Quantexa

Advanced Risk Insights Powered by Network Analytics

EY and Quantexa help financial institutions prepare for risk as global economic uncertainty persists with advanced risk insights capabilities.

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Advanced Risk Insights Powered by Network Analytics

EY and Quantexa help financial institutions prepare for risk as global economic uncertainty persists with advanced risk insights capabilities.

Advanced Risk Insights Powered by Network Analytics

In an uncertain world, it is imperative for banks and financial institutions to prepare for risks by developing systems that can predict, and therefore mitigate, upcoming risks. When developing “future-ready” systems, a crucial aspect to long-term success is the ability to harness data that provides a complete, 360-degree customer view. However, this capability is currently challenged by fragmented systems and poor-quality data, missed risk drivers, manual processes, and restrictive legacy systems.

By harnessing and connecting data from a wide range of internal and external sources, it is possible to identify a wider pool of risk drivers to support our clients building more advanced predictive risk models and insights. Here, we explore how clients are successfully utilizing these risk models to deliver tangible improvements in their risk management capabilities.

Using connected data networks to power advanced analytics.

Quantexa’s Decision Intelligence Platform allows financial institutions to connect internal and external data sources and construct networks, even in cases where data exists in silos or suffers from quality issues. Through this process, clients are able to create a full 360-degree view of their customers and their ecosystem to deliver a comprehensive basis for analytics and insights across a wide range of risk use cases.

Quantexa’s Decision Intelligence Platform includes three core capabilities:

  • Entity Resolution: matching and consolidating data to identify and link related entities within large datasets.

  • Networks: identifying relationships and connections between entities to uncover hidden patterns.

  • Analytics and insights: leveraging the network ecosystem with machine learning and AI techniques to generate actionable insights from complex and diverse datasets.

Decision Intelligence technology has already been implemented and proven to deliver improvements combatting financial crime, and is now increasingly being used to improve other areas of risk.

Building capability that delivers benefits across multiple use cases

Utilizing Decision Intelligence technology, EY teams in collaboration with Quantexa have developed an advanced risk insights capability that can be applied at scale to commercial credit portfolios. The power of this capability lies in use of networks, a highly connected representation of a customer, their key risk information, and their relationships. The Decision Intelligence technology underpinning this enables internal, external, structured, and unstructured data to be combined, breaking down existing silos. This creates a consistent basis for analytics, insights, and automation across a wide range of risk use cases including: (i) customer intelligence, credit decisioning, and early warning analytics, (ii) scenario planning and stress testing, (iii) financial outcomes, and (iv) capital optimization.

For example, this capability could help banks deliver significant business value for credit risk early warning:

  1. Up to 15% decrease in Expected Credit Loss (ECL).

  2. Identification up to 18-24 months prior to risk event.

  3. Up to 20% increase in operational efficiency.

The views reflected in this article are the views of the author and do not necessarily reflect the views of the global EY organization or its member firms.

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Decide With Confidence: The Executive’s Guide to Decision Intelligence
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The increasing significance of Context in AI decisions

Quantexa’s Data & AI Innovation Forum brings together Australia’s Data, AI and Analytics leaders and practitioners to explore how financial institutions, insurers and public sector agencies are using connected data, contextual intelligence, and trusted AI to make better decisions at scale.