Airtel Payments Bank spearheads the adoption of cutting-edge technology to enhance their risk management practices. Utilising Artificial Intelligence (AI) and Machine Learning (ML), they dynamically elevate the efficacy of risk assessment and management, underscoring their commitment to customers, shares Pradeep Rangi, Chief Risk Officer, Airtel Payments Bank in an exclusive interaction with Srajan Agarwal of Elets News Network (ENN).
In the constantly evolving landscape of digital banking and fintech, what innovative strategies Airtel Payments Bank is adopting under your leadership to manage and mitigate risks from emerging technologies and conduct?
Airtel Payment Bank’s ability to innovate, adapt to change and embrace-evolving technologies is rooted in a commitment to fostering a robust risk culture and upholding high standards of conduct. These are integral components of our Enterprise Risk Management Framework, providing guiding principles for colleagues and facilitating integrated risk discussions across the Bank and its three lines of defence. Digitalisation and technological development remain key items on the Bank’s agenda.
We continue to ensure that our control frameworks and risk appetite evolve accordingly to keep pace with new growth plans, product innovations and use of emerging technologies. We prioritise promoting a healthy risk culture by rewarding risk-based thinking, challenging norms, and creating an environment that encourages transparent communication of risk concerns. Senior management delivers conduct outcomes and maintains a zero-tolerance stance towards misconduct. Our unique footprint, diverse experiences, capabilities, and culture distinguish us, empowering us to identify risks and seize opportunities for our business, customers, and markets.
Could you describe your approach to implementing an integrated risk management strategy at Airtel Payments Bank? How do you ensure that this strategy effectively aligns with the bank’s overall business objectives while addressing the unique challenges of the banking sector?
Our approach to implementing an integrated risk management practice at Airtel Payments Bank is centered on aligning risk practices with the bank’s strategy and Risk Appetite. Our Enterprise Risk Management Framework (ERMF) structures risk management, addressing existing risks in line with our Risk Appetite. Principal risks inherent to our banking strategy are formally defined within this framework, and supported by policies, standards and procedures for achieving control objectives.
Our proactive approach involves impact analyses on risks from growth plans, strategic initiatives, and banking model vulnerabilities. This informs our strategy review process, allowing us to adapt to emerging challenges. Our integrated risk management strategy therefore is a dynamic framework contributing to business objectives in the banking sector’s and technology landscape.
In the context of Airtel Payments Bank, how are Artificial Intelligence and Machine Learning being utilised to enhance risk assessment and management? Can you share some examples where AI and ML have significantly improved risk prediction or mitigation?
Airtel Payments Bank spearheads the adoption of cutting-edge technology to enhance our risk management practices. Utilising Artificial Intelligence (AI) and Machine Learning (ML), we dynamically elevate the efficacy of risk assessment and management, underscoring our commitment to customers. Our advanced fraud risk models, supported by algorithms, scrutinise extensive datasets in real-time, enabling us to promptly identify patterns and anomalies. Take, for instance, our look-alike models, ensuring the prompt identification of vulnerable customers and enabling adaptive authentication for customers safeguarding. Additionally, through network effect models encompassing device intelligence and multiple parameters, we proactively track and mitigate evolving threats, enabling timely actions, in several cases, even before law enforcement agency involvement or customer complaints. This dynamic strategy reinforces our dedication to delivering secure and equitable banking experiences.
Emphasising responsible technology adoption, Airtel Payments Bank has implemented robust AI and ML frameworks, guided by meticulous assessments and aligned with key principles prioritising fairness, transparency, and accuracy.
How does the understanding of risks evolve across different stages of the AI life cycle?
Risk in the AI lifecycle is a dynamic process, and early evaluations of risk would usually diverge from later stages, and potential latent risks gaining prominence as AI systems evolve. This complexity is heightened by the varied risk perspectives held by different AI actors. Consider this scenario, a developer offering pre-trained AI models might view risks differently than a deployer responsible for using that pre-trained model in a specific case. This therefore requires a very comprehensive AI risk management framework which not only provides tools and standards but also enables organisations to overcome contextual risks by enabling collaboration, ongoing feedback loops and shared responsibility frameworks between developers and deployers.
In the current landscape, how do risk management skills stand out as essential competencies, considering the interconnected nature of risks, the influence of technological integration, and the expanding regulatory landscape?
Navigating with challenges like cybersecurity threats, technology advancements to regulatory complexities, shows how important risk management skills are. It also emphasises that risk management should be a part of how processes, products and customer lifecycles are proactively thought through for inherent and emerging risks and designed. In our ever-changing risk landscape, these hard technical skills, along with being adaptable, emotionally smart, and good collaborators, are vital for effective risk management. Combining technical expertise with empathy, critical thinking, and resilience helps managers foresee trends, handle inherent and emerging risks, and support growth plans in a dynamic business setting.
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 and Machine Learning (ML), they dynamically elevate the efficacy of risk assessment and management, underscoring their commitment to customers, shares Pradeep Rangi, Chief Risk Officer, Pradeep Rangi in an exclusive interaction with Srajan Agarwal of Elets News Network (ENN).){kind=link}