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Webinar write-up: How ML & Smart Analytics are helping FinTechs understand their data

Joe Roche / 9th July 2020

On Thursday 9th July the Northern FinTech community gathered to discuss how Machine Learning and Smart Analytics are helping FinTechs understand their data.

This webinar was hosted in partnership with Netpremacy.

Julian Wells, Director of Whitecap Consulting and FinTech North, welcomed everybody and provided an overview of FinTech North’s activity, which includes over 56 events across the North and a recent pivot to a webinar format.

Alastair Lumley, Google Cloud Account Director at Netpremacy, then introduced Netpremacy and explained how they help customers get the most out of Google’s cloud services. Netpremacy get to know innovative tech companies and tailor a bespoke solution to help them to:

  • Use data to build a customer profile
  • Be more secure
  • Improve risk assessment
  • Provide unbeatable customer service

Next up was Tom Anderson, Pre-Sales Consultant at Netpremacy. Tom started by defining smart analytics in a jargon busting way: “Use data intelligently to understand and influence business operations”.

Tom then explained the difference and progression of analytics; from descriptive analytics, diagnostic analytics, predictive analytics and prescriptive analytics.

Tom condensed analytics capabilities down into 3 layers which are to be considered together when implementing in any business:

  1. Data Acquisition
  2. Data Science Layer
  3. Business Layer

Jyrki Hayrynen, Customer Engineer at Google was our final speaker. Jyrki ran through a number of interesting case studies including Monzo and GoCardless.

Monzo, one of the UK’s leading challenger banks, optimizes its fast-developing product with accessible, zero maintenance, high powered BI analytics based on BigQuery and Google Cloud Platform. Anaytics play a huge part in streamlining their system for the future.

Moving to Google Cloud Platform allowed GoCardless to reduce infrastructure costs by 25%, reduced their operational burden and allows VPN-free user authentication.

Jyrki explained that Google’s cloud platform allows for increased security during a time when working from offices has become increasingly difficult.

We then broke out into a Q&A session with all our speakers and audience:

  • How does Google protect data?

Jyrki – The story with Google is amazing on that one. We make sure we keep easy access and good visibility on audits. Google’s philosophy is trust no one. It comes down to technical things like proprietary hardware. Google’s global reach allows us to build a network that is completely private. You rely less on public networks.

  • How important is it for people to be clear on their strategy and its relation to data?

Tom – absolutely vital, if you haven’t got an understanding of your capabilities and where you’d like to get to, you can’t possibly measure the success of a data strategy. That’s where you can start to map your journey across those analytical models. Where am I now, where do I want to be. It needs to be driven from the top down, senior management and all key stakeholders need to be aware of it.

  • A lot of the data and modelling talent within Fintechs has come from the traditional big banks that are very SAS heavy for risk modelling and regulatory analytics – how easy has it been for Fintechs to move from that to GCP tools?

Tom – It’s not a case of one size fits all and the best thing to do is to talk to Netpremacy!

  • If I want to use Google to do modelling, how do you advise a novice where to start?

Jyrki – get connected to your google account team. We have a platform called QuickLabs, you can get training and go straight into a training environment. BigQuery is the tool I would recommend to get started.

  • How do Google themselves use AI and Machine Learning? Have you used any Blockchain tech into your data to further secure user data?

Jyrki – Google has a very broad range of use cases there. It can range from small things like smart responses in Gmail and Google assistant, to in GCP to use models by Deep Mind to run our data centres. To my knowledge we aren’t using blockchain technology to secure data.

  • Are there any prime use case candidates to use as an entry point to introduce using GCP offerings into a business?

Tom – Either companies have a lot of data and don’t know what to do with it. Or they don’t know what they’ve got. Let’s try and collect and store everything we can. Being able to do descriptive analytics on all of your data is infinitely more valuable than doing no analytics at all. Netpremacy can help facilitate the data workshops and help produce a pipeline. We can start at the very beginning, we can help you understand the tools, or we can help you implement them aswell. Organisations of any size, talk to us! We love to hear about how people are using data!

You can watch the recording of the webinar by clicking here.

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