Throughout history, the very design and structure of banking systems rendered the economics of small loans unviable. It is the increasing focus on 'financial inclusion' that marked a shift from traditional banking practices, giving rise to the idea of ‘differentiated banking’. Small Finance Banks (SFBs) are an embodiment of this stylised thinking. 

Small Finance Banks have emerged as a recent innovation in the Indian banking structure, a direct outcome of the Reserve Bank of India's (RBI) efforts to promote niche banking. They are tasked with the responsibility of offering basic banking services to small business units, small and marginal farmers, micro and small industries, and unorganised sector entities in unbanked and under-banked regions.

In this context, the new SFBs face multiple challenges as they strive to establish and sustain a new, differentiated business model. They have the dual responsibility of building a low-cost liability portfolio while balancing regulatory compliances. Essentially, SFBs must embody the stability and credibility typical of traditional banks, along with the agility and innovation characteristic of fintech companies, simultaneously. 

The general consensus seems to be that this is best achieved through a technology-first approach, and rightly so. 

Technological prowess of Small Finance Banks serves as a reliable bulwark to competitive threats. It empowers them to maintain a low-cost ops model, effectively catering to small tenor credit requirements of underserved and unserved markets — a rather large addressable market. 

Essentially, what they have before them is a massive green field desperate for credit and convenience. But for the field to yield returns, you need a differentiated banking model enabled by technology so as to prioritise customer centricity and launch niche products (that reflect a deep understanding of  unserved/underserved segments) at scale. 

This explains why all 12 SFBs in India are actively embracing automation technology and digitisation. Furthermore, eight out of 12 SFBs openly talk about the need for an ‘agile business rules engine’. A smart workflow engine that significantly reduces turnaround time (TAT) to launch new lending policies at scale, is beyond doubt, crucial for serving niche markets effectively and efficiently. 

While some have built this technology (business rules engine) in-house, others have partnered with specialised vendors. For now, let's steer clear of the build v/s buy debate and shift our attention to the primary growth enablers for SFBs and the essential features that a business rules engine must possess to facilitate these growth factors. So, what exactly are these growth enablers?

• Large addressable market

• Well-diversified asset portfolio

• Customer centricity with a deep understanding of unserved/underserved segments

• Strong retail liability portfolio with a strategic distribution network

• Customised credit assessment procedures for effective credit risk management

• Technology as an enabler to drive operating procedures

1. How Sentinel helps tap into a large market, effectively

• Scalability : Sentinel provides a systematic and automated framework for credit decisioning, enabling efficient scaling of operations to cater to a larger audience without compromising on decision accuracy or speed. It is designed to deal with increasing complexity and volume, without compromising on decision accuracy and speed. 

• Flexibility: Sentinel offers a no-code graphical interface for workflow automation; wherein you can adapt rules to different segments within the market, allowing for tailored approaches that suit diverse customer needs. 

• Multiple data sources for tailored decisioning: 

Sentinel empowers lenders and fintechs to combine traditional data sources (such as bureau and bank data) along with proprietary data, scorecards, and alternative data sources for use in credit underwriting. 

2. How Sentinel supports in creating a well-diversified asset portfolio

• Risk management: Sentinel connects risk teams with a host of risk analytics such as data source-level demographic data, user- & funnel-level analytics, rule- & portfolio-level analytics. 

• Live simulation testing : Sentinel allows risk teams to run simulations — either on select users or FinBox’s historical user profiles — and generate analytics to understand the potential impact of the changes before making a policy/rule change live. Additionally, Sentinel has features such as Canary Mode or Champion/Challenger to test and run policies in a controlled live environment, enabling risk teams to make more informed decisions and enrich their strategies. 

3. How Sentinel helps SFBs quickly adapt to evolving customer expectations

• Orchestrate end-user journey 

For SFBs to sustain its differentiated model, it is important that they prioritise customer experience. 

The progress of a potential borrower from one screen to another is dynamic in nature as it depends on pass/fail outcomes at multiple touchpoints. Implementing this in code required significant development effort. 

If risk teams at SFBs had control over end-user journeys, they’d be able to create custom experiences, wherein premium customers, for instance, have fewer checkpoints. With Sentinel’s journey orchestration capabilities, the  lender could free up its engineering resources and stitch multiple journeys with simple drag-and-drop of modules connected by if-else conditions.

4. How Sentinel supports build strong retail liability portfolio with a strategic distribution network

• 360° view of your retail portfolio

See why a user was approved or flagged, and optimise your workflows for maximum performance and optimal performance

• Control over end-user journey on even partner channels 

Irrespective of where the loan originates, lenders can use Sentinel’s journey orchestration capability to create custom experiences.

5. How Sentinel helps with customised credit assessment procedures 

• Workflow automation : In digital lending, each stage — from onboarding to disbursal — can have multiple policies. For eg; you may have policies A, B, C, and D — if a borrower fails certain conditions of policy A, B runs, and when B fails, C runs, so on and so forth.

Over time, workflow analytics help risk teams understand optimum methods of credit risk assessment for various risk cohorts, allowing them to streamline the credit decisioning process for maximum approval at minimum cost — all without raising risk limits. 

6. How Sentinel helps drives down operating costs

• Free up engineering resources:

Sentinel unburdens banks from hosting and maintenance of rules engine, thereby considerably reducing IT cost. Additionally, its policy studio is designed such that risk teams don’t have to write a single line of code — whether it is to update a rule or create a whole new workflow. Banks don’t have to spend time and money integrating with multiple data vendors for decisioning. FinBox also provides support with scorecarding, thereby leaving only policy creation to banks.

To know more about how Sentinel can help, schedule a demo with our experts.