India’s banking sector transforms supplier management with AI and regulatory vigilance

India’s banks are harnessing AI-driven supplier risk management to enhance operational resilience, navigate regulatory demands, and mitigate systemic vulnerabilities amid a rapidly evolving digital landscape.

According to the original report by Arjit Agarwal, supplier management in India’s banking sector has moved well beyond routine compliance and documentation to become a strategic pillar of operational resilience and customer trust. Procurement teams are now expe...

cted to integrate AI-enabled supplier risk platforms with core systems such as ERP, finance and compliance databases to deliver continuous, real‑time oversight of vendor reliability, service delivery and cybersecurity posture. That shift, Agarwal argues, reframes procurement from a transactional function into a forward‑looking capability that can anticipate disruption and optimise value.

Regulatory pressure and recent guidance have crystallised that imperative. The Reserve Bank of India (RBI) has expanded its supervisory focus on third‑party risk: a 2024 guidance note urged all regulated entities to strengthen operational risk and ICT risk programmes, mandate due diligence before engaging service providers, make service providers contractually liable for subcontractor risks and develop incident response and recovery plans aligned with each entity’s risk tolerance. Industry data shows these directions were driven by the financial sector’s growing reliance on external vendors and the need to preserve continuity during cyber and operational incidents.

More recently, RBI governors have underlined both the promise and the peril of rapid digital adoption. In February 2025, RBI Governor Sanjay Malhotra warned about a rise in digital payment frauds tied to cyber incidents and deceptive domains; the bank announced the roll‑out of exclusive internet domains such as “bank.in” and “fin.in”, with registrations managed by the Institute for Development and Research in Banking Technology, as a measure to reduce lookalike‑domain fraud. In October 2024, former Governor Shaktikanta Das cautioned that heavy reliance on a narrow set of AI providers could create concentration risks and opacity that amplify systemic vulnerabilities. Those concerns were echoed in August 2025 when an RBI committee recommended a comprehensive framework, FREEAI, to foster indigenous AI models, create audit and assurance mechanisms, and establish a multi‑stakeholder body to oversee AI adoption in finance.

Against this regulatory backdrop, the adoption of AI for supplier risk management presents both operational benefits and governance challenges. AI systems can ingest thousands of signals, financial statements, public filings, threat intelligence, social sentiment, and generate near‑real‑time supplier risk scores. According to the original report, these scores give banks early warning of operational weakness, compliance lapses or data security issues. At the same time, RBI commentary and independent analyses stress the danger of overreliance on opaque algorithms and concentration around a few technology providers, which may increase systemic risk if those providers fail or are compromised.

Practitioners therefore recommend a hybrid model that combines machine intelligence with skilled human oversight. Automated monitoring and analytics can surface anomalies at scale; experienced analysts are needed to interpret context, validate alerts and engage suppliers constructively. Agarwal highlights that not every dip in a vendor’s score indicates a critical failure, it could reflect a temporary event, so human judgement remains essential to avoid false positives and preserve productive supplier relationships.

Beyond risk detection, AI insights can drive measurable business value. Procurement teams are using analytics to identify cost optimisation across direct and indirect categories, refine specifications, and pursue strategic supplier consolidation to reduce single‑vendor dependency and geopolitical exposure. Sustainability and ESG metrics are increasingly incorporated into sourcing decisions, extending risk management to labour, ethical and environmental considerations. Data‑driven workflows also free procurement professionals from routine administration so they can concentrate on strategy and supplier development.

Legal and policy changes further shape how banks must deploy these tools. The Digital Personal Data Protection Act and evolving cybersecurity laws place obligations on data handling and localisation that affect how banks collect and share supplier information. Commentary on emerging legal challenges warns of new fraud vectors, phishing, deepfakes, ransomware, that heighten the need for robust contractual, technical and operational safeguards when outsourcing critical services.

Implementation, however, is uneven and subject to meaningful trade‑offs. AI models require quality data, explainability and auditability; the RBI committee’s recommendations emphasise building indigenous AI capacity and creating audit frameworks so models can be stress‑tested and governed. Industry participants have also highlighted the need to avoid supplier concentration in technology stacks and to ensure that third‑party resilience aligns with a bank’s own recovery objectives.

The practical implications are clear. Banks must:

• embed continuous, AI‑enabled monitoring across vendor lifecycles while preserving human decision‑rights to interpret and act on alerts;
• align supplier contracts with regulatory expectations on subcontractor liability, incident response and data protection;
• pursue diversification and due diligence to minimise concentration risks in technology and critical services;
• incorporate ESG and sustainability metrics into procurement frameworks; and
• invest in explainability, audit trails and local capacity for AI to satisfy both operational and supervisory scrutiny.

Ultimately, supplier management in financial services is rapidly evolving into an outward‑facing risk function that intersects technology, compliance and strategy. When combined responsibly, AI orchestration, rigorous governance and human expertise, it can move institutions from reactive remediation to proactive prevention, strengthening resilience in a landscape of rising cyber threats and regulatory expectations. The institutions that balance technological advantage with clear oversight, contractual discipline and regulatory alignment will be best placed to sustain operations, protect customers and preserve public confidence as India’s banking sector deepens its digital transformation.

Source: Noah Wire Services