3 questions to smart minds
Photo: Dr. Robin Tech

How Artificial Intelligence Rapidly Accelerates M&A Processes

For this 3 questions to Dr. Robin Tech

delphai in Berlin
Photo: Dr. Robin Tech
30. June 2022

What if an arti­fi­cial intel­li­gence (AI) could shave weeks off your M&A process? Or would auto­mate manual rese­arch of company data? Or help the junior analyst enjoy insights like a part­ner? What arti­fi­cial intel­li­gence can be used for, what forms of AI are used and how custo­mers deal with the data obtained.

For this 3 ques­ti­ons to Dr. Robin Tech, Mana­ging Direc­tor and Co-foun­der of delphai in Berlin, also a rese­ar­cher at WZB and MIT.

1. What do you use arti­fi­cial intel­li­gence for at delphai?

With delphai, our users can iden­tify poten­tial custo­mers, compe­ti­tors and acqui­si­tion targets with maxi­mum effi­ci­ency. Instead of weeks of manual work, it only takes minu­tes with our AI. Simi­lar to Google, our programs go through the Inter­net with large “networks” and coll­ect data. Google is of course inte­res­ted in ever­y­thing — we are only inte­res­ted in data on compa­nies. So when one of our programs goes to a confe­rence website, it iden­ti­fies all the parti­ci­pa­ting compa­nies that atten­ded the confe­rence and stores the data point. We do the same with company websites, job postings, press releases, etc. . — Our Arti­fi­cial Intel­li­gence then comes into play to make sense of all this unstruc­tu­red data. We have deve­lo­ped algo­rithms that can auto­ma­ti­cally read texts to deter­mine which company and which topic they are about. With these results, the next stage of our Arti­fi­cial Intel­li­gence then begins to clas­sify orga­niza­ti­ons and compa­nies by indus­tries, tech­no­lo­gies, sustaina­bi­lity and other topics.

For each of these steps, we use our own speci­fic arti­fi­cial intel­li­gence. The trans­for­ma­tion of unstruc­tu­red data into struc­tu­red data, the clas­si­fi­ca­tion of compa­nies, that is done by indi­vi­dual neural networks that have been trai­ned to do exactly that, they can do nothing else. Most of the AIs or AIs we talk about are “Narrow AIs” that can do one thing really well. But as soon as you give them any other task, they are comple­tely lost. For text analy­tics, we have a neural network that is speci­fi­cally trai­ned to iden­tify client-supplier rela­ti­onships. Another neural network is trai­ned speci­fi­cally for mergers & acqui­si­ti­ons. And yet another finds sales figu­res from press releases and news artic­les — even from private mid-market companies.

2. You mentio­ned specia­liza­tion in M&A, what do your clients do with the analy­zed data?

Custo­mers use our services for diffe­rent topics. They conduct compe­ti­tive analy­ses and gene­rate peer groups auto­ma­ti­cally, create custo­mer profiles, iden­tify acqui­si­tion targets. Until now, this requi­red enorm­ously time-consum­ing manual and repe­ti­tive rese­arch — because you have to search Google, websites and other sources to find the latest infor­ma­tion and news about a company.

Our custo­mers have access via a subscrip­tion model and can perform all data analy­ses them­sel­ves online using the soft­ware. We have built the delphai infra­struc­ture in such a way that we can always adapt it. This is also very rele­vant in the field of AI, because we can also adopt a customer’s market clas­si­fi­ca­ti­ons, for exam­ple. Our users save costs for manage­ment consul­tants, are faster and more effective.

3. And what does the concrete result look like for the custo­mer, the person?

At delphai, this is a self-service dash­board that runs in the brow­ser. There you can enter search fields or compa­nies abso­lut­ely intui­tively. On a macro level, clus­ters of compa­nies are shown, for exam­ple: Where are the fleet manage­ment soft­ware compa­nies loca­ted on the map? Or where are the quan­tum compu­ting compa­nies? Then it is shown how the compa­nies are inter­re­la­ted. Are there clus­ters or is this super disper­sive? Are there perhaps also — if you look tech­no­lo­gi­cally — prevai­ling indus­tries in which a tech­no­logy is alre­ady being used more frequently today? Or are there “weak signals” because there are only three or four orga­niza­ti­ons alre­ady active in a niche.

In the next step, you have the oppor­tu­nity to look at these compa­nies with a very detailed and multi­di­men­sio­nal view. What do they do? How are they finan­ced? You can also find the peer group directly via the Simi­la­rity Search. You see the latest product news, job postings, patents, all of this presen­ted coll­ec­tively and orga­ni­zed in a tabbed view. In addi­tion, you can trace each data point because delphai stores the sources from which the infor­ma­tion was extracted.

Then our users create lists of poten­tial custo­mers, compe­ti­tors and acqui­si­tion targets. Instead of weeks of manual work, howe­ver, it only takes minu­tes. The lists then go to sales people or to buy-side/­sell-side custo­mers or busi­ness units that select compa­nies for due diligence.

About Dr. Robin Tech

Dr. Robin Tech is CEO and Co-foun­der of delphai( In addi­tion, Dr. Tech is a rese­ar­cher at the WZB and MIT, an advi­sor to the German Bundes­tag across seve­ral commit­tees, a high-tech coor­di­na­tor at the German Startup Asso­cia­tion, an advi­sory board member of Block­chain for Science, and a member of the econo­mic advi­sory board of B90/ Die Grünen.

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