The Future of Artificial Intelligence in Banking

2017-06-28
Price :
Published : Jun-2017
No. of Pages : 35

Artificial Intelligence (AI) has reached the stage where it is sufficiently advanced and affordable to warrant practical implementation in financial services. Banks are busy exploring ways in which they can harness the power of AI to streamline internal processes and improve the customer experience. This report will explore what AI applications are relevant in banking at this time, examine where AI is already making an impact, and offer recommendations on how banks should proceed.

Several aspects of banking are ripe for AI-driven intervention. Many of their data-driven back-office processes are high volume and repetitive in nature, and hence are ideal candidates for intelligent automation. At the front end, with the majority of customer interactions occurring through digital channels, there is also considerable scope for AI to improve the quality of and add value to the user experience.

Key findings include in this report –

  • AI encompasses a wide range of technologies, including robotic process automation (RPA), natural language processing (NLP), advanced data analytics, and image analytics. Use of these technologies will help banks improve both front-office and back-office processes.
  • Customer-facing uses of AI include chatbots that improve communication between banks and their customers, advanced analytics that can offer proactive advice to consumers and take simple financial decisions on their behalf, and facial recognition that improves onboarding and makes it easier for consumers to log into their accounts.
  • Back-office AI implementations include algorithms that can identify and block cases of fraud and money laundering, and analysis of non-traditional data to assess the creditworthiness of borrowers who lack standard credit records.

Critical success factors

  • Improve data quality: AI algorithms depend on access to high quality data to work effectively. Banks must move away from siloed and fragmented databases towards a single view of their customers. This will give the algorithms access to enough data to make effective decisions.
  • Collaborate with AI specialists: AI is an incredibly complex field, and banks are best advised to partner with AI specialists. This will enable them to launch AI-based services quicker and cheaper than if they were to develop solutions in-house.
  • Address potential execution risks:Banks need to be aware of the possible pitfalls of using AI, such as algorithm bias, a lack of transparency around decision-making, and concerns with data privacy. Steps should be taken to minimize these risks.

The report “The Future of Artificial Intelligence in Banking” examines the most significant uses of AI in retail banking, in both front-office and back-office implementations.

Additionally, this report insight into following –

  • The particular manifestations of AI that have the most relevance for banking.
  • How leading banks are already implanting AI-based solutions.
  • The factors banks need to address when introducing AI applications.

Companies mentioned in this report: Admiral, Amazon, Atom Bank, Bank of America, DataVisor, Ernest, EyeVerify, Facebook, Google, IDnow, Kasisto, Lenddo, Moneyhub Enterprise, Olivia, PayPal, Personetics, Plum, POSB, Starling Bank, USAA, TrustingSocial, Wells Fargo, ZestFinance.

Scope

  • AI encompasses a wide range of technologies, including robotic process automation, natural language processing, advanced data analytics, and image analytics. Use of these technologies will help banks improve both front-office and back-office processes.
  • Customer-facing uses of AI include chatbots that improve communication between banks and their customers, advanced analytics that can offer proactive advice to consumers and take simple financial decisions on their behalf, and facial recognition that improves onboarding and makes it easier for consumers to log into their accounts.
  • Back-office AI implementations include algorithms that can identify and block cases of fraud and money laundering, and analysis of non-traditional data to assess the creditworthiness of borrowers who lack standard credit records.

Reasons to buy

  • Discover where AI will have the most impact upon the delivery of banking services.
  • Learn how your competitors are already using AI to improve customer outcomes and profitability.
  • Understand what issues you must resolve in order to successfully launch AI-based services.
Filed in: Banking & Finance
Publisher : GlobalData
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