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Build me a NLP model to extract hidden costs from financial statements

I would like to build a deep learning model using NLP that is able to recognize hidden costs in a 10-K or 10-Q financial statement, and extract the monetary value. There are about 7 different expense categories, each category has different keywords.

Here are some examples:

---

"Exploratory dry-hole costs were $12.7 million, $1.3 million, and $1.0 million for the years ended December 31, 2012, 2011, and 2010, respectively."

Keyword: "dry-hole costs", "2012"

Output: $12.7 million

---

"2012 includes the recognition of a $3,340 million impairment charge related to the carrying value of Citi's remaining 35% interest in the Morgan Stanley Smith Barney joint venture"

Keyword: "impairment charge"

Output: $3,340 million

---

"During the year ended December 31, 2017, we decided to discontinue the internal development of AMG 899, resulting in an impairment charge of $400 million for the IPR&D asset"

Keyword: "impairment charge"

Output: $400 million

---

"We incurred $146 million of pre-tax expenses in 2017 related to Hurricane Maria."

Keyword: "incurred ... expenses"

Output: $146 million

---

"In fiscal 2019, we recorded a $53 million charge related to the fair value adjustment of inventory acquired in the Blue Buffalo acquisition."

Keyword: "recorded a ... charge", "fair value adjustment"

Output: $53 million

---

This is just one category, I have about 100 examples of how they are applied across historic statements that can feed into an initial training set.

There are some problematic sentences that need to be avoided. For example:

"We made $100 million in profit this year, despite having significant restructuring expenses"

The algorithm should realise that although "restructuring expenses" exists in the sentence, the "$100 million" does not refer to it, but to something else and should be ignored.

There are also cases where multiple values are provided in a single sentence, and it needs to pick out the right year:

"Restructuring expenses were $40,000 in 2020, $30,000 in 2019 and $20,000 in 2018"

The correct value here should be $40,000.

I have experimented using spaCy and prodigy, but I am not sure on the best approach. One idea is to develop a NER model that recognizes if a keyword exists in a sentence, and then uses another model to parse the $ value from the sentence, using the year if necessary. It might be better to just use a single training model.

If you need any further details, please reach and out and I can give you more context.

Kemahiran: Perlombongan Data, Bahasa Semulajadi, Kecerdasan Buatan, Python, Machine Learning (ML)

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Tentang Majikan:
( 0 ulasan ) Germany

ID Projek: #29836406

18 pekerja bebas membida secara purata €632 untuk pekerjaan ini

(68 Ulasan)
6.1
liveexperts123

Hi there,I'm biddin on your project "Build me a NLP model to extract hidden costs from financial statements" I have read your project description and i'm an expert in Machine learning/Python/C++/Java and Data science t Lagi

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achuthrao

Hello, I am Achuth. I am a researcher at the Indian Institute of Science Bangalore. I have 6+ years of experience in machine learning and deep learning. Please refer to my profile for more info I am familiar with PyTo Lagi

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techplusintl

Hi there, ★★★ Python / C++ / Machine Learning (ML) Expert ★★★ 10+ Years of Experience ★★★ I've read requirements and ready to create model to extract hidden costs from financial statements. We are a team of profession Lagi

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vorasiddh4it

I have read project requirements. I can give you more than 95% accuracy in this. Also, If you want to see demo then I will show you. I am managing director of software company and I have team for development so we ca Lagi

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tecogno

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vvreddy221

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sajjadtaghvaeifr

Hi, I hope you are doing fine. I have almost 10 years of experience in machine learning algorithms. I can implement various types of artificial intelligence algorithms including yours with Matlab, Python and etc. I hav Lagi

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ATeam17

Greetings, I hope you doing fine. I have been working in the field of Data Science for past 4 years with many top Fortune 500 US clients. Please check my portfolio and my LinkedIn profile to know more about my work. h Lagi

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vndeee

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snbhanja

Hi I have done similar extractive work in the past using deep learning. I am able to extract info correctly from the all example you shared except one wrong. I can retrain and fine tune the model. Let's discuss about Lagi

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helazna

Hello, Thanks for your posting and i read your description carefully. I have 7 years experiences of Machine Learning, NLP projects before such follows. - Text Generation and Classification - Auto ChatBot, Recommendati Lagi

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valeriyburykin

Hi I'd like to apply this job, as I have a lot experience in NLP(natural language processing) area I have experiences various kinds NLP tasks such as: - Text/topic classification & clustering - Text Summarization - Se Lagi

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Sandeep2805

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shabeermian

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nanditapatel2021

----- Build me a NLP model to extract hidden costs from financial statements ----- Hi! I'm 5 years experienced Data Scientist with experience in NLP, Data Science, Machine Learning & Deep Learning ready to do your wor Lagi

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knightmlpraput

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