Managing regulatory compliance is a top priority for all banking institutions, with the goal of reducing the risk of doing bad business and the fines associated with it. Unfortunately, it’s no easy feat to meet compliance requirements, leaving banks searching for the right resources and solutions to use. In complex environments, the firms that come on top are the ones that can find ways to safely capitalize on new technologies – like generative AI.
AI/ML has emerged in the last few years as a potential solution to managing compliance. This recent study from Alloy found that 84% of fintech survey respondents were exploring using AI/ML to help them meet compliance requirements.
At Zennify, we’ve been working with banking clients to find low to no-risk practical use cases for AI to help them manage regulatory compliance, which ensures customer and shared data are not leveraged by AI.
Below, we’ll highlight one example of how an AI Compliance Assistant can help reduce Loan Coordinator training time by up to 40%.
AI Compliance Assistant for Loan Coordinators
Working with a national commercial bank, we’ve been uncovering challenges associated with training loan coordinators on compliance management. Compliance training adds to the overall complexity and time to train, which can often take up to a year to fully onboard an individual loan coordinator; even with that training, support staff is often needed to help verify and back up these individuals when working with customers.
When analyzing a specific use case of filling out a compliance questionnaire, we discovered several common challenges:
- Gaps in Compliance Knowledge: Loan coordinators often do not know how to answer compliance questions on standard questionnaires correctly. These questionnaires often have dynamic dependencies based on the answers provided. If the wrong answer is given, this can create more issues and take them down the wrong path.
- Missing or Incorrect Information: In many cases, compliance questions go unanswered or are incorrect, which leads to more missing information and often unnecessary work.
- Changing Compliance Requirements: Federal and state regulations are constantly changing, making it challenging for compliance managers to effectively train staff and keep questionnaires up to date.
Building a No-Risk AI Compliance Assistant to Decrease Training Time
Internal training presents a viable opportunity to implement AI with little to no risk, given there is no need for customer data from core banking systems or the need to leverage shared data from unknown and untrusted sources. This drove our thinking when defining how to build our AI Assistant. First and most importantly, we leverage closed-loop data only eliminating the risk associated with pulling sensitive data into the AI Assistant. This included internal training documentation and resources and operational information, such as compliance policies.
Reducing Compliance Training Time by 25-40%
An AI Compliance Assistant that can provide answers on compliance to loan coordinators in real-time, reducing the risk of error and incorrect information being collected in compliance questionnaires. Additionally, compliance managers can review the questions that users are asking the AI Assistant to improve training documentation, compliance processes, which are then used as inputs to improve the foundational data leveraged by our AI solution.
Not only does the AI Assistant improve compliance training time and reduce errors by loan coordinators, but ultimately it helps the bank reduce the fines associated with not meeting compliance requirements.
How to Find Practical Use Cases for AI in Banks
Consider costly internal processes that need improvement but don’t rely on customer data. Enabling employee efficiency and training with AI tackles rising labor costs, which is a major challenge for banking institutions.
Compliance training is only one area where a practical and lightweight approach to AI can make a considerable difference. Engage with Zennify’s data experts to explore low to no-risk AI use cases that might be right for your financial institution.
- Do we require process mining to understand the true business process?
- Rationalizing & consolidating applications with a platform mindset.
- Consider technology connectivity through an API planning and integration strategy.
- Integration, consolidation, separation, and more; strategies for managing multiple Salesforce instances and M&A.
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