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What’s AI in Finance?

From:Nexdata Date: 2024-08-15

Table of Contents
Application of AI in finance
Nexdata AIFinance data services
Mobile phone speech data sets

➤ Application of AI in finance

The rapid development of artificial intelligence is inseparable from the support of high-quality data. Data is not only the fuel that drives the progress of AI model learning, but also the core factor to improve model performance, accuracy and stability. Especially in the field of automatic tasks and intelligent decision-making, deep learning algorithms based on massive data have shown their potential. Therefore, having well-structured and rich datasets has become a top priority for engineers and developers to ensure that AI systems can perform well in a variety of different scenarios.

The banking industry is going digital and becoming intelligent, and artificial intelligence as a “new infrastructure” has become a consensus. The IDC report shows that 90% of banks have begun to explore the application of artificial intelligence, and AI technology has become the main direction of bank technology innovation.

According to iResearch’s statistics, the AI+financial core market will reach 29.6 billion yuan in 2021, driving related industries to 67.7 billion yuan. By 2026, the core market will reach 66.6 billion yuan, driving related industries to 156.2 billion yuan.

Intelligent Finance (AiFinance) is the comprehensive integration of artificial intelligence and finance, with artificial intelligence, big data, cloud computing, blockchain and other high-tech as the core elements, fully empowering financial institutions, improving the service efficiency of financial institutions, and expanding financial services The breadth and depth of the system enable the whole society to obtain equal, efficient and professional financial services, and realize the intelligentization, personalization and customization of financial services.

➤ Nexdata AIFinance data services

Application Scenerios of AIFinance

● Intelligent customer acquisition
Relying on big data, the portrait of financial users is carried out, and the efficiency of customer acquisition is greatly improved through the demand response model.
 Identification
With artificial intelligence as the core, through technical means such as living body recognition, image recognition, voiceprint recognition, OCR recognition, etc., the identity of the user is verified, which greatly reduces the cost of verification.
● Big data risk control
Through the combination of big data, computing power, and algorithms, build anti-fraud, credit risk and other models to control the credit risk and operational risk of financial institutions in multiple dimensions, while avoiding asset losses.
● Robo-advisor
Based on big data and algorithm capabilities, user and asset information are tagged to accurately match users and assets.
● Intelligent customer service
Based on natural language processing capabilities and speech recognition capabilities, expand the depth and breadth of customer service, significantly reduce service costs, and improve service experience

Nexdata AIFinance Data Solutions

In the field of AIFinance, Nexdata provides data services in various interactive scenarios, such as intelligent customer service, face recognition, anti-spoofing and knowledge graphs.

● 23,110 People Multi-race and Multi-pose Face Images Data

This data includes Asian race, Caucasian race, black race, brown race and Indians. Each subject were collected 29 images under different scenes and light conditions. The 29 images include 28 photos (multi light conditions, multiple poses and multiple scenes) + 1 ID photo. This data can be used for face recognition related tasks.

● 1,417 People — 3D Living_Face & Anti_Spoofing Data

The collection scenes include indoor and outdoor scenes. The dataset includes males and females. The age distribution ranges from juvenile to the elderly, the young people and the middle aged are the majorities. The device includes iPhone X, iPhone XR. The data diversity includes various expressions, facial postures, anti-spoofing samples, multiple light conditions, multiple scenes. This data can be used for tasks such as 3D face recognition, 3D Living_Face & Anti_Spoofing.

● 25,820 People Face Recognition Data with Identification Photos

25,820 People Face Recognition Data with Identification Photos.The race distribution of data includes Asian race, Caucasian race, black race and brown race. For each subject, one ID photo and 5–10 life photos were collected. This data can be used for face recognition.

● American English Natural Dialogue Speech Data

2000 speakers participated in the recording and conducted face-to-face communication in a natural way. They had free discussion on a number of given topics, with a wide range of fields; the voice was natural and fluent, in line with the actual dialogue scene. Text is transferred manually, with high accuracy.

● 211 Hours — German Speech Data by Mobile Phone_Reading

The data set contains 327 German native speakers’ speech data. The recording contents include economics, entertainment, news, oral, figure, letter, etc. Each sentence contains 10.3 words on average. Each sentence is repeated 1.4 times on average. All texts are manually transcribed to ensure the high accuracy.

➤ Mobile phone speech data sets

● 357 Hours–Korean Speech Data by Mobile Phone

357 hours of Korean speech data collected by cellphone. It is recorded by 999 Korean in quiet environment and is rich in content. All texts are transtribed by professional annotator. The accuracy rate of sentence is 95%. It can be used for speech recognition, machine translation and voiceprint recognition.

● 769 Hours — French Speech Data by Mobile Phone

The data volumn is 769 hours and is recorded by 1623 French native speakers. The recording text is designed by linguistic experts, which covers general interactive, in-car and home category. The texts are manually proofread with high accuracy. Recording devices are mainstream Android phones and iPhones.

● 435 Hours — Spanish Speech Data by Mobile Phone

The data volumn is 435 hours and is recorded by 989 Spanish native speakers. The recording text is designed by linguistic experts, which covers general interactive, in-car and home category. The texts are manually proofread with high accuracy. Recording devices are mainstream Android phones and iPhones.

● 234 Hours-Japanese Speech Data by Mobile Phone

It collects 799 Japanese locals and is recorded in quiet indoor places, streets, restaurant. The recording includes 210,000 commonly used written and spoken Japanese sentences. The error rate of text transfer sentence is less than 5%. Recording devices are mainstream Android phones and iPhones.

End

If you want to know more details about the datasets or how to acquire, please feel free to contact us: info@nexdata.ai.

In the development of artificial intelligence, the importance of datasets are no substitute. For AI model to better understanding and predict human behavior, we have to ensure the integrity and diversity of data as prime mission. By pushing data sharing and data standardization construction, companies and research institutions will accelerate AI technologies maturity and popularity together.

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