Three ML and AI Uses That Are Powering the Growth in Automation in the Financial Services Industry

A survey of 1,419 customers, including more than 150 in the financial services sector, conducted by MIT Technology Review Insights in association with Google, found that marketers in the industry are among the most progressive in deploying machine learning (ML).

The financial services industry faces challenges on adopting ML due to the strict compliance regulations, especially in Europe with the new General Data Protection Regulation (GDPR). However, the research shows that 41 percent of financial services marketers currently use ML. The survey data also indicates that ML adoption will continue to crest: another 30 percent of financial services marketers plan to deploy the technology within the year.

I’ve been working for an AI tech company for the last seven months and we’ve been focusing on the financial services industry over the last couple of months. Here are some of the lessons learned, that are also reflected on findings from the MIT Survey.

Operational Efficiency

Banks are the first ones to ask how much they can save on operational cost if they transfer their human client support to an automated one.

Data from a UK leading bank shows that 73 percent is waste for the front line in traditional customer service. Voice agents and chatbots can play a significant role in your success story, expanding your business online or managing customer queries efficiently.

Survey respondents report making particular progress in the automation of customer inquiries.

The average respondent indicates that between a quarter and a half of all inquiries are now completely resolved through automated channels, and nearly one in ten indicated that the majority of inbound customer contact is fully automated.

That percentage is even higher among customer experience leaders, indicating that customer- centric firms are able to manage both the escalation of full contact automation without loss of customer satisfaction.

Predictive Marketing

Companies can harness the power of AI to improve customer engagement through actionable insights on sentient, content and meaning of every client interaction. But most importantly, ensuring that all data gathered through these interactions is funnelled into all areas of the company to predict customer’s behaviour and adjust commercial processes.

This is something that I personally found interesting since technology is now able to automate and connect the dots throughout the entire customer journey.

In the survey, 60 percent of financial services marketers said they believe ML can capture intent throughout the entire customer journey. The ability to contextually examine connections and relationships enables marketers to analyse the customer journey, from initial contact with a brand to conversion and ongoing engagement. They can use ML to trace the first sales or marketing pitch to the actions that led to the buying decision and use the insights they glean to improve areas such as customer service and support.

Sentiment Analysis Helps Manage Costs

For the majority of survey respondents, operational costs have increased, but less so for those that invest in customer sentiment analysis. Companies using sophisticated tools such as natural language analysis are generally the leaders in customer experience technology deployment and are more able now to see cost performance results from these investments.

Most of the difficulties we’ve faced are related to sentiment analysis in different languages. Sentiment analysis requires a lot of customisation and cannot be applied on templates across industries and languages. However, by investing in tools that drive deeper customer understanding, they are able to make smarter investment decisions.

Sources:

MIT Global Research: Humans + Bots: Tension and Opportunity,https://www.genesys.com/resources/mit-global-research-humans-bots-tension-and-opportunity?thankyou=109214&page_type=resources&page_attr=Research%20Report%3BEnterprise%3BMid-Market&cid=7010d000000mbLV

AI Trends, “Conservative Financial Industry Progressing with Machine Learning”, https://www.aitrends.com/financial-services/conservative-financial-industry-progressing-with-machine-learning/