July 1, 2019 | Written by:
Categorized: AI | FinTech | IBM RegTech Innovations | Security
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Until recently, the words “customer experience” and “compliance” didn’t really come up in the same conversation – let alone exist in the same universe. The former was the domain of customer care professionals, contact center managers, marketing leaders and digital strategy teams with the goal of helping streamline and simplify products and services, as well as ensure proper resolution of customer issues post-purchase. Compliance, on the other hand, was the domain of so-called “back office” personnel involved in risk management and regulatory matters, and perhaps with either “compliance” or some niche acronym in their titles. There didn’t seem to be a need to connect this area, governed by rules and regulations, with the “front office” customer experience.
Siloed information hides systemic risk
That is, until events like improper sales practices led to a number of high-profile incidents that have continued to haunt institutions for years. In many of these cases, customer complaints would have provided an early warning to the institution that there was a breakdown in the process. But because the mechanism to not only share, but also understand this information didn’t exist, these issues snowballed into a lingering crisis.
As a result, the idea of “conduct risk” has expanded beyond its traditional place on the trading floor and in monitoring for market abuse and manipulation, and instead financial institutions are turning those technologies toward their customer-facing channels. But the focus of this conversational insight isn’t just limited to understanding whether a representative is violating policies. It’s also a valuable training tool that can help improve agent performance, reduce the number of customer complaints and even highlight an emerging issue that may not be on anyone’s radar.
Seeing customer feedback as a data source
Innovation in the contact center has created no shortage of channels and tools to improve interaction with customers. From traditional voice and email to web-based chat, video conferencing and mobile messaging, consumers have plenty of ways to get support as well as voice their concerns. But often, these individual technologies are designed for usability and customer experience, rather than generating valuable insights.
If these tools do have some kind of reporting or transcription, they are designed for the scope of that particular interaction channel rather than to contribute to a holistic conversation with a customer across multiple channels.
This may be helpful to understand that customers who prefer text-based conversations tend to web chat about a certain topic. But if that only represents a small portion of your customer interactions, you may be over-representing the needs of your entire customer base because of the available insight within a smaller channel.
Getting to a complete picture of customer feedback
As I noted above, the proliferation of interaction channels has been a boon to consumers, giving them conversation options that fit their changing preferences. While this is great for customers, it makes it difficult to look across different technologies, interactions streams and media to clearly understand what customers are saying and what that means to the organization.
We at IBM have been working with financial institutions to solve this challenge using IBM Surveillance Insight to create greater understanding, at greater speed. Using artificial intelligence and machine learning, we’ve been able to automate one of the initial and often time-consuming tasks in this process: the cataloging of complaints by issue, product and complaint type. After the data is properly organized, we apply machine learning to surface common themes and help pinpoint the root causes of complaints by identifying systemic and emerging issues.
By expanding the scale and scope of complaints analysis, we help clients identify emerging issues and spot trends that might be a small portion of a single channel but represent a significant portion of all interaction channels. In addition, the speed of this analysis takes a fraction of the time of manual analysis or combining ad hoc reporting from multiple systems.
The value (and challenge) of customer insight
Like any other data source, customer complaints data can be imperfect, disorganized and end up being used for something for which it was never intended. But at a time when customer experience is high on everyone’s priority list, those flaws shouldn’t prevent financial institutions from seeing it for what it truly is: a relatively untapped data source that customers are providing readily and at no cost as well as a competitive advantage that can expose flaws as well as new opportunities. Silos have already caused enough damage – there’s no reason this data can’t serve both the customer experience and compliance groups equally.