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With 73% of millennials and 66% of Gen Z living paycheck to paycheck, it's crucial for credit unions to adapt and play a role in improving their financial health. However, currently, only a small fraction of the younger generation, 5% of millennials and 4% of Gen Z individuals are credit union members.

Advancements in AI present a game-changing opportunity for credit unions using MeridianLink. By automating loan application assessments, AI technology liberates underwriters' time, allowing them to establish personalized relationships with members who have unique stories.

Using AI, MedianLink users can gain a deeper understanding of members and adopt fair, transparent, and regulatory-compliant AI-powered underwriting. This approach enables the provision of a hyper-personalized digital lending experience that fosters trust.

Discover the transformative power of AI in credit unions, specifically catering to the financial needs of Gen Z and millennials.

In our webinar, we had delve into:

• How AI revolutionizes credit unions' ability to serve Gen Z and millennials.

• The automation of loan decisions through AI

• Real-world examples showcasing how MeridianLink users increased approvals and automation

• How AI works for credit unions of all sizes

In today's fast-paced digital lending landscape, traditional fraud detection methods are no longer sufficient. Identity theft remains a significant cause of losses for credit unions, and synthetic ID Fraud is a growing concern, with recent studies revealing 1.8 million consumer credit accounts potentially linked to fraudulent synthetic identities within a year. Alarmingly, over 30% of these accounts were at risk of major delinquency or charge-offs, resulting in average losses of $8,000 - $10,000 per incident. Credit unions need comprehensive solutions to effectively detect and prevent fraudulent applications during origination while ensuring genuine members' experiences are unaffected.

Join Scienaptic and SentiLink for an insightful webinar on how deep understanding of these tactics coupled with technology can be a game changer in credit origination fraud prevention. Together, let's combat synthetic ID fraud and identity theft, and create a safer and more secure credit origination environment.

Our discussion will include: 

• Evolving fraud landscape: Understand the changing fraud techniques and regulatory challenges in credit origination. 

• Human insights powered by machine learning in fraud prevention: Discover how this union can accurately detect and prevent fraud, leveraging vast data analysis and complex pattern recognition.

• Streamlined operations with AI: AI-powered solutions automate manual processes, reduce false positives, and provide a frictionless credit origination experience.

• Real-world success stories: Gain insights from credit unions that have achieved reduced fraud losses, improved detection rates, and enhanced compliance through AI implementation.

• Best practices for AI fraud tool adoption: Understand key considerations for implementing AI-driven fraud prevention systems, including member experience, and false-positive considerations.

• Q&A engagement: Get specific answers to your questions about credit origination fraud prevention and AI adoption.

Many financial institutions are turning to AI for recession-resistant, fair, and inclusive lending strategies to support their customers. Financial institutions that have implemented AI-enabled platforms have seen 70-90% increases in automated decisioning with gains of 30-50% in automated approvals. In addition, overall approval rates improved by 15-40% while decreasing loss rates by 10-25%.

Our discussion will include:

• The benefits of leveraging AI for financial institutions and their customers

• Strategies for financial institutions and lenders to build recession-resistant portfolios powered by AI

• How to use AI to increase credit access for underbanked and marginalized customers

• Examples of successful implementation of AI in lending

• Methodologies to manage the Internal and external challenges in bringing AI into a lender’s risk organization

This webinar is designed for senior risk leaders and lending professionals who want to learn how to use AI to mitigate recession risks. 

In an effort to support their members, many credit unions have turned to AI for recession-resistant, fair, and inclusive lending strategies. In this webinar, we will dive deep into the specific ways that fair and inclusive AI can be used to assist deserving members and improve credit access safely.

The webinar is designed for credit unions and lending professionals who want to learn about using AI to mitigate recession risks and improve credit access for underserved members. It will showcase examples of lenders who have successfully implemented fair and inclusive AI-powered lending and its positive impact on their members and loan portfolios.

Our discussion will include the following:

• Benefits of fair and inclusive AI in increasing access to credit for underbanked and marginalized members

• Strategies for credit unions and lenders to use fair and inclusive AI to mitigate risks

• Examples of successful implementation of fair and inclusive AI in lending

• How fair and inclusive AI can help credit unions and lenders weather a recession

Nobel-winning economist Paul Samuelson had once quipped that Wall Street had predicted nine out of the last five recessions. While the markets may be touted as cautiously pessimistic, it is evident that we are on the cusp of an economic downturn.

The use of AI in credit decisioning can be a game changer for credit unions looking to support their members, especially in light of recessionary trends. Instead of tightening their belts, credit unions can use AI to tighten their underwriting. Through the use of AI, credit unions can provide members with fast access to credit, customized loan options, and transparent and inclusive credit decisions.

But this transition to AI requires careful planning. We must understand and learn from the experiences of risk leaders so that we can take this evolution to fruition.

In this webinar, we bring you perspectives from seasoned risk leaders on how to make this transition. We will cover the following:

• Creating a sustainable, recession-resistant lending toolkit

• AI-enabled fair, transparent lending for enhanced customer relationships

• Differentiating between credit-worthy members in need vs. high-risk ones

• Building early warning systems

• Help realign risk strategies as per the changing economic climate

A recent survey of borrowers across the USA revealed that only 47% of Gen Z respondents in the USA claimed to have an account with a traditional bank, neobank, or Credit Union.

The above stat reflects the emerging disconnect between traditional lenders like Banks and Credit Unions, and point to the generational differences in banking habits and banking expectations. With Gen Z and millennials set to become the most important consumer groups in the next 10 years, lenders need to take into account the fact that new age borrowers have expectations of personalized recommendations, instant decisioning speed, and an easy application process.

The answer to these expectations boils down to two words: Artificial Intelligence.

The way we lend is evolving so quickly that those lenders that try to understand the lending landscape better, and go beyond normal data sources and lending models to gain a deeper insight of who they are lending to, are the ones who are able to grow sustainably. Leveraging and consolidating multiple sources of seemingly unstructured data into actionable credit decisions that help lend to more deserving borrowers and personalize offers in line with modern day expectations is what AI strives to achieve.

In this webinar, we will be deconstructing the expectations of the new generation of borrowers, and how traditional lending methods may fall short in fulfilling these expectations. We’ll showcase how AI has had on transforming lending infrastructure for traditional lenders, and elucidate the impact of AI-enabled lending through real-life examples by lending leaders and AI lending practitioners.

Points to be Covered

• The evolving lender demographic: Advent of Gen Z

• Expectations from the modern lender: Personalization, Instant Service, and much more

• What’s taking so much time? The bottlenecks in the current lending ecosystem

• Looking at lending from the AI lens:

• A blow by blow comparison with current lending methods

• Solving the personalization expectation with richer data

• Solving the Instant service expectation with self learning custom models

• Beyond expectations: How AI is changing the growth story for traditional lenders

• Measuring the impact of AI for modern lending with real stories