Blog 110: Tech systems within the lending value chain in India’s DPI era

Indian lending moved from paper-heavy silos to an integrated, API-first framework. This is powered heavily by India’s Digital Public Infrastructure (DPI).

Now, let us identify the key tech systems within this lending value chain. Key players within the Indian lending ecosystem comprises of commercial banks, NBFCs, HFCs, Fintechs etc.

1. Sourcing & Customer Acquisition (Front Office): This layer captures the lead, builds the digital relationship, and acts as the entry gate for the borrower.

a. Customer Relationship Management (CRM): Enterprise systems that track lead pipelines, assign tasks to agents, and orchestrate omnichannel interactions.

Some examples of Tech/Tools: Salesforce Financial Services Cloud, LeadSquared, Zoho CRM etc.

b. Embedded Finance & Marketplace APIs: Infrastructure enabling non-financial platforms (e.g., e-commerce, food delivery apps) to offer instant credit like Buy Now Pay Later (BNPL) or Merchant Cash Advances.

Some examples of Tech/Tools: FinBox, Decentro, M2P Fintech etc.

c. Direct-to-Customer (D2C) Front-Ends: Web portals and mobile applications built on cross-platform frameworks allowing customers to apply for a loan directly.

Some examples of Tech/Tools: React Native, Flutter, progressive web apps (PWAs) etc.

2. Onboarding & Identity Verification (Regulatory Technology Layer or RegTech Layer): This segment transforms traditional physical verification into instant, compliant digital checks heavily reliant on the India Stack.

a. eKYC & Video KYC (V-KYC) Platforms: Core identity processing tools that leverage Aadhaar data and automated workflows. Goal is to fulfil Reserve Bank of India (RBI) compliance with minimal drop-off rates.

Some examples of Tech/Tools: Signzy, HyperVerge etc.

b. Verification APIs: Single-point integrations used to query government and regulatory registries in real time.

Some examples of Tech/Tools: Digio, Karza Technologies etc.

c. Document AI & Fraud Engines: Machine learning models that extract and analyse data from unstructured documents (e.g., salary slips, property papers).

Some examples of Tech/Tools: Finezza, Perfios etc.

3. Credit Underwriting & Risk Assessment (Mid-Office): Where data aggregates to calculate default probability and build alternative credit scoring models.

a. Loan Origination Systems (LOS): The orchestration engine managing the entire workflow from application entry through underwriting to final approval.

Some examples of Tech/Tools: Lentra, Nucleus Software etc.

b. Business Rule Engines (BRE): No-code/low-code environments where risk parameters, policy criteria, and multi-bureau rules are written and executed dynamically.

Some examples of Tech/Tools: Drools, Camunda etc.

c. Account Aggregator (AA) & Financial Analysers: Tools pulling structured, user-consented financial data via the RBI-regulated Account Aggregator network to execute automated bank statement and GST parsing.

Some examples of Tech/Tools: Perfios, FinBox (BankConnect) etc.

d. Credit Bureau Integrations: Real-time querying of standard Indian credit registries.

Some examples of Tech/Tools: CIBIL, Experian, Equifax etc.

e. Unified Lending Interface (ULI): The RBI's framework built to drastically reduce appraisal timelines by enabling friction-free digital access to land records, milk pourer data, agricultural statistics etc.

4. Loan Servicing & Core Management (Mid-Office): The database of record handling ledger balances, interest computations, and corporate reporting.

a. Loan Management Systems (LMS): The transactional core managing repayment schedules, moratoria, processing fees, and asset classifications.

Key Some examples of Tech/Tools: Nucleus Software (FinnOne Neo), Finflux (M2P) etc.

b. Core Banking Systems (CBS): Large-scale traditional platforms (usually at legacy retail banks) that interface directly with the LMS.

Some examples of Tech/Tools: Infosys Finacle, TCS BaNCS, Oracle FLEXCUBE etc.

c. Co-Lending Platforms: Specialised platforms built to team up NBFC originators and the big banks in real time.

Some examples of Tech/Tools: Lentra (Co-Lending Cloud), CredAble (Supply Chain / B2B Co-lending) etc.

5. Disbursements & Collections (Payment Rails): The infrastructure facilitating liquidity distribution and recurring fund recovery.

a. Disbursement & Settlement Gateways: Handling bulk fund transfers.

Some examples of Tech/Tools: RazorpayX, Cashfree, IMPS/NEFT networks etc.

b. Mandate Management Engines: Systems automating recurring debt collection via electronic mandates.

Some examples of Tech/Tools: NPCI eNACH, Digio mandate etc.

c. Digital Collection Integrations: Intermediaries pulling repayments via consumer payment interfaces.

Some examples of Tech/Tools: UPI Intent, BBPS (Bharat Bill Payment System) etc.

d. AI-Driven Delinquency & Allocation Models: Routing bad-debt portfolios to physical collection agencies (based on behavioural probability scores).

Some examples of Tech/Tools: Credgenics, Spocto etc.

6. Analytics, Governance & Reporting (Back-End): The supervisory layer ensuring financial health, regulatory reporting, and risk forecasting.

a. Early Warning Systems (EWS): Predictive analytics models tracking borrower cash flows and external industry metrics to trigger alerts before an account defaults.

Some examples of Tech/Tools: Finezza Credit Analytics, Perfios Insight etc.

b. Regulatory Reporting Software (RegTech): Platforms collecting transactional logs to auto-generate statutory regulatory artifacts required by the Central Repository of Information on Large Credits (CRILC) and RBI.

Some examples of Tech/Tools: Nelito Systems (FinCraft), IRIS RegTech etc. 

c. Data Infrastructure: Enterprise architecture supporting unified storage, real-time pipelines, machine learning etc.

Some examples of Tech/Tools: Snowflake, Amazon Redshift, Databricks etc.

To conclude, if you are looking to innovate or intervene in this value chain, you could focus on these current industry bottlenecks (this is not an exhaustive list):

1.   LOS-LMS Silos: Many institutions use an LOS from one provider and an LMS from another, creating data translation friction. Modern systems are shifting to unified data models (e.g., M2P's core lending architecture).

2.   ULI Adoption: Integrating early with the Unified Lending Interface (ULI) will give a significant time-to-market advantage for secured rural and agricultural lending products.

3.   Local Language & Voice AI: The onboarding and collection segments suffer high drop-offs outside Tier-1 cities. Integrating solutions like "Banking Bhashini" (vernacular translation AI) can optimise user conversion.

Jump to blog 100 to refer to the overall product management mind map.

I wish you the best for your journey. 😊