The emergence of analytics has allowed all sorts of businesses to sift through a proverbial haystack of information and turn isolated facts into meaningful and actionable insights.

Analytics Drives Insight: Leveraging Data in the Future of Banking

The emergence of analytics has allowed all sorts of businesses to sift through a proverbial haystack of information and turn isolated facts into meaningful and actionable insights.

Increasingly, big banks are utilizing predictive data-mining techniques to better understand clients, projectively model business scenarios, gauge the intent of potential partners, and assess risk. Wall Street is using these cutting-edge tools to increase knowledge and decrease uncertainty in the M&A process.

Insight Enhances Opportunity

Dealmakers have long recognized that knowing as much as possible about prospective clients, partners, and acquisition targets are key to maximizing upside opportunity and minimizing risk.

For instance, a detailed awareness of a decision maker’s interests, personality, and career track record can help seal an agreement or provide a decisive advantage. In the past, much of this information has been gleaned through personal relationships and interactions.

However, today M&A specialists are leveraging many of the same predictive analytic techniques employed by insurance companies, online marketers, digital retailers, and social media platforms.

The Age of Analysis

Although some M&A professionals remain skeptical about the use of big data, there’ s little doubt that top investment firms are embracing the trend. There are numerous reasons this shift will only accelerate.

First, private equity managers have traditionally appreciated the value of tracking interactions. In the past, taking detailed notes regarding phone conversations and social engagements helped build up client profiles.

Nowadays, the typical client base has expanded many-fold and the number of possible data points has multiplied exponentially. No doubt, the wealth of quantitative financial information now available is staggering. However, analytic tools allow users to quickly organize and scrutinize vast reams of data to discern meaningful patterns.

AI and Algorithms Augment Human Judgment

The advent of big data coupled with AI is enabling a level of predictive analysis never before imagined. Essentially, databases now have built-in algorithms, which can be used to model multiple financial scenarios, and make probabilistic predictions regarding a client’s behavior.

In fact, leveraging historical data to make informed decisions in M&A processes is immensely sensible because it leads to fewer failed deals. For example, private equity firms typically entertain dozens of deals before settling on the most promising. Data analytics tools can provide insight on what is being said about acquisition targets on social media, assess executives by scouring professional network profiles, and sift through key financial metrics.

The information gleaned helps form a comprehensive picture of prospective acquisition targets, which deal makers can use to augment their own judgment in the due diligence process.

Cloud-Based and Off-the-Shelf Solutions

Traditional industries, of course, have been utilizing data-driven models for years. Surprisingly, many M&A professionals have been under the false impression that these tools are too complicated to use or that their deals are too time-sensitive for these techniques to be employed.

On the contrary, recent advances in cloud-based platforms and off-the-shelf solutions have made analytics more affordable, intuitive, and user-friendly than ever.

In most cases, data transparency is in the interest of both buyers and sellers. In fact, nowadays,  financial information can shared virtually instantaneously. And thanks to AI cognitive-learning systems — like IBM’s Watson — it can be analyzed in real-time.

Key Takeaway

Successful M&A deal making requires increasing the scope of knowledge while reducing uncertainty. That’s precisely what analytics are designed to accomplish. It enables one to sift through revenue projection models, supply chain scenarios, and other factors that might give businesses a competitive advantage.

Consequently, private equity professionals can utilize big data to better understand portfolio companies, acquisition targets, and the intermediaries and industries they transact with. It can the enhance deal maker’s confidence that they have the most complete picture possible of the investments and transactions they make.

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