While most companies tend to focus on launching new businesses, the real value comes from being able to scale them up. An analysis of U.S. venture-capital data showed that two-thirds of value creation is achieved through scale-ups. According to Mckinsey , VC firms have a clear understanding of that value. Of the $135 billion invested by US VC firms in 2018, 63 percent was deployed to enable successful start-ups to scale their product or service (series C funding and later). 

If you look at the business of lending, scalability remains one of the top challenges. Manual processes, legacy systems, and limited resources trap lenders in a vicious cycle of stagnation. Those that manage to break free from it, hit their limits when loan portfolios expand to an overwhelming volume or when they fail to keep up with constantly evolving regulations, compliance requirements, and customer expectations.

That’s not all. As lenders scale their operations, managing risk becomes excruciatingly difficult. 

What I am about to suggest may seem obvious and trite. Nevertheless, all these problems have one solution — technology. Having built digital credit infrastructure for several leading lenders, we at FinBox are all too familiar with the scalability challenge. We have been invested in designing a workflow and structure for the digital lending business that allows for scalability. And the outcome is Sentinel. 

Sentinel is a scalability- first business rules engine (BRE) powered by big data analytics. It is designed for rapid growth and strengthens unit economics along the way. Here’s how. 

Data is centralised within Sentinel to provide a comprehensive and unified vview of loan portfolio, performance of individual business rules and policies, customer activity, and more. This enables better growth-oriented decision-making. Let’s delve deeper into how Sentinel helps identify business opportunities and process improvements. 

• Macro analytics in a BRE: It stores all structured and unstructured data that was ever routed through the BRE in an anonymised and encrypted format and deduces from it macro-level trends such as demographic, behavioural, and other multi-faceted data patterns. For instance, you can generate demographic trends and patterns at individual data source level or embed feedback loops, say, delinquency data to optimise your risk buckets — whether it is for minimising risk, maximising approval rates, or both. Based on these trends, you can even set alerts; for e.g. ceilings or floors on loan amounts.

• Risk reporting & analytics in a BRE:   Sentinel gives business users visibility into why a borrower was flagged, approved, or rejected. Tt ranks lending policies based on performance and gives insights at individual policy- and rule-level. Further, it offers funnel-level analytics to help track failure points and identify areas of improvement in a lending workflow. For instance, if the decisioning outcomes for a specific user base using bureau data alone and bureau + bank + GST are no different, why use three in the place of one, only to add cost. These kinds of insights can be easily derived from funnel-level analytics, allowing you to sequence workflows for maximum output and minimum cost.

  
  

  In case of lack of historical data to test new growth strategies, you remain one step ahead with Sentinel. Its features such as Canary testing and Champion/Challenger empower you to test new strategies in a live environment without affecting your daily operations. 

Sentinel provides a comprehensive set of no-code tools and features to automate processes, improve efficiency, and enable businesses to focus on value-added activities. Wondering how no-code automation enables growth? One, it speeds up operations. Two, it enables your business to handle increased volumes efficiently. Three, it equips you to quickly adapt and respond to changing business requirements. 

• Access to multiple data sources : Sentinel offers access to a host of data sources, including a range of powerful alternative data. Besides connecting lenders with data sources such as bureau data, device data, GST data and bank data via FinBox’s proprietary products, Sentinel also empowers users to integrate external data sources via third-party APIs. It also has an input feature that allows users to include custom data into the decisioning process. 

• Automated decisions and workflows : Sentinel has what is called a Policy Studio. It’s an easy-to-use tool that allows business experts to automate complex business logic without having to code. A business user can use natural language end to end to do two things using the Policy Studio;

(i)Automate underwriting, onboarding, and fraud decision

(ii) Sequence a range of actions in a workflow. For example, sequencing a bureau data-based policy followed by a bank data-based policy offers potential borrowers  a better chance at approval while ensuring a seamless application process. l. 

The beauty of Sentinel is that it scales your business, and scales alongside your business. How does it achieve this? Firstly, it enables lenders to expand their customer base by identifying new customer segments within their risk tolerance, effectively widening the lending funnel. Secondly, it remains robust as the volume of data and the complexity of decision-making requirements grow. To know more about how Sentinel can solve your scalability challenges, get in touch with us .