Re-Thinking AI for Financial Processes

There is endless debate about the meaning of the term “artificial intelligence,” but there’s one point where everyone can agree: AI is not for amateurs. Implementing a predictive analytics system, teaching a car to drive itself, getting a customer-facing chatbot up and running — these AI-based tasks are not for beginners. But change is coming.

A new wave of intelligent offerings is bringing technology that was once reserved for global corporations with sophisticated IT departments to small and medium-sized businesses. There are hundreds of vertical niches and horizontal opportunities for AI-based systems that ordinary business people can use. Fintech is one of the most promising.

An Evolving Space

While fintech companies have enjoyed enormous success over the past decade, few have relied heavily on AI. There are plenty of reasons why, beginning with the fact that AI really is rocket science. AI requires hard-to-find data scientists plus complex data cleansing and integration plus employees who actually understand how to use it. Beyond that, some of the most promising predictive applications, like credit scoring, have been stalled by concerns about unfairness and discrimination. New, innovative payment systems like Venmo simply don’t need AI.

We’re now entering a new era, however, and AI is booming. Banks, for example, are expected to spend $5.6 billion on AI solutions in 2019, and some predict that the total AI market in fintech will exceed $25 billion by 2024. Many of the original players have been folded into larger organizations, making room for the next round of startups and innovation in the space. As McKinsey put it recently, “The fintech landscape is evolving at an accelerated pace, as new firms and innovations enter the market while others drop out, and ideas are rapidly developed and deployed.”

Augmented Intelligence

One change that’s coming that will put AI in the forefront of fintech’s next generation begins with a new view of what AI means. At Ignition, one category we are excited about is “augmented intelligence.” In this view, software augments human talent and processes rather than attempting to replace them. This approach is already working in factories, where “co-bots” assist human beings to dramatically increase productivity, and now it’s primed for the white-collar world.

Botkeeper, one of our portfolio companies, is an excellent example of how AI can be put to work in a practical, straightforward way to deliver clear business benefits to the small to medium business (SMB) market. Botkeeper’s software specifically targets SMBs. It extracts data from both financial and non-financial sources, and then automates bookkeeping functions such as categorizing expenses, paying bills, invoicing customers, accruing revenue and other manual tasks. It uses AI — specifically, machine learning — to make the low-level decisions such as classifying transactions that are necessary for day-to-day operations.

By automating time-consuming tasks, Botkeeper lets accountants focus on what they do best: analyzing operations from a financial perspective and providing financial guidance to the people running the business. The system typically reduces a firm’s accounting costs by 50 percent, while offering accuracy of 99.97 percent, which is a substantially higher level of precision than that achieved by the average bookkeeper at 95 percent. Botkeeper enables accountants to service up to 5 times the number of clients, and also perform more consultative value-add work. Another benefit is much faster end-of-month, end-of-quarter and end-of-year closing. Ultimately what’s important here is that SMBs can realize all of these AI-based benefits without having to understand or build out the complexities of AI systems.

Beyond SMBs

While the augmented intelligence view of AI is particularly attractive to SMBs, it can have enterprise-scale applications as well. Software created by Icertis, another of our portfolio companies, applies AI to contract management to address previously intractable contract challenges. This includes digitizing legacy contracts and importing third-party contracts at scale, analyzing past negotiation history to gain insights for improvement, and deep data visualization capabilities that provide unprecedented visibility into contract relationships and performance. In doing so, Icertis enables companies to not only reduce cycle-time and eliminate errors by automating key aspects of the contract review process, but also consistently negotiate the best possible terms and outcomes while ensuring compliance with all required terms and clauses, even for third-party contracts.​

A Bright Future

The success of these companies points the way to a future where start-ups that can leverage augmented intelligence will thrive and transform the way business is conducted in every aspect of financial services, from consumer interactions and evaluations to back-office functions. We are especially excited about how AI can transform financial services processes such as insurance underwriting, real-time lending, and collections.

If you are building an intelligent application, we would love to talk to you, please reach out at Kellan@ignition.vc or @kellancarter9.