When we think of Fintech, we think of innovation in financial services. But for Fintech companies to be successful, they must not only have amazing products but a market-winning sales and distribution team.
In the wake of the financial crises, Fintech companies are faced with unprecedented opportunities, but they face many challenges as they attempt to scale their revenue-generating activities. Take fictitious P2P mortgage lender CrowdNdowed. With a sales team of 100 reps selling P2P-backed mortgages across New York State, CrowdNdowed receives about 500 leads a day of varying quality. Customers routinely call their sales line to ask basic questions but more often than not, they get queued in automated phone trees. Life for sales reps at CrowdNdowed is stressful. Each rep manages about 30 deals at once. Sales activity is measured at forensic levels by management.
Life isn’t much better for the 10 sales managers. CloudNdowded has a 10:1 rep to manager ratio. Managers are maxed out hiring new staff whilst trying to meet monthly targets. The 3 VPS of sales are under pressure to meet revenue targets and introduce new savings and credit card products across the sales team. CrowdNdowed is growing full tilt, but their VC investors have huge expectations and the management team is under pressure to grow the business by 300% this year, whilst trying to keep customer acquisition costs at a minimum.
The people who feel the burden of fast-growing fintech companies the most are in the sales department. The good news is new AI-driven applications will play a huge role in improving sales productivity and will allow sales teams to focus on more valuable activity, whatever their role is in the business. In the future, its likely humans will be accompanied by an AI-powered virtual assistant, for example, Einstein is Salesforce’s new AI super hero. CRM and marketing automation have been hugely helpful at improving the productivity of sales teams over the years, but the stage is set for AI to take things to the next level.
Circling back to CrowdNdowed, here are 6 ways AI will allow this budding fintech company to meet the demands of their VCs without burning out the sales team.
Predictive lead scoring
With over 500 leads being generated a day, our friends at CrowdNdowed have a hell of a job qualifying and converting leads to real opportunities.
However, with the of power sentiment analysis and inference, AI will be able to prioritise real opportunities. This can be done using basic logic but with the power of machine learning applications can start to learn what a good lead looks like for CrowdNdowed – not just if it meets the qualification criteria. Fintech companies love selling to customers with a particular “inflection points” e.g. recently married, bought first house, new born. When marketing becomes predictive, it starts to figure when that inflection point might happen. If a customer is not yet married, but “likes” a ring on his Instagram account, this might be an indication he is about to get married and probably buy a house soon afterwards.
Our sales reps at CrowdNdowed are managing a big number of opportunities each month. It can be a real challenge to keep track of all those deals at once. Sales reps have 3 key responsibilities: originating deals, progressing deals and closing deals. AI can track whether deals are progressing and make recommendations to move them forward. AI is especially good at spotting risks to deals.
The fuel for AI is data. The more data an AI can pull from multiple sources the better. Picture a customer who is applying for a mortgage but recently posted their down-sizing on Facebook, or a customer who published photos of their new Porsche on Snapchat after they said they live below their means on a personal loan application. AI will be able to crawl the web for important events like these which will help reps predict whether a deal will close. This will help improve CrowdNdowed’ forecast accuracy and allow reps to focus on deals that are actually going to happen.
We are data rich and insight poor, but imagine having your own data scientist on demand. For our sales managers at CrowdNdowed, they could really do with some strategic help. As a start-up, they have one strategy person who reports to the CEO.
It’s a real challenge to spot gaps in their deal pipeline, weaknesses in key deals, and stay on top of mortgage renewals. Between hiring new people and helping reps to close deals, they simply don’t have time to analyse all their sales data. In the future, sales managers will have an AI-powered sales strategy assistant that will whisper insights in their ear as they buy their morning coffee. When they are not listening to their new-found virtual data analyst on their way to work, they will be telling it what to do because this guy is capable of understanding speech due to the power of natural language processing. Say goodbye to the drudgery of creating reports or sifting through endless spreadsheets.
Automated advice is one of the strongest use cases for AI in fintech and banking in general. When we think of a fast-growing company like CrowdNdowed, receiving 500+ leads a day with VC scrutiny on the bottom line , an extra hand from a robo-advisor tied to the website or an app will make a huge difference to employee and customer experiences alike. Modern Robo-advisors are capable of qualifying leads, answering customer questions and in some cases processing quite complicated sales transaction — Rep Emptor!
A cutting edge Insurtech company like lemonade is a great example. Lemonade are changing the game with AI-driven apps that are profoundly different to what incumbents are offering — check ’em out. As well as automating the sales process, applications like Lemonade are delivering a fresh customer experience at a far lower cost than their human counterparts.
Smart activity logging
Logging activity is a necessary evil for all sales professionals, but AI will be able to unburden even the most willing of sales reps. Future AI solutions will log calls, gauge the sentiment of the customer and pen follow-up emails with key points and next steps discussed.
Reps will never forget to log a site visit again! An driven AI app will be able to cross-correlate the meeting address in your diary with your location and log the meeting for you. Walking out of meeting, your AI solution will be able infer where you are and recommend a site visit to a new customer a few doors down.
CRMs have been at the heart of sales productivity over the past 20 years. Until now the interface between the CRM and human has been the humble web-brower.. with a sprinkling of mobile apps in recent years. CRMs won’t go away, but in the future, the interface will be voice, virtual assistants and peripheral applications like Alexa. The future of revenue generating activities in fintech companies will be slick, efficient and unencumbered by slow human IO.