Although PB (Private Banking) and IB (Investment Banking) teams cater to completely different types of clients, AI tools offer common solutions for both. Both PB and IB teams can use AI deal sourcing to find the ideal candidates among millions of companies. If you're wondering how AI can help PB and IB teams with deal sourcing and more, we've got you covered! 

In this article, we'll explore how AI can assist PB and IB teams with deal sourcing.

TL ; DR

Private Banking (PB) and Investment Banking (IB) teams serve different clients, but both can use AI deal sourcing to find, qualify, and prioritize investment opportunities faster. AI deal sourcing automates data collection, market research, company similarity analysis, target qualification and prioritization, and outreach preparation. Key advantages include faster dataset processing across structured and unstructured sources, automated market mapping by geography and niche, real-time data enrichment from financial records and public platforms, smart scoring against internal criteria, continuous market monitoring for signals like leadership changes and funding rounds, and personalized cold outreach that improves response rates. TextCortex supports PB and IB teams with AI agents, knowledge bases, and web access: it analyzes connected databases (Google Drive, OneDrive, Slack, Notion, etc.), automates data-related tasks, conducts real-time market research, and builds custom workflows from simple email drafting to complex multi-step data enrichment. In practice, M&A advisory firm Atares saved up to 20 hours per user per week using TextCortex.

AI in Deal Sourcing

AI deal sourcing refers to the use of large language models and machine learning-powered AI tools to enhance and automate the process of finding, qualifying, and prioritizing investment opportunities. PB or IB teams spend a significant amount of time manually completing tasks like finding potential targets and investment opportunities. AI tools, however, help shorten the process and produce results much faster. Today, those who do not utilize AI are at a competitive disadvantage.

AI in Deal Sourcing Landscapes

AI offers time savings through automation in deal sourcing, while its research and other capabilities provide cost savings and reduced workload. AI can be used for M&A in various stages of deal sourcing, such as:

  • Data Collection
  • Étude de marché
  • Company Similarities Analysis
  • Target Qualification
  • Target Prioritization
  • Outreach Preparation

Why is AI the New Deal Sourcing Frontier?

With AI tools being frequently used and providing value in every sector, those who don't use AI in their work today start at a competitive disadvantage, and deal sourcing is no exception. Traditionally, M&A deal sourcing begins by researching companies that are already publicly for sale or known to bankers or brokers. Then, by narrowing the circle and conducting intensive research, you start to find companies that are not yet known or on the radar of the market. However, thanks to AI, you can conduct AI-powered in-depth research much faster instead of focusing on already known and well-known companies. Especially, platforms like TextCortex allow you to complete tasks such as research and target identification much more efficiently, accurately, and quickly, thanks to AI agent builders that you can optimize for a specific task. If you don't know how to build AI agents, you can check our quick guide.

Advantages of AI in Deal Sourcing and M&A

AI tools aim to lighten the workload and save time for users at various stages of deal sourcing. If you're wondering how AI can help with deal sourcing, let's explore some examples.

Dataset Processing

In traditional deal sourcing, employees must manually manage large databases and complete analytical research using their experience. AI, however, makes this process much smoother and easier by scanning structured and unstructured databases and piecing together semantic signals. Furthermore, AI can transform this data into visual and various document types, such as graphs, Excel spreadsheets, and slides, presenting users with final results. Of course, the final checkpoint is human control; AI only speeds up the processing part of this process.

Market Mapping

In the traditional method, analysts had to manually build lists and research companies from databases. This process is naturally time-consuming and error-prone. However, thanks to AI, employees can quickly rank potential targets according to geographies and niches. AI scans all databases for you, completing market mapping tasks much faster and leading you directly to action. Furthermore, thanks to AI's real-time analysis, you can include the newest companies not currently in the databases.

Automated Data Enrichment

Data enrichment is a challenging, mundane, overly demanding, and time-consuming task when done manually. For example, analysts first analyze financial data, then use the information to research on platforms like LinkedIn to find headcounts, and scan relevant documents like press releases to find growth signs. However, AI tools automate all these processes, processing all data, including important data that is easily overlooked, and outputting a complete process. All analysts need to do with AI is automate the data enrichment process, check the final results, and move on to the next step.

Smart Scoring

In deal sourcing, investment opportunities are categorized and scored according to the standards and filters of companies or teams. AI-driven systems analyze your team's or company's standards, making scoring much more efficient. Furthermore, you can enhance your ranking and scoring system with AI and automate target scoring.

Market Monitoring

Market monitoring involves tracking and identifying company signals to find potential deals. This process is typically done in quarterly timeframes. However, thanks to AI's real-time market analysis, companies can implement continuous tracking of signals like leadership hires, funding rounds, and regulatory changes. Furthermore, you can configure AI tools to track these signals and send you alerts for changes.

Cold Outreach

Cold outreach is usually done using pre-prepared and barely customizable templates. However, thanks to AI, you can dynamically find potential targets for cold outreach. Once you find a potential target, instead of using generic templates and mundane words, you can create hooking and personalized cold emails that include recent moves, executive interests, opportunities, and more. This increases the response rate of your cold outreach and attracts the attention of the person who will receive your email or message. After all, among dozens or hundreds of messages that look the same, what is different is more engaging.

TextCortex AI: Smart Deal Sourcing

TextCortex can simplify deal sourcing and save you time with its various features such as AI agents, knowledge bases, and web access. TextCortex is a leading knowledge management and workflow automation platform that aims to lighten the workload of various sectors, including M&A. With TextCortex, you can gain various advantages, from data analysis to automating repetitive tasks.

Data Management and Data Analysis

TextCortex knowledge bases allow you to analyze the databases you upload or connect to, turning your raw data into insightful information. You can upload documents manually to TextCortex or connect databases like Google Drive, OneDrive, Slack, and Notion with a single click. Afterward, you can automate a wide range of data-related tasks, from target identification to dataset processing, saving you time. For example, Atares saves up to 20 hours per employee per week by automating data-related tasks and enhancing knowledge management with TextCortex.

Market Research and Web Access

TextCortex web access allows you to automate tasks requiring real-time online data, such as market mapping, cold outreach, and market monitoring. By combining both internet data and your own data, TextCortex processes even the smallest details that might otherwise escape human attention, maximizing your research quality.

Custom Workflow Automations

TextCortex shines with its highly customizable automation capabilities. With TextCortex, you can automate a wide range of deal sourcing tasks, from simple tasks like cold outreach email/message writing to complex tasks with multiple steps, such as data enrichment. TextCortex already offers AI agents optimized for different tasks. However, with the TextCortex AI agent framework, you can build AI agents that you can customize for your specific tasks, from the default large language model to databases. You can complete the entire process manually or using our AI-powered agent builder. If you want to make your M&A tasks smart, including deal sourcing with TextCortex, feel free to contact us.

Questions fréquemment posées

What is AI deal sourcing?

AI deal sourcing refers to automating the repetitive and time-consuming parts of the deal sourcing process with AI tools or making deal sourcing tasks faster with AI. For example, TextCortex can provide support in all steps of deal sourcing thanks to its automation, knowledge management, and web access capabilities.

How accurate is AI in M&A deal sourcing?

AI tools provide highly accurate results because they generate output based on the documents and datasets you provide.

How much time does AI save in M&A deal sourcing?

AI tools save you time based on your usage intensity. For example, Atares (a specialized M&A advisory firm) saves up to 20 hours per user per week through TextCortex AI.