Is Artificial Intelligence (AI) the secret to automation and growth

Claire Gibbons

What Is Artificial intelligence (AI)?

Artificial intelligence (AI) is used in various aspects of our lives and every day we are surrounded by companies, technologies and devices that use AI. You unlock your phone using face recognition, social media personalises your feeds, spam emails are filtered from your inbox and banking systems determine if your latest purchases are fraudulent, not to mention ChatGPTs disruption of how we interact with AI. What may have until recently felt new, exciting and progressive is now becoming the norm, and 2023 will go down in history as a pivotal time for AI.

Financial Institutions, Central Banks, FinTechs and Payments providers globally had no option but to move operations online quickly to keep up with an ever-changing world. Digital is the new operating model and AI holds the key to success in the financial sector. Large banking and financial institutions recognised the advantages of AI early on and have successfully implementing the technology for various purposes.

  • Revolut use machine learning to protect you from fraud, leveraging vast amounts of payment data to identify abnormal activity which deviates from users usual behaviour.
  • Erica, an AI employee of the National Bank of America is a digital financial assistant and has already served over 7 million customers and handled over 50 million queries. 
  • MyBank has lent to over 16 million small businesses in China using its AI powered 310 model, 3 minute application online, 1 second decision and 0 human intervention.

Methods of Artificial Intelligence

Machine Learning is the main driving force behind AI. In simple terms, Machine Learning takes large amounts of data and learns to detect patterns. This enables it to predict future outcomes as well as reveal other insights about the data. 

Statistical techniques are used to create an algorithm to parse data, identify patterns, translate those patterns into rules, and make determinations or future predictions.

It has the ability to detect trends and patterns from historical data that may be too complex or subtle for humans to identify or programmers to code. This ability to detect and analyse such data patterns or relationships sets AI-based algorithms apart from traditional algorithms.

AI Driven Lending

Banks, Credit Unions, Building Societies and non-bank lenders need to future proof their lending processes. Customers won’t accept anything less than convenient, secure and easy to use digital services. Millennials and Gen Z, in particular, prefer digital channels over physically going into a branch or phoning in, and already experience the speed and convenience of AI driven digital interactions in all other areas of their lives.

Lending at its core is a data problem, making it naturally suited for Machine Learning models and algorithms. Machine Learning gives lenders better insights into a borrower’s ability to pay by working with historical data sets and more complex calculations than traditional models. While traditional underwriting focuses on credit scores and income data, automated models can include a wider set of alternative data, leveraging Open Finance to automate data gathering and processing. Extra data sources provide more insight into people and businesses with established credit scores, but it can also be particularly useful for determining creditworthiness without a traditional credit history.

While most loan applications are reviewed by a human underwriter, some loans could be automatically approved or rejected based on thresholds set by the lender.

Practical applications of AI in lending include:

  • Faster acquisition and online application processes with automated data gathering, extraction and validation
  • Consistent, transparent and quicker decisions
  • KYC, ID&V and fraud detection, including identity fraud and document validation
  • Real time data analytics and forecasting for business processes

The Benefits of AI Driven Lending

The use of AI has a positive impact on the lender because it eliminates time and effort involved in origination, onboarding and underwriting. Automated machine learning models assess the borrower’s risk faster and more accurately. Online loans enable greater self-service for the borrower, and applications processed in a matter of seconds instead of days, with the help of AI driven solutions.

At Luna Connect we believe the future of financial services for organisations of all sizes is frictionless digital experiences, and online growth demands faster, better decisions. AI is the key ingredient in achieving this future and is the core of our software platform used by financial services companies to efficiently grow online while reducing operational costs.

Where do I start?

AI, automation and other forms of digitisation may seem overwhelming at first glance. The complexity lies in how to make digitisation a reality in a traditional organisation without any external standards to measure how well you are performing. At Luna Connect we have developed a free tool to help you plan your automation journey, check out our lending automation assessment to find out how you can start your own journey BENCHMARK YOUR LENDING OPERATION USING THE 6 LEVELS OF LENDING AUTOMATION

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Claire Gibbons
Claire is a Data Scientist at Luna Connect, and is passionate about Data Analytics, Machine Learning and Artificial Intelligence. Women and girls in Tech and STEM advocate.