As companies across industries contemplate how much they should integrate Artificial Intelligence (AI) into their operations, the mortgage industry faces unique deliberations.
Finding the right balance between human operations and AI is paramount. In the mortgage sector, AI is designed to augment human capabilities rather than replace them. This chapter explores the key considerations and strategic steps in determining the optimal level of AI investment for mortgage-related businesses.
Finding the Right Level of AI Integration
AI offers a broad spectrum of software platforms and applications, each tailored to various business and customer needs. Determining the appropriate level of AI implementation involves thoroughly analyzing your business operations, customer requirements, and compliance with relevant regulations.
Step 1:
Involving Data Scientists and IT Leaders
The first step in this journey is to involve data scientists and information technology (IT) leaders. Given that there is no “one size fits all” approach to AI, the expertise of these professionals is crucial in navigating the myriad considerations required to determine the optimal AI technologies for integration.
A 2022 Deloitte report1 emphasizes that “one common key to success is maintaining a clear connection between AI efforts and the core business strategy.” Data scientists and IT leaders must collaborate with senior executives from the outset to identify the AI use cases that offer the strongest opportunities to support and expand the company’s mission.
1 Four Practices Your Organization May Need to Lead Its AI Transformation
Step 2:
Assessing Impact on Day-to-Day Operations
Before ruling out or committing to any AI solution, it's essential to assess how AI will impact day-to-day operations and specific functions within your organization. The pertinent question to address is:
"To what degree should our company integrate AI into its workflows and business processes?"
This question requires careful consideration of the unique needs of different functions and the potential benefits AI can bring versus the challenges certain processes might pose for AI integration.
Conducting a Risk/Benefit Analysis
Performing a thorough risk/benefit analysis is a key component of any AI adoption strategy. Here are some critical questions to guide this analysis:
How will AI impact our customers?
Understanding the customer impact is critical. AI can drastically enhance customer service through personalized experiences, faster loan processing times, and more accurate risk assessments.
Does the quality of our data merit the adoption of an AI application?
And what is our willingness and ability to invest in data oversight?
High-quality, comprehensive data is the foundation for effective AI implementation. Investing in robust data management and governance is crucial to realizing the full potential of AI.
Does the AI application fit into our compliance/regulatory framework?
Regulatory compliance is non-negotiable. Ensure that any AI applications align with all legal and regulatory requirements, especially those around data privacy and nondiscrimination.
Based on how much we plan on scaling our business, can we afford NOT to invest in AI?
Evaluate the competitive landscape. Not investing in AI could disadvantage your business, particularly as competitors leverage AI for enhanced efficiency and customer satisfaction.
Detailed and informed answers to these questions will make it easier to determine how AI can best fit into your business model, along with the level of investment required.
Lower-Level Versus Higher-Level AI Integration
AI integration can occur at various levels. Here's a brief overview:
Lower-Level AI Integration: This involves implementing tools that automate and optimize existing workflows without directly impacting customer decision-making processes. Examples include automated data entry, document verification, and basic customer service chatbots.
Higher-Level AI Integration: This involves technology that is more active in decision-making processes, directly impacting customers. Examples include AI-driven credit scoring models, predictive analytics for underwriting, and advanced risk assessment tools.
Each level of AI integration has its own benefits and implementation challenges. The key is to choose the level that aligns with your strategic objectives and operational capacities.
Making a Game Plan for Change Management
Once a company determines its ideal AI investment level, it can move forward confidently with a specific game plan for change management. This plan should include:
Alignment with Business Strategy
Ensure AI efforts closely align with the core business strategy and goals.
Stakeholder Engagement
Involve all relevant stakeholders from the beginning to secure buy-in and facilitate smooth implementation.
Training and Education
Invest in comprehensive training programs to familiarize employees with AI technologies and demonstrate their benefits.
Change Management Processes
Develop clear, structured processes for transitioning from legacy systems to AI-enabled workflows.
Continuous Monitoring and Improvement
Implement mechanisms for ongoing monitoring and enhancement of AI systems to ensure alignment with business objectives and regulatory requirements.
Conclusion
Addressing the challenges and opportunities of AI investment requires thoughtful deliberation and strategic planning. Mortgage companies can harness AI's transformative potential by involving key stakeholders, conducting thorough risk/benefit analyses, and developing robust change management plans. This balanced approach will enable to pave the way for long-term success, driving innovation and enhancing customer experiences in the mortgage industry.
