How AI-driven analysis can turn compliance into a CX tool
Customer attrition rates have started flashing on the radar of retail banks and credit unions as they face growing competitive threats from digital-native direct banks, neobanks, and other digital wallet and fintech players angling to take a larger slice of the market.
According to recent data, some 13% of retail bank customers are considering changing their primary banks. Many are doing so quietly by adding new banking relationships without closing their existing accounts — a phenomenon known as “soft switching.”
Against this backdrop, customer experience and loyalty have become crucial barometers of attrition risk.
Countless new digital tools and analytics have been introduced to interpret and act on changes in net promoter scores and other customer satisfaction ratings. While these benchmarks have been around for decades, the depth and breadth of analysis that is now possible is unearthing much deeper insights than ever before possible.
- Banks and credit unions spend huge sums complying with multiple regulatory requirements. Adopting a fresh mindset can turn those expenditures into investments that will help improve CX, customer promotion, and retention at a time when financial institutions need all the help they can get.
- Artificial intelligence can provide the analytical muscle to help engineer this transition.
- Financial institutions represent huge repositories of customer knowledge that can be repurposed.
How compliance can connect with CX
Increasingly, what we find as we dig into the data is that traditional aspects of CX like digital engagement, branch accessibility, and account fees are not the only things influencing customer loyalty and attrition.
Today, issues like account security, fraud prevention, identity verification, and complaint analysis, which have typically been the domain of the compliance department, are rising to the top of the list of satisfaction drivers.
Example: Consumers respond to antifraud measures. A recent survey of U.S. retail bank app users found that overall satisfaction scores rose significantly when customers were required to use multi-factor authentication prior to logging into their banking app.
It seems clear that the fastest way banking institutions can capitalize on this trend is to start connecting the dots between CX and compliance. The following are some key areas of overlap where improvements in compliance-related functions can have the biggest positive impact on CX and brand loyalty. These are based on EXL’s work integrating AI-powered analytics with some of the world’s leading banks.
Real-time account security has CX payoff
When CX and compliance collaborate, fraud detection in banking becomes smarter and more customer-friendly. AI-driven solutions can identify anomalies in transactions and provide immediate alerts with fewer false positives. This automated activity also ensures regulatory requirements for fraud monitoring and reporting suspicious activity. The result is more effective fraud detection that protects the bank and your customers, reduces friction, and builds lasting trust.
Case in point: Real-time fraud fighting. A large U.S. bank was able to achieve its goals by implementing a real-time detection framework to identify synthetic IDs and fraud rings based on personally identifiable information and other digital attributes. As a result, the bank can now proactively alert customers to potential security issues as they are happening.
By leveraging AI institutions can incorporate multiple attributes into the fraud analysis process, including home addresses, phone numbers, device and internet protocol addresses.
In this case, EXL flagged potential irregularities much earlier, and, importantly, intervene with the bank’s clients to get them actively involved in the fraud prevention process.
In addition to saving an estimated $10 million in fraudulent activity, the bank earned valuable trust with its customers.
Turn KYC and AML requirements into friction-fighting features
Know Your Customer (KYC) requirements have historically been treated as a cumbersome and laborious regulatory mandate. However, when channeled properly, this work can have a positive effect on customer experience. Automating identity verification with AI technology ensures that banks not only meet anti-money laundering (AML) and counter-financing of terrorism (CFT) regulations but also reduce friction in the onboarding process.
Many institutions are now using AI technology to automate identity verification through facial recognition and document scanning. These technologies not only accelerate the verification process but also minimize errors and reduce manual effort, creating a smoother experience for new customers.
Case in point: SAR filing. One area where EXL has seen recent successes leveraging AI to improve the KYC and AML workflow is in tracking suspicious activity report (SAR) filings.
Generative AI frameworks can be used to automatically review SAR filings and surface insights based on data anomalies and other red flags. At one institution, we were able to dramatically reduce the amount of time spent manually poring over data. Additionally, errors were reduced by 25% versus the typical human-powered, manual review process.
Armed with this information and more time to focus on higher-level tasks, the bank’s compliance team could spend more time investigating the types of high-risk activities that threaten their customers and their own operations.
Deeper examination of complaints boosts CX results
Initiatives such as reducing customer complaints often originate from compliance requirements, ensuring that banks meet regulatory obligations. However, these activities also provide a significant opportunity for CX teams to add value.
Several large banks EXL recently worked with are beginning to use AI to analyze the root causes of customer complaints, whether they stem from service issues, marketing inquiries, or other drivers. By leveraging AI to analyze complaints and detect systemic issues, CX organizations can drive faster resolution, improve service recovery, and enhance the overall customer experience. At the same time, the compliance team can ensure that complaint tracking and resolution meet regulatory mandates.
Case in point: Turning complaints into insights. In one recent project, EXL used an AI solution to categorize complaints into 25-30 granular problem types and their associated causes (such as a breakdown in business processes or an issue with a call-center representatives). By organizing and cataloging the most common customer complaints in this systematic, data-driven way, and using all available data instead of relying on a small sample of data, better bank-wide solutions were possible. Best of all, the newly freed resource capacity could be focused on addressing the root causes of complaints instead of trying to analyze why they were occurring in the first place.