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Ecosystem Risk Score for Data-Backed Credit Decisions

What is Ecosystem Risk Score (ERS)?

Ecosystem Risk Score – powered by Corestrat’s Model.ai – is a cutting-edge tool that helps you harness the power of alternate data to assess creditworthiness. Analyzing a variety of non-traditional [ecosystem usage] data provides a more comprehensive view of a borrower’s financial health and helps you make more informed and profitable credit decisions.

We employ advanced analytics to conduct consumer behavioral analyses on the usage pattern of an interconnected set of services offered to users and make customer-persona-relevant predictions that are targeted and risk-informed.

Hover over the below examples of how ERS can help you harness the potential of your alternate/ecosystem usage data to make profitable credit decisions.

Use Cases & Benefits of ERS

Unlock the True Potential of Superapp Ecosystem Data Through Predictive Intelligence To Drive Better Business Decisions

Introducing Ecosystem Risk Score - powered by Model.ai. Digital banks and fintech businesses can now effectively use alternative data (user demographics, click data, etc.) to achieve 3x credit approvals while maintaining the same levels of risk.

Ecosystem Risk Score with a Unified Data Layer From Various Sources

Many of the ML solutions in the market today are found to be sub-optimal as they are built on disparate data that aren’t unified at a user/customer level. At Corestrat, we believe that the critical first step in developing a robust and predictive Ecosystem Risk Score (ERS) is to orchestrate a unified data layer across partner ecosystem data sources. Click here to learn more about ERS and how Corestrat can help you conceptualise, develop and deploy an effective ERS model for your business.

Ecosystem Risk Score (ERS) for Reduced Customer Acquisition Costs

Ecosystems Risk Score (ERS) presents several clear strategic benefits. The most important benefits include ERS’s ability to meaningfully reduce customer acquisition costs because it enables predictive targeting on a large scale by providing an analytically whitelisted pool of pre-select users of the ecosystem with transparent limits and committed price points. ERS can create significant value by identifying unserved customers and cross-selling products and services based on ecosystem users’ preferences, usage patterns, and financial strength.

ERS for Customer Churn Reduction

ERS can help transform how you engage with users of your ecosystem, enabling you to generate product offerings that meet specific customer needs and offer frictionless experiences that reduce customer loss and churn. Corestrat employs advanced analytics to conduct consumer behavioural analyses on the usage pattern of an interconnected set of services that are offered to the users to proactively identify silent attritors.