Tag: Experian DataLabs

Chatbots, reduction of manual processes and explainability were all hot topics in a recent discussion between Madhurima Khandelwal, Vice President and Head of DataLabs at American Express®, and Eric Haller, Executive Vice President and head of Experian DataLabs. The importance of AI’s role in innovation in the financial services space was the focus of the recent video interview. In the interview, Khandelwal highlighted some of the latest in what American Express DataLabs is working on to continue to solve complex challenges by building tools driven by AI and Machine Learning: Natural language processing has come a long way in even the last few years. Khandelwal discussed how chat bots and conversational AI can automate the simple to complex to enhance customer experience. Document recognition and processing is another leading-edge innovation that is useful for extracting and analyzing information, which saves staff countless manual hours, Khandelwal said. Fairness and explainability are consistently brought to the forefront especially in financial services as regulators are looking at ways to prevent AI/ML from causing bias for the consumer. Khandelwal showcased how there is extreme rigor in each part of creating their models and how human oversight and training are primary drivers for how they stay on top of this. As for innovation advice, Khandelwal points out that it’s important to be aware that AI and innovation are not always interchangeable, and companies need to think through whether a problem needs to be solved through AI/ML models before charting ahead. Another major key to the equation is the data. In all use cases, the undercurrent of innovation in any form is dependent on the data being used. Learn more about this topic and what Harry Potter has to do with women in data science. Watch the Interview

If someone asked you for stats on your retail card portfolio, would you respond with the number of accounts? Average spend per month? Or maybe you know the average revolving balance and profitability. Notice something about that list? Too many lenders think of their portfolio and customers as numbers when in reality these are individuals expressing themselves through their transactions. In an age where consumers increasingly expect customized experiences, marketing to account #5496115149251 is likely to fall on deaf ears. Credit card transaction data including bankcard, retail, and debit cards holds a wealth of information about your consumers' tastes and preferences. Think about all the purchases you made using a credit card this past month. Did you shop at high-end retail stores or discount stores? Expensive restaurants or fast food? Did you buy new clothes for your kids? Maybe you went to the movies, or met friends at a bar. How you use your card paints a picture of who you are. The trick is turning all those numbers into insights. You may have been swept up in all the excitement around Apple’s announcement of the iPhone X in August. However, you may have overlooked the incorporation of Neural Embedding, or machine learning, as one of the most powerful features of the new phone. Experian DataLabs has developed an innovative approach to analyzing transaction data using similar techniques. Unstructured machine learning is applied and patterns begin to emerge around customer spending. The patterns are highly intuitive and give personality to what was previously an indecipherable stream of data. For example, one group may be more likely to spend on children’s clothing, child care services, and theme parks while another spends on expensive restaurants, airlines, and golf courses. If these two consumers happened to spend approximately the same each month on your card, you’d probably treat them as category. But understanding one is a young family and their other is jet setter allows you to tailor messaging, offers, and terms to their needs and use of your products. Further, you can ensure they have the best product based on their lifestyle to minimize silent attrition as their needs evolve. But it’s not just about marketing. When your latest attrition dashboard is updated, what period are you measuring? Do you analyze account closures from the previous month? Maybe a few months back? Understanding churn is important, but it’s inherently reactive and backward looking. You wouldn’t drive a car looking in the rearview mirror, would you? Experian enables clients to actively monitor the portfolio for attrition risk by analyzing usage patterns and predicting future spend. Transactions are then monitored up to daily and, when spend doesn’t occur as expected, an alert is sent so you can proactively attempt to save the account before it closes. These algorithms are finely tuned to reduce false positives that can come from seasonality or predictable gaps in spend such as only using a card at certain times during the week. Most importantly, it gives you an opportunity to manage each account and address changing customer needs instead of waiting for customers to call to cancel. So how well do you know your customers? If you’re still looking at them as numbers, it may be time to explore new capabilities that allow you to act small, no matter how large your portfolio. Transaction Data Insights brings cutting-edge machine learning capabilities to lenders of all sizes. By digging into behavioral segments and having tools to monitor and send alerts when a consumer is showing signs of attrition risk, card portfolios can suddenly treat customers like people, providing the customized experience they increasingly expect.