Current Challenges in Financial Services
The economic and financial pressures created by the current global pandemic have caused great uncertainty in established approaches to identifying the right customers and managing risk. Ironically, such episodic events are often not considered in risk models but have very large effects on such portfolios. Financial Service Providers must adapt to both avoid significant negative consequences and take advantage of available opportunities. The ability to evaluate, manage, and mitigate risk has rarely been more pressing.
Dynamic organizations are adapting their risk perspectives to try and benefit from the current situation. For example, some Financial Service Providers are working towards increasing profitability by extending credit to new and existing customers to help them overcome temporary periods of hardship. This approach involves building new Customer Segmentation Models for customer acquisition and then revising models that predict the probability of loan default. Once these models are built various numerical optimizations methods are applied that aim to maximize revenue over the lifetime of a customer, subject to specific business and regulatory constraints. . The ability to use data-driven approaches to adapt in these unprecedented times will help define the future leaders in Financial Services.
About The Event
Data and Analytics Innovations in Financial Institutions will address current challenges and present case studies on how forward-looking organizations are optimizing customer analytics, mitigating risk, and maximizing profitability.
Advanced Machine Learning and Artificial Intelligence in Risk Management
Advanced Machine Learning and Artificial Intelligence have the potential that will help financial institutions understand their customers and reassess risk with increased precision. Join us to learn how organizations are deploying AML/AI to measure and mitigate risk more accurately and faster.
Head of Analytics Propositions & Partnerships, Southeast Asia at Experian,
Altair data analytics enables people of all skill levels to access, generate, and use smart data to make insightful, informed decisions.
Our solutions are designed so that people who work with data can partner with business teams to collaboratively generate and share insight. No code data transformation and machine learning from Altair reduces the complexities often encountered in data analytics. We eliminate the need for specialized programming knowledge and democratize the analytics process. As a result, people across the business can leverage the value of insightful analytics.
Topics Covered at
How to better predict revenue Opportunities and Probability of Risk
Building propensity-to-buy models with actionable collection and recovery strategy
How to develop an optimal collection strategy using a model to determine customers’ propensity to pay outstanding debt.
Expedite the workflow of internal audit activity while reducing the number of loan files with missing, erroneous, or non-compliant data
Credit Risk Analytics
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Ara Damansara, Kuala Lumpur,
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