Everything changed in 2020. Finance was no exception. The first half of 2020 dealmaking was $971 billion, a 6.6 percent year-on-year reduction in value and a 15.5 percent drop in deal count. In comparison, the second half of the year had the greatest dealmaking activity since 2007, with $2.2 trillion in total M&A activity.
We think that the management vision and support that leads to a marriage between the business and technology teams is one of the most important factors in their success. What is the imperative? Innovate quickly and at scale.
Banks can collect considerably more data about client and prospect interaction by employing intelligent marketing automation technologies to provide high-value content pieces to their audiences, including a better picture of who is actively interacting with them on social, on webinars and analyst calls, and more. Event engagement data from systems like as MeetMax, CVent, and Zoom, for example, is integrated into Salesforce so that a banker can quickly and easily tap into 360-degree relationship insights; it is possible to picture a tomorrow in which the study reports that a venture capital negotiator reads are almost as suggestive of interest as the good old-fashioned call notes the banker may record.
The appropriate type of AI and predictive analytics are required to make sense of all of this first-party, second-party, and third-party data (and the possible ramifications for the rest of your company). With the advancement of technology over the last decade, investment banks are beginning to leverage the power of AI and machine learning to get preemptive notifications when their professional networks alter.
Robots will not replace Managing Directors or executives, but they will increase the speed of deal-making and make it faster and easier for your team to receive the information they want, when they require it. AI and bots may help investment banks with high-pressure deals, reducing human mistake on complicated contracts, automating the signing process, or just ensuring that meeting scheduling is flawless.
Many of the banks we’ve worked with over the years have started to use 10+ years of Salesforce data to look at predictive bid ranges and spreads, to inform deal team staffing with an eye toward maximizing success fees and minimizing time to deal close, and to surface real-time trends about client and sponsor behavior using tools like Einstein Prediction Builder, Einstein Discovery, and Tableau CRM.
Silverline takes its responsibility as an expert service provider extremely seriously as organizations aim to enhance their analytics and data science capabilities in order to better monitor and investigate their portfolios. Our purpose is to give industry insights and experience in growing technology sectors, as well as practical tips on how to achieve rapid outcomes. The long-term client relationships we value the most are built in the practice of cooperation, which allows us to create and implement innovative technological concepts that benefit dealmakers and investors.
