and uncertainty. Traditional financial reports are often lengthy, static, and difficult to interpret quickly. My research on data visualization focuses on transforming financial and operational data into intuitive dashboards that highlight key risks, trends, and performance indicators. In industry settings, effective dashboards improve situational awareness, align departments with strategic goals, and support faster responses to emerging issues. When designed correctly, visualization tools reduce cognitive overload and help decision-makers focus on what truly matters.

Q7: What are the biggest organizational challenges companies face when adopting AI and analytics in accounting functions?
Hosne Ara Mohna: The biggest challenges are cultural resistance, skills gaps, and change management. Many professionals fear that automation will undermine their expertise or replace judgment with algorithms. There is also a shortage of professionals who understand both accounting principles and analytics. My research suggests that successful adoption requires gradual integration, user education, and transparent systems. When employees see analytics as a support tool rather than a threat, acceptance improves. Industry leaders must invest in people alongside technology to ensure sustainable transformation.

Q8: How does your research address regulatory compliance and governance concerns in industry?
Hosne Ara Mohna: Regulatory compliance is central to accounting and financial analytics, especially in banking and public finance. My research emphasizes explainable AI, documented data pipelines, and clear governance structures. These elements ensure that decisions can be audited, justified, and defended to regulators and stakeholders. For industry, this approach reduces compliance risk while enabling innovation. Rather than viewing regulation as a barrier, my work frames governance as an enabler of responsible analytics adoption.

Q9: You have also examined public-sector reform and political economy. How does this research connect with industry needs?
Hosne Ara Mohna: Public-sector accounting reforms shape the regulatory and institutional environment in which industries operate. Understanding political economy dynamics helps organizations anticipate policy changes, compliance requirements, and governance expectations. My research in this area provides insights into how financial transparency and accountability mechanisms influence institutional performance. For industry, this knowledge supports better regulatory alignment and more informed strategic planning, particularly in emerging markets.

Q10: Once research-based systems are implemented, how do industry professionals typically respond over time?
Hosne Ara Mohna: Initial skepticism is almost inevitable, particularly among experienced professionals. However, acceptance grows as systems demonstrate consistency, reliability, and transparency. Over time, many professionals begin to rely on analytics as a decision aid that enhances, not replaces, their expertise. In successful cases, analytics becomes embedded in daily workflows, shifting organizational culture toward evidence-based decision-making.

Q11: What future industry-focused research directions are you planning to pursue?
Hosne Ara Mohna: My future research will prioritize empirical studies of AI adoption in banking, corporate accounting, and public-sector finance. I am particularly interested in ESG reporting systems, sustainability analytics, and digital governance frameworks. These areas are becoming critical for industry competitiveness, investor confidence, and regulatory compliance.

Q12: What advice would you give to industry leaders navigating the transition toward data-driven accounting and analytics?
Hosne Ara Mohna: Industry leaders should approach this transition strategically rather than reactively. Technology alone is not enough. Success depends on aligning analytics initiatives with organizational goals, investing in talent development, and fostering a culture of transparency and learning. Accounting professionals who embrace analytics will play a central role in shaping future organizations.
Hosne Ara Mohna’s work demonstrates how accounting research can directly influence industry practice by addressing real-world challenges of adoption, governance, and trust. Her industry-focused perspective underscores a broader transformation underway—one in which accounting evolves into a strategic, analytical, and decision-centric function. As organizations increasingly rely on data-driven systems, her research offers a roadmap for responsible and effective implementation in banking, enterprise management, and public institutions.