While modifying sales goals can be a good place to start, artificial intelligence and intelligent machines (along with a comprehensive process) can be leveraged to analyze data and identify patterns. Aside from knowing the real identity of customers, companies are obligated to ensure that their customers have willingly opted to do business with them through the selection of certain products.
To help catch suspicious activity and reduce risk, companies can put forth a three-part process to detect, prioritize, and evaluate predetermined indicators found in various data sources.
- Detection: The act of looking for and/or identifying indicators using data from any source
- Prioritization: The act of applying plausibility criteria to identified indicators so as to place the indicators in context and apply appropriate resources
- Evaluation: The act of formally gathering additional data to evaluate the identified indicator for the purpose of risk management
Digital transformation challenges in banking have been well understood and the strategies to address them simple and clear. However, it is becoming increasingly apparent that the industry is reaching a tipping point in the digital transformation journey.
The ability to actively monitor and identify data disparities and suspicious activity early on can help protect customers from unauthorized activities, such as the opening of accounts, and prevent companies from falling victim to disciplinary action, millions of dollars in fines, or the need to pay restitution to victims.
While there can be immediate repercussions, unethical behavior can also take a toll on a company’s reputation for years to come and even result in the elimination of key personnel.
In a new guide, we outline six ways financial services organizations can employ a strategy focused on building customer and public trust, strengthening a company’s culture, and reducing risk exposure, all while increasing sales. To read the other five ways, you can download the guide here.