AI Market Map: Fintech

This article is part of a series on AI Agents. See also: AI Market Maps: Marketing

Investing in AI-native software

At Antler Elevate, Antler’s $285M Series A+ fund, we’re excited about how AI is rapidly transforming what application-layer software can be. Over the past 2 years, we’ve seen an explosion of AI-native software across a variety of industries and functional areas. There’s one overarching theme that’s emerged: AI-native startups can — and will — build 10x better software over the next few years - and they’re doing it at unprecedented speeds.

Advances in AI mean software is no longer confined to automating rote, rules-based tasks. Today, AI analyzes vast amounts of structured and unstructured data to offer suggestions, generate insights, and assist with tasks. But it doesn’t stop there. By chaining actions together, AI is beginning to replace human judgment and execution, solving complex tasks with growing autonomy and efficiency—and putting us in the passenger seat. This opens the door for founders to create immensely more capable software and a far superior user experience.

AI-native startups have this wow factor that wins over early customers. At the root of this wow factor — the AI does complex tasks that would normally take multiple people working on them full-time. Sarah Tavel from Benchmark writes that founders should “sell work, not software”. Instead of software being a platform where humans do work, next-gen AI software can just do the work.

Of course, there are levels of automation. In general, more automation will drive more value to software customers (labor is more expensive than software).

At Antler Elevate, we’ve focused a lot of our time and energy on identifying companies that are pushing the boundaries of automation. Internally, we’ve used the term ‘AI agents’ to describe this category, though we recognize that’s a catch-all term. The reality is, the space is still evolving, and definitions are far from settled - what qualifies as an ‘agent’ can vary widely depending on who you ask. What we’re really looking for is teams who build with AI at the core of their software, using a web of “agents” to make complex decisions and take actions based on those decisions to ultimately deliver a 10x product experience for their customers.

As we’ve spoken to startups and tried their products, it has become increasingly clear that the opportunity ahead is massive. We wanted to share our market maps broken out by vertical or functional area - with an eye to making a distinction between levels of automation. We think it’s important to distinguish between whether AI is doing the work (or building towards that ‘full automation’ future) or if it’s just a pocket assistant to make existing headcount more productive, by augmenting existing workflows. We believe that the former is a 10x improvement over current software, and the latter is only 2-3x. We think that founders building towards full automation will make different product decisions today than those building AI assistants (though this is not always true). We want to back founders who are building towards that future of full automation as opposed to just riding the AI wave.

Caveat: We think getting to higher levels of automation is generally better, but we respect the nuance of 1) automation needing time and data, so the tortoise may yet prevail, and that 2) better products that are more integrated into workflows will continue to win and that automation is not the only factor for startup success.

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AI Market Map: Fintech

And with that, let’s dig into the AI-native opportunity in Fintech.

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AP/AR Automation: AP and AR solutions are flush with unstructured data and manual processes. Companies like Tabs are helping extract unstructured data, automatically generate invoices, automate payments, chase payments, and automate revenue reporting.

Accounting & Tax: Startups are using AI for automating manual bookkeeping, reconciliation, expense categorization, reconciliation, financial close, and for client reporting. Outmin is an example of an accounting software building their own general ledger from the ground up to maximize future automation.

Research & Financial Analysis: Financial institutions deploy armies of analysts for financial analysis and research across public and private markets. From AI agents for specific analyses (see how AgentSmyth deploys macro, sentiment, and technical analysts), to process automation, to memo writing - there’s a lot of room for improvement.

KYC & Onboarding: New tools like Greenlite help triage the screening alert backlogs, perform customer due diligence from web and financial statement data, automate onboarding reviews, and only bring humans into the loop when needed. AI also enables KYC to scale to be a continuous process as opposed to intermittent.

Regulatory Compliance: Compliance teams are overburdened which causes them to be reactive. AI is being used by startups like Hadrius to reduce bottlenecks to monitoring compliance at scale across a number of compliance standards such as marketing compliance, employee compliance, and electronic communication compliance.

Audit: Managing the vast quantities of unstructure data is a challenge for audit firms. AI is being used by companies like FieldGuide to process and search large quantities of data, automate reporting, identify potential fraud, prepare evidence, and manage client communications.

Insurance: Many insurance companies still have paper-based processes. Recent advances in AI are pushing insurance companies to move faster with their automation efforts, moving beyond document extraction and integrating this rich data to further automate their claims and underwriting processes. Sixfold AI is one such solution tackling the insurance underwriting workflow.

Wealth management: There’s countless opportunities to improve the wealth management experience for advisors and consumers alike. Today we already see automatic rebalancing of portfolio and robo-advisors, but with further automation AI agents could optimize the onboarding flow, create fully bespoke portfolios based on customer preferences, use (actually smart) chatbots to provide investment advice, help advisors do research, and automate communications between advisors and their customers. Companies like Thyme and Powder are just a few working to solve a subset of these challenges.

There’s also startups helping financial institutions automate their internal processes: FileAI and Multimodal are just two of many.

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This is a generational opportunity to build and invest in startups. If you’re building an AI-native startup and looking to raise your Series A or Series B, reach out to me at chris.millisits@antler.co.

Or if you’re just getting started, Antler runs the premier global pre-seed accelerator across 20 countries. You can apply to the relevant location using this link.

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