Financial Services are experiencing AI application in three major areas: Firstly; Machine Learning; to produce propensity models. Banks and insurance companies are putting machine learning on websites or mobile channels for real-time target marketing. ML predict the product propensity of their customers based on their behavioural data in real-time.

Secondly, it is applied around natural language processing, like chatbot, contract intelligence and so on, where AI can read the free text in a contract and detect non-compliance in the document.

Thirdly, it is applied in image recognition. For instance, customers can take a snapshot of their image and take a picture of their identity documents. The machine can match the two objects automatically and support the bank in KYC and on-boarding. For artificial intelligence to work effectively, financial institutions need to have a lot of big data which provides a pool of resources that enable the creation of useful business insights. JETHRO’s jBI is an efficient Business Intelligence Suite.

Financial services around the world are being optimised with one or more of the following: artificial intelligence (AI)/machine learning (ML), cloud computing, robotic process automation (RPA), distributed ledger technology (DLT), Internet of Things, analytics and big data. These technologies are at different stages of maturity.

For instance, a large Financial Institution in Europe developed an AI trade-matching tool that automates trade management services via predictive analysis of historical data to discover patterns in trades, resulting in prompt decision making. Also, major banks in Europe developed AI bond trading tool; that support human traders by speedily gathering bond prices.


Impact of AI in Insurance

“Emerging technologies – like big data, the Internet of Things (IoT), mobile technology, blockchain, wearable devices and artificial intelligence (AI) – are revolutionizing the insurance industry and changing consumer expectations and preferences…” via collaborative efforts with FinTech companies; the National Association of Insurance Commissioners (NAIC), stated.For instance; Praedicat INC an insurance company, is using machine learning to scan and profile massive data to detect the possibility of product litigation risk generated during their lifecycles.Similarly, gomedici shared that Shift Technology helped insurers in Europe to evaluate 13 million claims and detected 3,000 new instances of possible fraud as well as a malicious scheme that continued to steal millions of Euros from the insurers company over many years.In addition, Cytora is using AI and open-source data to help business insurers to loss ratios, grow premiums, and improve expenses. InsurTech innovations are happening all over the insurance industry via AI.

Impact of AI in America’s 6 Top Banks

Techemergence shared on the level of AI application at 6 top banks in US, classified by Federal Reserve as follows:-

JPMorgan Chase recently launched a Contract Intelligence platform for evaluating legal documents. The manual review of 12,000 annual commercial credit usually take about 360,000 hours. However, the new platform evaluated the same quantity in seconds.
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Similarly, Wells Fargo revealed a new Artificial Intelligence Enterprise Solution to accelerate its payment infrastructure and API for corporate banking customers resulting in huge time saving.

Also, Bank of America recently announced its intelligent virtual assistant; Erica – a chatbot that uses predictive analytics and cognitive messaging to provide financial advice to more than 45 million customers. Erica is available to clients 24/7 and support daily transactions.

In addition, CitiBank recently implemented Feedzai, a real-time global data science enterprise that detects and exterminates fraud in all route of trading as well as online and in-person banking. It performs massive evaluation of large amount of rapid data to detect fraudulent activities and notify customers accordingly.
PNC has not achieved much in its AI research transformation, unlike Chase and Wells Fargo. AI is still at awareness stage in PNC. However, there is indication of transformations in the coming years.

Bank of NY Mellon Corp; a 233-year-old financial institution currently utilize robotic process automation (RPA) to improve the performance of its operations and to ensure cost reduction. RPA mingles with artificial intelligence via software applications. The banks boast of the following results: 100 percent accuracy in account-closure validations across five systems; 88 percent improvement in processing time; 66 percent improvement in trade entry turnaround time; ¼-second robotic reconciliation of a failed trade vs. 5-10 minutes by a human; and $300,000 in annual savings.AI scientists continue to improve the technology with the aim of passing the turning test by which customers can interact with the machine without knowing.