Ivan Hancko
AI is fast becoming a part of our life and is changing almost every industry with financial services being no exception.
Mortgage brokers assist clients to identify the right mortgage solution for their needs and circumstances. In theory, AI can do the same, but better.
So, what are the pros, cons and future options for using AI in this industry?
Well, as part of a mortgage broker CRM system, AI can automate certain tasks, make better decisions and find opportunities that might have been missed otherwise.
Some examples are:
1. Data Collection and Analysis
Mortgage broking requires data analysis: looking at your credit commitments and credit history, employment history and income details, and various other aspects in order to determine whether you are eligible and how much you can afford to borrow.
This is usually done by manual data and document collection and time-consuming assessment and research.
AI can cut the need for human data input into mortgage CRM platforms, use algorithms to analyse and verify data. For example, AI can analyse payslips and company accounts, bank statements and tax returns to check a borrower’s max affordability and the likelihood of repaying the mortgage.
2. Customer Service Enhancement
The use of chatbots and virtual assistants can improve customer engagement by providing instant answers to simple customer queries, suggesting mortgage products that could fit the customer’s needs, and by guiding the client through the mortgage application process.
For example, when a potential borrower gets in contact, AI can quickly assess the borrower’s financial situation, record the details in the mortgage broker CRM platform and make appropriate recommendations – as long as the situation is straightforward.
AI can even provide the borrower with preliminary quotes or explain how a change in interest rates, loan terms or the down payment will affect the monthly payments.
AI can also help answer the routine questions that normally take a lot of time to explain and just waste the broker’s time.
3. Automated Decision Making
The underwriting process involves reviewing the borrower’s credit history, income, etc. before making a lending decision.
AI models are able to evaluate and predict the consumer’s behavior and suggest underwriting decisions that are better and faster than those of human underwriters. In theory.
It can look at a borrower’s financial situation and look at other data points such as rent and utility payment history to predict the borrower’s likelihood of repay the mortgage.
This is important because by virtue of the feedback loop, the AI gets better with every single underwriting decision that it makes. It enhances the accuracy of future loan evaluations and reduces the chances of late payment and default.
4. Fraud Detection
Fraud, especially fraud that includes misrepresentation of income or assets, is a major problem in the mortgage industry. AI tools help in the identification of potential fraud in the mortgage application process from anomalies in the borrower’s financial data, document inconsistencies or behavior that may be indicative of fraud that would not have been detected by human brokers.
This approach helps the brokers and lenders to reduce the risk of fraud and to enhance the security of the mortgage process.
5. Risk Assessment
The probability that a borrower will default on a mortgage has to be assessed by the lender and this is a complex process. Traditionally, this process has been based on credit scores, but AI can give a more holistic view.
For instance, employment history, spending patterns and even the macroeconomic trends could be used in the assessment of the likelihood of defaulting.
In other words, in what way can the consumer, the broker and the lender benefit from the application of AI?
1. Improved Efficiency and Speed
In the case of mortgage processing, Artificial Intelligence can replace manual work in the mortgage broker CRM system, which means that brokers can process and prepare applications faster.
That means brokers are in a better position to do more business and give their clients results faster, which in turn makes the customers happy.
2. Cost Reduction
By performing routine tasks and enhancing the workflow, even within the mortgage CRM system, AI can help reduce operational expenses that can lead to more profits for the brokers and lenders and possibly share some of the costs with the clients.
3. Personalize Mortgage Solutions
Since AI can analyze the financial status of the consumer, it can suggest the best mortgage products to help the client select the products that are suitable for their financial situation and their goals.
4. Greater Accuracy
In the mortgage processing, AI helps in the prevention of errors and the ensuring that important details are not omitted. This increases the chances of making the right decisions in order to protect the lenders and the buyers.
Some potential issues in implementing Artificial Intelligence in the Mortgage Broking Process may include:
1. Data Privacy and Security
Since mortgage brokering involves collecting and storing clients’ personal and financial information in mortgage broker CRM systems, it is important that the AI systems used are compliant with the data protection policies.
Mortgage brokers have to ensure that the AI tools they use are secure and meet the necessary data security and privacy standards including those set out in the GDPR.
2. Bias in Algorithms
AI is powerful but trained on a set of data, which can be biased. For example, if an AI system is trained on a historical lending dataset that discriminated against certain demographics or restricted lending on certain types of properties, AI will include these biases in its recommendations.
The problem is that as lending criteria, scoring settings and target demographic change for lenders all the time and are not always clearcut, so it can be difficult to train AIs.
3. Integration with Existing Systems
In order for mortgage brokers to get the most out of AI, the new technology must be compatible with the current mortgage CRM software and other data platforms. This may mean that new systems need to be altered or replaced to work with new AI driven tools which can be a costly and time consuming process.
The Future of Using AI in the Mortgage Industry
AI can enhance mortgage broking to be faster, cheaper and possibly less risky. However, just like with any other technology, there is a need to make sure that AI is used properly to avoid problems such as bias, data security and regulatory compliance.
AI does have the potential of transforming the mortgage broking industry by improving the efficiency of the process with the help of mortgage CRM softwares, reducing costs and enhancing the customer experience. Nevertheless, the technology is still in its infancy and we should be careful before replacing us humans.