The Importance of Data in AI Initiatives for Financial Services

Successful AI and Analytics Strategies in the Financial Services and Tech Industry

Presented by Envestnet | Yodlee

For the financial services and tech industry, successful AI and analytics strategies require expertise in the complex world of data and modeling. In this VB Spotlight event, learn why it’s critical to partner with experienced data and AI organizations to develop and launch AI initiatives.

The Critical Connection Between Strategic AI Use Cases and Data

“It’s crucial to take a systematic approach, not only to drive value-oriented insights that are applicable to the business, but to ensure you’re using the technology strategically,” says Om Deshmukh, head of data science and innovation at Envestnet | Yodlee.

Deshmukh emphasizes the importance of identifying problems where data can provide real insight. It is essential to have access to reliable, generalizable, and enrichable data to drive specific insights. Envestnet | Yodlee utilizes scalable proprietary algorithms to analyze consumer financial transaction data, deriving personalized insights that enhance customer engagement with financial institutions.

“We know that the opportunities are vast to apply AI and ML techniques to improve the experience, but a regulated financial institution is treading carefully and gaining learnings, and there is a lot of risk,” says Nicole Harper, director of corporate strategy at Jack Henry & Associates.

Harper highlights the need to prioritize use cases and align them with business challenges. Whether the objective is improving customer experience, driving revenue, or enhancing efficiency, a well-defined business challenge and use case are essential before implementing any data-driven solution.

“We make sure that we have a well-defined business challenge and use case before we move forward with any type of data-driven solution,” says Joe DeCosmo, CTO and CAO of Enova. “That then informs what data we gather, how we build the sample of the data that we’re going to use.”

Ensuring an unbiased sample of data that represents the behaviors of interest is crucial. Deshmukh emphasizes the importance of sampling across multiple dimensions to derive insights that are truly generalizable and can adapt to emerging dimensions in the future.

“A lot of times there is a lot of business pressure to just building models and showing some outputs,” Deshmukh explains. “We go to great lengths to ensure that our data is sampled across multiple different stratified dimensions so that the insights that we derive are truly generalizable, not just along the dimensions that are of interest to us, but also along the dimensions which are not seen today, but which may become prominent, let’s say, a couple of months from now.”

DeCosmo highlights the importance of reliability and relevance of data for decision-making in the financial institution. Careful selection of data partners is essential to ensure the quality of the data being incorporated.

“AI is a team sport,” adds Harper. “It requires an ecosystem approach with data, AI platform, and fintech partners. Organizations need to select partners wisely, based on innovation and sustainability.”

Harper emphasizes the need to choose fintech partners that are viable, sustainable, and have a good runway in the business. Third-party due diligence helps to limit and de-risk the selection process. Collaboration with a vast ecosystem of partners is essential.

For a deeper understanding of how data can make or break an algorithm and how to identify the right data to enhance the power of AI solutions, register for the free VB Spotlight event.

Agenda Presenters

  • Om Deshmukh – Head of Data Science and Innovation at Envestnet | Yodlee
  • Joe DeCosmo – CTO and CAO of Enova
  • Nicole Harper – Director of Corporate Strategy at Jack Henry & Associates
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