Chat software can respond quickly and efficiently to prospective borrowers, answering questions about obtaining a mortgage in a conversational manner. A new generation of homebuyers has grown up with this type of technology. Mortgage originators should understand why this technology can be so effective at securing new business.
Time is money and there’s no way around that. Because mortgage rates can change daily and potential homebuyers are free to shop for rates, mortgage originators who respond to clients quickly hold a considerable advantage.
Businesses that contact leads within the first hour of the initial point of contact are seven times as likely to have meaningful conversations with them, according to research from the Harvard Business Review. But only 37% of businesses manage to do this.
Technology can help to augment the follow-up process and answer borrower questions in a way that’s fast, easy and accurate. Originators and lenders should consider intelligent chat nurturing — smooth-flowing conversations available 24 hours a day and powered by chat bots, or automated software programs that interact with people or other computers. Mortgage professionals should know the basics before implementing solutions backed by artificial intelligence (AI).
Intelligent chat nurturing technology is able to qualify leads before ever needing human intervention.
Right-sized solution
Automation is not always a one-size-fits-all solution, and solutions range in degree of autonomy. Depending on the needs of lenders and mortgage companies, institutions can choose customized solutions, from a chat plug-in on their website all the way up to fully automated intelligent chat.
Although it’s not uncommon to discover that chat products are still primarily driven by humans in call centers, simply having a chat option on your website is going to make consumers more likely to engage. The American Marketing Association found that companies that have a chat function on their website experienced a 20% increase in conversions.
Although live chat or semiautomated chat helps with conversion rates, they often do little to alleviate phone-tag issues — repeated missed calls — that many mortgage companies face. Because these tools are still mainly powered by humans, the customer-service employees who receive inquiries from the chat software are still at risk for making mistakes. If an institution has 10 qualifying questions that need to be answered, for example, some questions might be accidentally skipped from time to time. This not only slows down the lending process, but the lag in communication can potentially push buyers to another institution.
If having enough staff to answer buyer inquiries is a concern, this can be addressed by choosing something with more automation capabilities. There are highly intelligent chat solutions on the market that are extremely skilled at understanding the context of buyer inquiries.
Conversational manner
One of the most popular ways mortgage companies have been using AI-powered chat is by making the form process conversational. When lenders need to obtain paperwork from buyers, it’s not uncommon for these buyers to abandon the process when they see the wall of text they’re expected to complete.
To combat this, lenders can use intelligent chat to turn long forms into bite-sized questions. Rather than filling out 30 minutes of paperwork, the intelligent chat agent can feed each question to the client one by one in a way that feels like text messaging — something already familiar to the buyer. This also makes the process feel less like a homework assignment and more like a pleasant interaction.
Additionally, intelligent chat nurturing technology is able to qualify leads before ever needing human intervention. With fully automated messengers, lending institutions can gauge how serious a buyer is based on a few key questions. The tech also is skilled at reading responses for question flow and context. If the buyer asks an intelligent chat agent about credit eligibility, it would know the next question is likely to pertain to what that eligibility is able to purchase. It also analyzes keywords, so if a person uses the word “credit,” it understands the buyer means financial credit instead of a public acknowledgment.
Similarly, the technology also can fill in gaps in a buyer’s financial literacy. AI-enabled chat agents can ask more probing questions to get an accurate picture of a buyer’s knowledge. If a buyer doesn’t know what a credit report is, or the difference between a fixed-rate and variable-rate mortgage, the tool can guide the consumer through their options to help make an edu- cated purchase without feeling pressured by a loan officer. Financial-services companies typically have a section dedi- cated to education, making the process even more fluid.
Most importantly, lenders can use intelligent chat nurturing to spark buyer engagement right away. Several marketing studies have confirmed that a business’s response time is the No. 1 pre- dictor of closing on leads. Fifty-nine percent of prospective buyers are more likely to complete a purchase when their questions are answered in less than a minute, according to a survey by call analytics and automation company DialogTech.
Competing approaches
Before selecting an intelligent chat solution, it’s beneficial to have a basic grasp on how these platforms learn new information. Today, there are two approaches: brute force and ontology-based natural language processing (NLP). Brute force is exactly what the name suggests — forcing the chat engine to learn new things. This is an early form of learning that classifies text and generates an answer.
This type of chat is sufficient at answering general questions, but it doesn’t always do a great job at providing detail. These tools can answer questions like, “What are your operating hours?” with ease, but when it comes to helping buyers review their unique financial situations, they’re limited in the help they can provide. They might be able to link consumers to a website or connect them to a human, but that’s it. This is because the chat engine is learning through a script. A programmer can code it to answer questions about upfront mortgage costs but would likely struggle to code the chat experience to address individual financial concerns.
The more modern approach, ontology-based NLP, is much more skilled at addressing free-form questions. It works by studying patterns in buyer inquiries and it uses these patterns to predict what buyers will ask next. The NLP approach is especially beneficial for lenders that need to operate on a large scale. Because responses are learned through practice and not through manual data entry, this type of intelligent chat agent can learn quickly and service any sized lending institution — from a small local office all the way to enterprise-level businesses — without compromising quality.
Privacy is one of the top things mortgage companies need to consider before implementing chat. Because buyers will be providing personal and identifiable information through the tool, it’s not an option to choose one with less-than-stellar security.
One of the quickest ways to determine whether a chat tool has robust security is whether the solution is free. Free chat products are free because they make their money by extracting and selling personal data, so lenders should not, under any circumstance, use a free offering. Instead, lending institutions need to look for one that encrypts data and protects personally identifiable information. The more layers of protection, the better.
The new wave of buyers, especially younger millennials and Generation Z, expect conversational user interfaces when engaging with any company.
Market direction
Lending institutions need to consider where the mortgage market is heading. The new wave of buyers, especially younger millennials and Generation Z, expect conversational user interffaces when engaging with any company. This demographic is just entering the home-purchase market, giving lending institutions the time to prepare.
Conversational interfaces include automated chat functions, but they also can include voice-based conversation. These next-gen buyers are used to asking questions of Amazon’s Alexa and other voice assistants, and they expect nothing less from the companies they engage with. Because they grew up with instant information at their fingertips, they’re reluctant to even scroll through a webpage to find the information they need. Institutions that can address these future buyers’ unique needs are much more likely to see better results than those that don’t.
Intelligent chat nurturing is not only an effective way to respond more quickly to buyers, but it also is a strong approach to help buyers make smarter purchasing decisions through real-time inquiry and response. Lending institutions and the mortgage originators who work with them can increase their success rates, lower their administrative costs and boost their bottom lines. ●
