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A Call To Fintech Firms Everywhere


Are fintech companies approaching their conversations with potential partners in the most clear and efficient manner

Dec. 20 2018 — In our Risk Services Product Research and Innovation group, we spend time meeting with new or established financial technology (or “fintech”) companies. Many of these companies are either attempting to disrupt traditional business models with creative ideas and powerful digital solutions for individuals and businesses, or they are looking to partner with the traditional market participants.

The Risk Services Product Research and Innovation team within S&P Global Market Intelligence is involved with many Fintech companies as our role is to build new products, and create new approaches to problems. We also serve as experts in new data and technology, which is useful in discussing potential partnerships or investment opportunities.

But are these fintech companies approaching their conversations with potential partners in the most clear and efficient manner? The insights we gather help shape our assessments of market opportunities and risks. What we noticed in our meetings with many fintech firms is they focus the conversation on what they do instead of focusing on what problem(s) they can solve, and often include jargon that gets lost in translation.

Most start-up companies we meet with identify themselves by the technology they provide. For example:

  • Distributed ledger technology (DLT)/blockchain/Crypto: “we are a blockchain company in finance” … Language that these companies typically use might include: zero knowledge proof, smart contracts, crypto ratings, ‘this is not Bitcoin’, or some other types of technical jargon. 
  • Alternative data: This is a grab bag of new data sets not previously available, or as defined by our Chief Data Officer of our Data Management Solutions offering: it is “nontraditional and the value clients’ gain from it is in the form of supplementing their existing data and analysis.” Examples being data from social media, internet of things devices, geolocation, satellite imagery and how each data set can be leveraged to solve many questions. Their tag lines usually go something like: “We search the public internet/social media and answer your questions.”
  • Machine learning/artificial intelligence (AI): “We are an AI company” and then sprinkle acronyms such as NLP (natural language processing), NLG (natural language generation), ML (machine learning) all in the conversation. And at the end of the conversation, the question we get is “what problems do you have that we can solve for you?”
  • Cloud services: They promise almost limitless computing power with numerous points of access, and no installed machines. Most of the time combined with machine learning/AI capabilities, cloud services offer an intriguing new platform to build products.

Our advice to fintech firms—instead of focusing on what you do, change the conversation to describe who you serve and your value proposition. That will support a deeper analysis of the trends within your target client base, growth opportunities, competitive dynamics, and risk-reward tradeoffs to help investors with their decision making.

If we go back to the earlier themes, with the value proposition in mind, the conversation should be the following:

  • Distributed ledger technology (DLT)/blockchain/Crypto: Our solution delivers significant efficiency in the settlement of over the counter transactions. Our offering removes the need for long settlement cycles, mismatches, reconciliation cycles, and dispute resolution. To achieve this, we are leveraging a private blockchain technology.
  • Alternative data: We have identified potential use cases for the data we have been collecting for another purpose that could be of interest. We have been capturing “XYZ” data, which we believe can provide early risk signals in the lending process, and allow you to make better risk adjusted lending decisions. We leverage different data collection mechanisms then process them via NLP and ML techniques to generate signals. 
  • Machine learning/artificial intelligence (AI): As part of the standard processes, we can discover inconsistencies that can lead to improvement in risk management practices.
  • Cloud services: You can have the ability to load new content sets, map them, test them using multiple techniques against your own data and analytics, find patterns and with minimal effort port the code to production.

Don’t be afraid to share your value proposition first and foremost. By steering the focus towards the problem that needs to be solved, fintech firms will benefit from communicating how they link to, and positively impact different businesses. This should lead into more successful partnerships and investment. Also think about it as cost reduction – you spend less time customizing your tools/products because you solve specific problems (focused approach) as opposed to the buckshot approach of going broad and wide.

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