Banks Can Boost Customer Identification and Verification with Automation and Analytics

A new approach to financial crime prevention is emerging, as banks increasingly integrate data from separate functions, both internal and external sources, to enhance customer identification and verification. By combining artificial intelligence and machine learning with aggregate information, institutions can rapidly produce insights that uncover correlations between credential attacks, account takeovers, and criminal money movements.

Reducing False Positives and Enhancing Detection

According to industry experts, this integrated approach can significantly reduce the rate of false positives in detection algorithms, lowering costs and allowing investigators to focus on actual incidents. The aggregation of customer information from various sources will also heighten the power of an institution’s analytic and detection capabilities, enabling real-time risk scoring and transaction monitoring to detect transaction fraud.

Optimized Customer Experience

The integrated approach can also result in an optimized customer experience, with banks segmenting fraud and security controls according to customer needs and using automation and digitization to enhance the customer journey. Survey after survey has shown that customers highly value banks’ performance on fraud prevention, making digital trust a key differentiator for financial institutions.

Holistic View of Financial Crime

The ultimate goal is a holistic view of the evolving landscape of financial crime, achieved through efficient intelligence sharing and collaborative responses to threats. To get there, banks must redefine their organizational structure and roles, responsibilities, activities, and capabilities across each line of defense.

Key Questions for Banks

As they design their target risk operating model for financial crimes, fraud, and cybersecurity, leading banks are probing key questions about processes and activities, people and organization, data and technology, and governance. These questions include:

• What are the key processes or activities to be conducted for customer identification and authentication?
• Who are the relevant stakeholders in each line of defense?
• What data should be shared across cybersecurity, fraud, and other financial-crime divisions?
• What tools and frameworks should converge?

Leading Examples

Some banks have already made significant progress in integrating their risk functions. A leading US bank has set up a holistic “center of excellence” to enable end-to-end decision making across fraud and cybersecurity, while a global universal bank has combined all operations related to financial crimes into a single global utility.

Conclusion

As the financial industry continues to evolve, banks that can effectively integrate data, technology, and processes will be better equipped to prevent financial crime, reduce costs, and enhance customer satisfaction.