{"id":16971,"date":"2026-05-05T10:28:38","date_gmt":"2026-05-05T10:28:38","guid":{"rendered":"https:\/\/www.salesforce.com\/?p=16971"},"modified":"2026-05-05T10:28:40","modified_gmt":"2026-05-05T10:28:40","slug":"digital-lending-risks-in-india","status":"publish","type":"post","link":"https:\/\/www.salesforce.com\/in\/blog\/digital-lending-risks-in-india\/","title":{"rendered":"5 hidden risks slowing down digital lenders in India"},"content":{"rendered":"\n

India\u2019s digital lending volumes have grown faster than most lending operating models were built to handle. In FY 2024\u201325, fintech-focused NBFCs alone sanctioned over 10.9 crore<\/a> personal loans worth \u20b91.06 lakh crore, a clear sign of how retail credit origination has shifted to high-speed digital channels.<\/p>\n\n\n\n

This growth has not come in bursts. It has been steady and continuous.Marketplace-led acquisition, embedded credit, and app-based lending have turned loan origination into an always-on system. Underwriting, verification, compliance, and borrower communication now operate under constant pressure, not occasional peaks. <\/p>\n\n\n\n

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In the first half of FY 2025 alone, digital lenders disbursed <\/em>\u20b997,381 crore<\/em><\/a> in small-ticket personal loans, largely to borrowers entering the formal credit system for the first time.<\/em><\/p>\n\t\t<\/div>\n\t<\/div>\n<\/div>\n\n\n\n\n

At the same time, borrower patience has dropped sharply. Research across financial services shows that 61%<\/a> of customers now prefer self-service for routine interactions and tend to abandon journeys when updates feel slow or unclear. In lending, this impatience shows up immediately as drop-offs, with applicants often switching lenders within the same session rather than waiting for resolution.<\/p>\n\n\n\n

In this environment, risk no longer shows up mainly as isolated fraud cases, compliance lapses, or customer complaints. Instead, it builds up inside everyday decision flows. Borrower information sits across systems, handoffs increase under time pressure, and recovery work gets pushed aside because there is no leeway left in the system.<\/p>\n\n\n\n

How sustained pressure affects digital lending decisions in India<\/strong><\/h2>\n\n\n\n

When digital lending runs under continuous load, risk does not arrive suddenly. It appears through small coordination gaps that quietly compound over time. Five patterns tend to surface first.<\/p>\n\n\n\n

1. Fragmented borrower context across systems and partners<\/strong><\/h3>\n\n\n\n

As lending ecosystems expand, borrower data spreads across verification partners, loan origination systems, CRMs, bureau platforms, and service tools. Industry surveys show that 98%<\/a> of financial services leaders still deal with data and application silos, even in digitally mature organisations.<\/p>\n\n\n\n

Under pressure, this fragmentation slows decisions and increases error risk. Teams spend time piecing together context instead of acting on it, and approvals move forward with partial visibility rather than full confidence.<\/p>\n\n\n\n

2. Fraud exposure driven by delayed and uncoordinated signals<\/strong><\/strong><\/h3>\n\n\n\n

Fraud risk rises when identity, bureau, device, and partner signals are reviewed sequentially or too late in the lending flow. In many digital lending setups, critical checks arrive after decisions have already moved forward, creating blind spots rather than protection. Research shows that nearly two-thirds<\/a> of the data used for financial services decision-making is over a day old by the time it is applied, allowing inconsistencies to surface only after risk has moved deeper into the funnel.<\/p>\n\n\n\n

The cost of late detection is rising. RBI-cited data shows that the value of financial frauds in India reached \u20b936,014 crore<\/a> in FY25, nearly three times the previous year. When mismatches are flagged late, teams are forced into reactive reviews and reversals under pressure. Over time, this also leads to pre-approval stalling, as journeys pause to rerun checks, request additional information, or resolve conflicts that should have been surfaced earlier.<\/p>\n\n\n\n

3. Compliance gaps that surface under speed, not neglect<\/strong><\/strong><\/strong><\/h3>\n\n\n\n

India\u2019s regulatory expectations for digital lending have tightened steadily. This has led to the creation of the RBI\u2019s Digital Lending Directions, 2025<\/a>, which strengthen requirements around borrower consent, audit trails, disclosures, and data governance.<\/p>\n\n\n\n

In practice, compliance issues rarely come from deliberate shortcuts. They appear when consent is captured in one system, documents are stored in another, and approvals are processed elsewhere. Under pressure, these gaps stay hidden until audits or disputes bring them to light.<\/p>\n\n\n\n

4. Borrower experience breakdowns driven by uncertainty<\/strong><\/h3>\n\n\n\n

As lending speeds increase, borrowers expect clarity as much as velocity. When applicants cannot track progress, receive inconsistent updates, or are asked to repeat information, confidence drops quickly.<\/p>\n\n\n\n

Drop-offs rise not because lenders are slow, but because uncertainty feels risky to the borrower.<\/em><\/p>\n\n\n\n

How Agentforce supports more resilient digital lending at scale<\/strong><\/h2>\n\n\n\n

In digital lending, risk does not come from one step failing. It comes from decisions, coordination, and execution drifting out of sync as volumes rise. Fixing this requires a connected operating model, not incremental optimisation.<\/p>\n\n\n\n

Agentforce Financial Services <\/a> is built to support lending as a single decision system rather than a collection of disconnected tools.<\/p>\n\n\n\n