• “To overcome this challenge, data exploration and extraction will become vital and prove a turning point for banks in 2022. We’ll see banks undergo large-scale data exploration programs to scruntize and examine the data they retain so they can fully understand their data assets. This includes everything from transaction and payroll data through to foreign exchange data.
  • Ultimately, banks of the future will need to differentiate themselves by demonstrating they are connected, present and relevant to customers as they navigate their daily lives, and focus on becoming trusted advisors in the eyes of those users.
  • While banks have a wealth of data, many also have significant technology gaps. Luckily, one of the most influential technologies today can help them address gaps between merely holding and effecitvely using data: artificial intelligence.
  • Banks can leverage AI to shorten the KYC and AML compliance requirements by conducting the necessary checks and following all the processes, just like digital bank Monzo did for its onboarding. It focused on optimizing verification accuracy, lowering signup abandonment rates, reducing manual review and improving verification speed. Banks can now get one step ahead and create a bank that is driven extensively by algorithms that nudges its customers at the right time to make the right decisions that consider customer financial goals.
  • If banks continue to rely solely on these robust, but rigid core systems, can they remain relevant to customers?
  • What banks must do in 2022 is deploy a middle layer that has the intelligence to translate data available in their core ecosystem into actionable insights. This middle layer will amplify the effectiveness of the robust core system making the bank more agile and flexible to meet customer needs while leveraging the benefit of a robust core. This can help banks effectively deliver value while taking informed decisions to remain profitable.”


AI, Metro Bank and Personetics

How AI and Big Data will Transform Banking in 2019

Metro Bank is already doing that with Insights, an in-app money management tool that gives customers complete control of their finances. It alerts customers when there’s not enough money to cover a likely spend, recommends a top up before an automated payment is due, flags if a customer has accidentally been charged twice and alerts the customer when there has been any kind of unusual activity.


Metro Bank personalises advice with Insights

Metro Bank has gone live with Insights, an in-app money management tool, which uses artificial intelligence (AI) to generate bespoke tips and alerts.

The feature was developed with Personetics, a developer of an opt-in tool for predictive analytics of users’ spending patterns.

As well as alerts that anticipate customers’ spending, users will be able to see a breakdown of where their money goes each month, delve into individual spending categories, and receive bespoke tips about how to manage their finances, based on their specific circumstances.



Predicting the ROI of AI – Pitfalls to AI Adoption in the Enterprise (Part 3 of 3) – Daniel Faggella

  • If you work for a results oriented company, the topic of ROI will be central to your pitch for funding/capital. In this post Daniel from emerj.com does a really nice job offering suggestions to get your project started. Here are a couple snippets. A link to the full post at the bottom.
    • “If you’re a banking executive and all you do is read banking press releases before you spend money with AI vendors, you are inevitably going to be investing in the wrong places. It makes sense to get a deep understanding of where a return on investment is being garnered with AI in your sector.
    • They’re re-imagining their business in the era of Amazon, and recommendations is a very big priority for them. If that’s the case, it’s worth understanding which facets of recommendations within the world of eCommerce and brick-and-mortar retail are actually garnering a return.
    • So when we’re looking for an ROI as a business, we might want to look for a technology we’re already shopping for that might be served via an artificial intelligence vendor in a way that is going to be relatively easy in terms of integration.”


    AI and the bottom line: 14 examples of artificial intelligence in finance

    “Builtin put together a rundown of how AI is being used in finance and the companies leading the way. 

    Credit Decisions

    ZestFinance – https://www.zestfinance.com

    Scienaptic Systems – https://www.scienaptic.com

    Underwrite.ai – http://www.underwrite.ai

    DataRobot – https://www.datarobot.com

    Managing Risk

    Kensho – https://www.kensho.com

    Ayasdi – https://www.ayasdi.com

    Quantitative Trading

    Kavout – https://www.kavout.com

    Alpaca – http://www.alpaca.ai

    Personalized Banking 

    Kasisto – https://kasisto.com

    Abe AI – https://www.abe.ai

    Trim – https://www.asktrim.com

    Cybersecurity & Fraud Detection

    Shape Security – https://www.shapesecurity.com

    Darktrace – https://www.darktrace.com/en/

    Vectra – https://www.vectra.ai


    Emirates NBD launches WhatsApp banking

    “Emirates NBD has launched the WhatsApp Business Solution to offer customised mobile banking services to its customers, claiming to be a first in the region.

    The implementation, carried out in partnership with Infobip, allows customers to interact with the bank through the chat for functions such as checking account balances, the last five transactions of account or credit cards, or the last credit card mini statement, temporarily blocking or unblocking cards, new cheque book requests and checking foreign exchange rates.”