The UK’s Help to Buy scheme helps first-time buyers onto the property ladder - and floods mortgage brokers with complex and time-consuming mortgage applications. To help process leads, SPF Private Clients created an AI-powered app featuring a chatbot, accelerating application processing times with 24/7 Help to Buy qualification.
“The IBM [...] solution enabled us to speed up processing of Help to Buy mortgage applications. Now we can take on more opportunities while decreasing our internal costs, meaning we can better service our clients and introducers.” - Freddie Savundra, Digital Architect, SPF Private Clients
Business challenge
Getting on the property ladder for the first time can be tricky, and people don’t always know when they’re ready. SPF Private Clients wanted to speed up the process of being qualified for Help to Buy.
Transformation
SPF Private Clients created a portal where applicants can upload documentation and chat with an AI chatbot and humans, with the top leads passed automatically to brokers.
Results
24/7 Help to Buy qualification and higher conversion rates
Fast-tracks responses to promising leads and new-buyer questions, enhancing client experiences
Offers a valuable competitive advantage
Solution components
Watson Assistant
Watson Tone Analyzer
Business challenge story
Tackling a high-effort, low-yield market
To open the door to more people owning their own homes, the UK government launched the Help to Buy initiative in 2013. The scheme provides qualifying UK residents with an equity loan for up to 20 percent of the property value (40 percent within London).
By increasing the number of potential buyers, Help to Buy gives mortgage brokers such as SPF Private Clients the opportunity to increase their revenues - but only once they’ve sifted through a huge volume of applications. It’s a complex scenario for mortgage brokers, as the government scheme only applies to new build properties with a purchase price of up to GBP 600,000 and many banks are limiting their lending on new build properties.
Freddie Savundra, Digital Architect at SPF Private Clients, picks up the story: “Our New Homes department spent a lot of time qualifying people for the scheme. It sometimes took up to two days to evaluate a client - a process that includes gathering and inspecting information and documentation from an applicant.”
SPF Private Clients wanted to simplify the process and qualify more people for the scheme. The company recognized this was an ideal use case for intelligent automation and began looking for the right technology and partner to make its vision of smarter lead qualification a reality.
Transformation
Bringing Ava to life
For SPF Private Clients, selecting IBM Watson technology for its AI capabilities was an obvious choice.
“Choosing IBM Watson was a no-brainer for us,” explains Savundra. “It’s a best-of-breed solution designed for use cases just like ours, which means we didn’t need to adapt it or worry about scaling it. Thinking long-term, it includes extra functionalities that we can turn on once we’re ready.”
Using IBM Watson and IBM Cloud solutions, a portal was created for Help to Buy applicants, where potential SPF Private Clients customers can submit information, upload documentation and interact with Ava - an AI chatbot. The solution is written in JavaScript, with Node.js on the back-end and Angular.js on the front-end. It runs in an IBM Cloud Foundry environment, and uses IBM Compose for MongoDB to securely manage customer information. IBM Cloud Object Storage provides scalable, resilient and secure object-based and file system storage.
Chris Patterson, Managing Director of EscalateAI, says: “With Cloud Foundry, we have the tools to ship high-quality code rapidly, scale seamlessly and deliver continuously, enabling agile, fast development. IBM Compose for MongoDB and Cloud Object Storage are both extremely scalable and robust, giving the solution solid foundations.”
Based on IBM Watson Assistant, Ava, The SPF Help to Buy mortgage advisor chatbot, can provide relevant information to customers outside of office hours, enabling round-the-clock self-service. Ava, with its hybrid human chat solution, analyzes customer messages and automatically escalates to a human operator when it detects a low level of confidence or tone. The solution incorporates IBM Watson Tone Analyzer technology. Savundra comments: “Watson Tone Analyzer makes Ava more human-friendly, allowing us to combine live and bot chat to elevate customer experiences.”
SPF Private Clients uses algorithms to analyze customer information to offer immediate feedback on their viability for a mortgage. With just three minutes’ effort, visitors to the portal can get a quick mortgage indication; 15 minutes will give them a Decision in Principle and 30 minutes will collect most of the information a member of the SPF New Homes team requires to recommend a product. The solution assigns a traffic light rating to each lead, with green indicating leads qualified by Ava for action, amber for those that need further information and red for applications that require attention from a specialist team in SPF Private Clients (such as low credit rating or a complicated employment history).
Results story
Helping people onto the property ladder
By automating the lead qualification and information-gathering process for Help to Buy applications, SPF Private Clients can process more leads without extending the size of its New Homes team. Leads are pre-qualified, allowing brokers to focus on the most promising to drive up conversion rates. And when brokers receive the pre-qualified leads, the leads come with supporting documentation uploaded and verified, allowing brokers to close deals faster.
“The IBM [...] solution enabled us to speed up processing of Help to Buy mortgage applications,” says Savundra. “Now we can take on more opportunities while decreasing our internal costs, meaning we can better service our clients and introducers.”
At the same time, the solution helps SPF Private Clients respond faster to applicants. Customers can get instant responses to frequently asked questions via Ava at any time of day, and quickly receive an indication of the viability of their application. Combined, these factors help the company deliver better customer experiences.
“Lots of people want help understanding how much they can afford through the Help to Buy scheme and how each stage of the mortgage application process works,” comments Savundra. “With help from IBM [...], we can guide them at every step, giving them confidence that they’re in the best possible hands with SPF Private Clients.”
SPF Private Clients is breaking new ground with its New Homes portal and Help to Buy chatbot, giving it an edge over its competitors. Looking to the future, the company plans to extend the solution into other parts of its business, positive that it can achieve even greater returns on its investment.
Savundra concludes: “We’re very proud to present the SPF Help to Buy chatbot in Ava, which IBM [...] made possible. And the innovation doesn’t stop here – next on the agenda, we’ll expand IBM Cloud and AI solutions into our other mortgage and remortgage departments, insurance, wealth management and short-term financing team. We see the potential for transformations across SPF Private Clients.”
About SPF Private Clients
SPF Private Clients helps its clients achieve their financial goals through funding, wealth management and insurance advice. With offices in London, Manchester, Guernsey, Nottingham and Oxford, the company is one of the market leaders in UK financial services.
AboutIncede.ai
Incede.ai is the AI division of Locus Solutions, Inc.; harnessing the power of Data, AI and Machine Learning
With more than half of the world’s data in natural language, Incede.ai solves business problems and creates a competitive advantage by leveraging the power of Watson AI and machine learning.As thought leaders, we collaborate with stakeholders to deploy AI solutions that deliver real value.