CREDIT RISK SCORING : Determine creditworthiness and make better decisions
Perspective:
Managing credit risk is always a complex problem to solve with ever changing market volatility and customer demographics. Here at iSteer, we help our client realize the potential of AI & ML in risk evaluation of their customer credit worthiness and lending personalization using the credit risk models, not only limited to user behavior but by adding geo-political and economic status of the terrain of consumers.
Business Challenges in Consumer Loans
Archaic form of risk evaluation:
Perhaps paper based, or traditional risk modelling techniques are resource intensive and resulting to many denials.
Virtual Data Layer:
Credit firms establishing centralized virtual data store combines omni-channel data leveraging SOA principles such as decoupling, reuse, and agility with key information governance principles, such as abstraction, shared semantic models and data standards, to enable IT to build and deploy a layered, enterprise-wide data architecture, this serves as a unified, enterprise-wide view of customer, demographics, Bureau, loans, marketing, utilities and other “Alternate data”
No utilization of “Alternate Data”:
Organizations not realizing the value borrower’s current situation or other extenuating factors, such as demographics, Utilities, Insurance details, resulting to loosing borrowers to competition business.
Individualized Approach:
Lack of more granular and individualized approach limiting the business not to oer the differential pricing of interest rates Omni-Channel experience
Lack of cohesion in the organization to treat th omni-channel borrowers and lack of providing the customer 360, leading to customer attrition. A data foundational layer such as data lake powered by TIBCO can be a solution for managing the disparate data coming from various channels for its correctness, completeness, accuracy and provision of real-time data services.
The Proposed Solution:
A data foundational layer such as data lake powered by TIBCO can be a solution for managing the
disparate data coming from various channels for its correctness, completeness, accuracy and provision
of real time data services.
Virtual Data Layer :
Credit firms establishing centralized virtual data store combines omni-channel data leveraging SOA principles such as decoupling, reuse, and agility with key information governance principles, such as abstraction, shared semantic models and data standards, to enable IT to build and deploy a layered, enterprise-wide data architecture, this serves as a unified, enterprise-wide view of customer, demographics, Bureau, loans, marketing, utilities and other “Alternate data”
Enterprise Data Lake
An enterprise data lake combines streaming and interactive analytics and operates on based huge volumes of the structured, semi-structed and unstructured data pertaining to this solution , in a single easy-to-manage distributed cluster. Helps to persist the data and run heavy machine learning risk models to , This can be an optional data layer and iSteer recommends when there are heavy analytical work loads should be considered on vide varieties of data
Data science platform
This layer anchors as advanced analytical engine for the model selection, model training , configuration and create necessary workflows. The probability of the default score, customer credit risk profiling , customer segmentation and many more outcomes will be produced using state-of-the-art-data science platform allows organizations to expand the data science deployments across the organizations with flexible authoring and deployment capabilities/
Collaboration, Crowdsourcing, Governance: Define the future of data cataloging
iSteer’ s solution leverages the TIBCO Omni-Gen platform offers a robust, full-featured
data catalogue system encourages collaboration and crowdsourcing with capabilities
such as ratings, reviews, annotations, lineage, deprecations. This is the
human-machine interface that breaks down the organization silos and fosters the
culture of sharing- data sharing, knowledge sharing, process sharing, analysis sharing.
The solution becomes data epicentre connecting people, data, and use cases to meet
and exceed the enterprise business challenges.
Our solution addresses the key features of accessing heterogeneous data across the
business, operational & field systems, and visualization against a backdrop of spatial
frameworks and provide meaningful contextual analysis. Yet this huge data is often
trapped in individual department silos throughout the enterprise. With numerous
disparate information technology (IT) as well as operational technology (OT)
software systems, changes to one system are often not adequately reflected in the
others. It becomes very crucial to define the critical data assets by crowdsourcing
and collaborating among business & technological teams to be able to derive
meaningful business information from the data. The goal of the comprehensive
solution is to gather and consolidate metadata, data quality, data lineage, rule
management from a variety of sources and displays it in a timely and meaningful way
to the business & technical users for driving your digital transformation initiatives
DO YOU HAVE THESE CHALLENGES?
Disparate Data Sources:
When the information exists in separate silos and never fully comes together, could be
holding your data or digital transformation initiatives, particularly analytical needs.
Data Trustworthiness:
Increased need of data sharing among multiple business units and organizations,
and you cannot define its trustworthiness or quality of the data.
Data Inventory:
Unavailability of catalogue of the data assets, data lineage and rules, holding up your
downstream system requirements.
Data Governance:
Lack of data governance counsel, no ownership on the data.
Data Compliance:
No central place to organize and retrieve information in a manner that helps your
organization to comply with regulations such as GDPR.
COLLABORATION AND CROWDSOURCING WITH DATA CATALOGUE AND DATA GOVERNANCE:
Our solution provides a clean separation of data discovery, data lineage, integration,
data quality, and data governance tiers. It features a pluggable framework to allow
required integrations, functionalities, and features to expand over time. Our crowd sourcing solution enables almost everybody in your organization with equal
and full rights and is encouraged to participate. Everyone has self-service access to
add key data elements, propose business metrics, flag a data type, request data
sharing, and more. Powered by TIBCO’s Omni-Gen platform that includes appropriate
clean and control tools (e.g., Data Quality, Rule Management, workflow, commenting,
suggestions, machine learning, etc.) you can grow a very collaborative community
including norms that provide a very resilient barrier against total chaos.