Anodot: AI and Data Driven Decision Making in Banking | The Fintech Times

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Banks must replace manual monitoring with real-time monitoring analysis, and this can only be done through the use of AI and automation. These technologies will allow banks to streamline operations, improve efficiency and deliver better customer service.

Not only can AI cut costs by automating processes and reducing errors, it can help produce new revenue streams by enabling a more personalised service, which also reduces customer churn. These are the view of David Drai, Anodot‘s CEO and co-founder. Having worked in the technology sphere for over two decades, Drai has witnessed the gradual change in banks first hand. 

It is essential for a business to stay competitive in a changing environment, as well as for create new opportunities to grow, explained Drai as he told The Fintech Times about how banks must incorporate AI and automation into their systems:

David Drai, co-founder and CEO, Anodot
David Drai, co-founder and CEO, Anodot

For banks striving to keep up with the ongoing shift to a digital financial world, one of the best investments they can make is in artificial intelligence — and the reasons add up quickly. In fact, a McKinsey report from 2020 estimates that AI can deliver $1trillion in additional value to banks each year.

AI will automate and speed up, back-office processes, improving customer engagement and personalising services. It enhances security and fraud detection through monitoring and analytics. It cuts costs by automating manual processes and reducing errors. AI is essential to keeping pace with current banking trends, enabling greater implementation of online and mobile banking while reducing the need for physical locations and legacy applications. AI breaks down silos, cuts across distinct business lines and mines different repositories of data to generate actionable intelligence in real-time.

But, as the report notes, many banks have struggled to fully implement AI, held back by a mix of outdated operating models, insufficient investments in new technology and the lack of a clear AI strategy. Banks need to understand the integral role AI plays in the future of financial technologies (fintech) and payment companies. And they would do well to follow several key best practices toward making the most efficient and profitable use of the technology.

AI: Faster, More Efficient—and More Personal

The covid-19 pandemic drove many people to pursue online banking, accelerating a shift that was already underway and which will continue as more people get comfortable with not banking in person at a physical location. New mobile and online banks cropped up during the surge in online banking, creating new competition as people reevaluated their options.

As a result, banks are emphasising improved, personalised customer service with faster backend processes and more comprehensive fraud detection. As such they are turning to AI to make it happen. AI lowers costs by automating manual processes and reducing error rates, while greatly increasing speed, but the benefits of properly implemented AI solutions can go far beyond that. Its analytics capabilities can provide insights on a range of issues, parsing massive amounts of data on anything from failed or declined transactions and the total transaction amounts per product, to device usage and patterns behind multiple login attempts.

Critically, it brings a sharp eye to security, enabling improved fraud detection and faster, better-informed response and remediation.

And, somewhat ironically, the machine-based speed adds insights. For example, AI can provide leads to create more personalised services for customers. Increasingly personable chatbots are always available, handling routine questions and services, allowing human employees to focus undistracted on more complex requests — and AI’s insights allow employees to offer customers more personalised options.

6 Best Practices

Adopting AI isn’t just deploying a new technology; it represents a cultural change in how fintech companies operate. It starts at the top with a focus on business, not just technology, and must become familiar and intuitive for all employees, not just IT teams. Following essential best practices will help fuse AI into an organisation’s business strategy. For example:

  • Incorporate investments in AI into the organisation’s strategic plans, rather than treating it separately as part of the IT budget.
  • Ensure that senior management and the board are fully aware of the importance of how AI and other technology will be used in the business.
  • Board members and C-level leaders must understand exactly how AI can reduce costs and increase revenues.
  • The organisation’s Chief Data Scientist should carry the message clearly, explaining to the C-suite what AI can and cannot do.
  • Understand the risks of this powerful technology. Senior leadership should be aware of the ethical implications of using AI in the business, and the kinds of dilemmas that have affected other sectors.
  • The combination of business goals and technology works both ways, so be sure the AI team has a grasp of business objectives and priorities, such as marketing goals or reducing bottlenecks in payment processing.

Time to Abandon Traditional Processes

If banks and fintech companies need a reason to adopt AI—in addition to its benefits—they need only look at their current processes in relation to the fast-moving changes in the financial and cybersecurity worlds. Manual monitoring and lag times in finding and fixing payment errors just don’t cut it anymore. Customers expect real-time services. Cybercriminals employ sophisticated, machine-driven practices that move too fast for the human eye. Without AI-assisted automation, organisations can’t streamline operations well enough to keep up.

Online banking companies making use of AI have upped the ante on processing loan applications quickly. Established banks are employing AI to improve their existing loan-writing methods, which move at a snail’s pace by comparison and often deliver an incomplete risk assessment. In addition to improving the speed and accuracy of loan applications, AI provides a host of other benefits, such as pulling information in real time from multiple billing systems to quickly reconciling any failures to charge for services—yet another way it helps increase revenues.

We are in a digital era — digital meaning automation — and automation has to be controlled and managed by AI. Banks need to operate in real-time –whether they are delivering customer service or monitoring the security landscape. In short, they need to make AI a fundamental component of their strategic plans, involving everyone from top leaders to rank-and-file workers.

The potential payoffs of implementing AI effectively are promising. Replacing manual monitoring with real-time monitoring and analysis streamlines operations, improves efficiency and delivers better customer service. And not only can AI cut costs by automating processes and reducing errors, it can help produce new revenue streams by enabling a more personalised service, which also reduces customer churn. It’s essential to staying competitive in a changing environment, as well as for creating new opportunities to grow the business.

About Anodot:

Anodot applies AI to deliver autonomous analytics in real-time, across all data types, at enterprise scale. Unlike the manual limitations of traditional Business Intelligence, we provide analysts mastery over their business with a self-service AI platform that runs continuously to eliminate blind spots, alert incidents, and investigate root causes. Anodot has nearly 100 customers in digital transformation industries like ecommerce, FinTech, AdTech, Telco, Gaming, including Microsoft, Lyft, Waze, and King. Founded in 2014, Anodot is headquartered in Silicon Valley and Israel, with Sales offices worldwide.

David Drai, co-founder and CEO, Anodot: linkedin.com/in/daviddrai

Go to Publisher: The Fintech Times
Author: The Fintech Times