20 Ways Artificial Intelligence Might Shape Financial Services

Artificial Intelligence (AI) has the potential to significantly influence the future of financial services. Some of these ways are apparent, others will take years to evolve and play out.

To quote research published by Andreessen Horowitz, “hundreds of new startups are rushing into the market to develop foundation models, build AI-native apps, and stand up infrastructure/tooling.”

Chat GPT, developed by OpenAI, is a powerful language model with the ability to generate human-like text. Recently it has been getting a lot of well deserved attention.

My intuition is that Chat GPT — and its competitors — will slowly (but then suddenly) play central roles in financial tech stacks.

In short, these are interesting times.

I surveyed dozens of FinTech CEOs, AI builders, financial institution executives, investors, and industry builders and asked each how AI will impact how risk is priced and the ways AI will alter our interactions with financial institutions.

Although my thinking is evolving (and subject to change) these are the domains that excite me, and those I spoke with, most about the deployment of AI tools in financial services.

Regulatory Tech

1. Enhancing compliance through AI-powered monitoring.
2. Providing real-time risk analysis for financial institutions.
3. Enhancing fraud detection and prevention with AI analysis.
4. AI can analyze and interpret vast amounts of data to identify and mitigate financial risks more effectively. AI can analyze large amounts of data to detect and prevent fraud more effectively, reducing the cost and impact of fraud on financial institutions and their customers. Today fraud is a $30B market opportunity with a projected five year CAGR of 22%.
5. Reducing manual labor costs with automation. AI can be used to provide quick and accurate answers to customer queries, improving overall customer experiences, on-boarding, etc.

Insurance

1. Automating loan underwriting processes. AI models can automate the verification of income, assets, and debt etc. This should enable faster loan approvals and reduce the risk of loan defaults.
2. Reduce human error in the application process. The result is insurers who are better equipped to sell customers the plans most suited for their needs. Customers benefit from the streamlined service and claims processing that AI affords.
3. Chatbots (onboarding), customer experience bots (for user retention), and claims bots that handles the “first notice of loss”. Future state claims bot will be able to manage an entire claim through resolution without any human involvement.

Wealth Management

1. Providing personalized financial advice with less complexity and lower fees.
2. Next-generation wealth management: AI can provide personalized financial advice to help individuals manage their wealth more effectively and reach their financial goals.
3. Enabling more informed investment management. Improving customer service and personalization with AI-powered chatbots (similar to the insurance use-case).
4. AI models can analyze large amounts of customer data to provide personalized financial products and services, and improve the overall customer experience/support.
5. Improving credit scoring and risk assessment processes.

Financial Tools

1. Reducing human error in financial forecasting with AI models.
2. Streamlining expense management with AI automation.
3. Streamlining account reconciliation processes.

Payments

1. Increased speed and accuracy of payments: AI can streamline and automate payment processes, reducing errors and increasing the speed of transactions.
2. AI can assist in detecting and preventing fraudulent payments, improving the security of payment transactions and reducing the cost of fraud for financial institutions and merchants.

Capital Markets

1. AI can assist traders and investors in making informed investment decisions by analyzing market trends, historical data, and real-time news and events. With AI, financial institutions can manage to ingest high volumes of unstructured text data sources to build powerful investment signals. For instance, AI bots can index web pages to notify financial professionals about relevant datasets.
2. AI can help financial institutions comply with regulatory requirements by automating compliance processes and reducing the risk of human error. Robotic Process Automation (RPA)–a type of automation software that handles repetitive tasks in place of a human–is abundantly used in capital market firms and is applied across front, middle, and back offices. These trends should be accelerated by AI.

The adoption of AI technologies will continue to shape the financial industry and bring new opportunities for innovation and growth.

This list will certainly grow with time.

Thanks for reading. Have predictions about how AI will impact Financial Institutions? I welcome your feedback and can be reached here.