ऋण अधिकारी
व्यापार और वित्तAI एक्सपोजर
- डेटा स्रोत: BLSप्रकाशन: 2026-08
बहुत उच्च· सापेक्ष
कमचार सापेक्ष श्रेणियाँबहुत उच्चव्यवसाय-समूह स्तर का मान
मापक्रम, आधार और स्रोत
चार सापेक्ष बैंड (कम / मध्यम / उच्च / बहुत उच्च)
BLS रोज़गार पूर्वानुमान तालिका के 831 विस्तृत व्यवसायों के आधार पर। मान NEM (नेशनल एम्प्लॉयमेंट मैट्रिक्स) कोड के स्तर पर दिया जाता है, इसलिए एक ही NEM कोड वाले व्यवसायों को वही बैंड मिलता है
- डेटा स्रोत: Anthropicप्रकाशन: 2026-03
0.186
0.000यहाँ दिए गए मानों की सीमा0.745मापक्रम, आधार और स्रोत
- डेटा स्रोत: ILOप्रकाशन: 2025
0.60
0.09यहाँ दिए गए मानों की सीमा0.70व्यवसाय-समूह स्तर का मान
मापक्रम, आधार और स्रोत
जेनरेटिव AI एक्सपोजर सूचकांक, प्रकाशित रूप में 0–1
ISCO-08 यूनिट समूह — समान कोड वाले सभी व्यवसायों को यही मान मिलता है
यह इस साइट की गणना है, ILO द्वारा प्रकाशित आँकड़ा नहीं: इस साइट द्वारा ILO डेटासेट से जोड़े गए 1,012 व्यवसायों में से 4% इस मान के बराबर या उससे अधिक हैं।
यह स्रोत किस प्रकार का आँकड़ा प्रकाशित करता है
BLS की श्रेणी सापेक्ष रैंक है, निरपेक्ष स्तर नहीं, और यह प्रथम-हस्त माप भी नहीं है: यह कई प्रकाशित अध्ययनों में व्यवसाय की पर्सेंटाइल रैंकों को चार बैंडों में बांटती है। यह रोज़गार या वेतन का पूर्वानुमान नहीं है, न अपनाए जाने की संभावना, और यह स्वचालन और संवर्धन में अंतर नहीं करती।
Task-level exposure
केवल एक्सपोज़र वाले कार्य| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Explain to customers the different types of loans and credit options that are available, as well as the terms of those services.13-2072 | 0.088175.6 | 0.014326.8 |
Market bank products to individuals and firms, promoting bank services that may meet customers' needs.13-2072 | 0.00564.8 | 0.00397.3 |
Analyze potential loan markets and develop referral networks to locate prospects for loans.13-2072 | 0.00524.5 | 0.011321.2 |
Handle customer complaints and take appropriate action to resolve them.13-2072 | 0.00403.4 | 0.012623.6 |
Prepare reports to send to customers whose accounts are delinquent, and forward irreconcilable accounts for collector action.13-2072 | 0.00342.9 | —0 |
Analyze applicants' financial status, credit, and property evaluations to determine feasibility of granting loans.13-2072 | 0.00292.5 | 0.00387.1 |
Obtain and compile copies of loan applicants' credit histories, corporate financial statements, and other financial information.13-2072 | 0.00242.1 | 0.005810.9 |
Confer with underwriters to aid in resolving mortgage application problems.13-2072 | 0.00201.7 | —0 |
Work with clients to identify their financial goals and to find ways of reaching those goals.13-2072 | 0.00151.3 | —0 |
Provide special services such as investment banking for clients with more specialized needs.13-2072 | 0.00151.3 | —0 |
| Not observed on any surface — 12 task(s) — These tasks have no row in the source for this release. The 0 in the share row is a display-stage composition ratio; absence is what the — in the raw row states. | ||
Approve loans within specified limits, and refer loan applications outside those limits to management for approval. | —0 | —0 |
Meet with applicants to obtain information for loan applications and to answer questions about the process. | —0 | —0 |
Review and update credit and loan files. | —0 | —0 |
Review loan agreements to ensure that they are complete and accurate according to policy. | —0 | —0 |
Compute payment schedules. | —0 | —0 |
Stay abreast of new types of loans and other financial services and products to better meet customers' needs. | —0 | —0 |
Submit applications to credit analysts for verification and recommendation. | —0 | —0 |
Supervise loan personnel. | —0 | —0 |
Set credit policies, credit lines, procedures and standards in conjunction with senior managers. | —0 | —0 |
Arrange for maintenance and liquidation of delinquent properties. | —0 | —0 |
Interview, hire, and train new employees. | —0 | —0 |
Petition courts to transfer titles and deeds of collateral to banks. | —0 | —0 |
Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.
| Task | βE1 + 0.5 × E2 |
|---|---|
Explain to customers the different types of loans and credit options that are available, as well as the terms of those services.O*NET Task ID 3410 | 1.0 |
Review loan agreements to ensure that they are complete and accurate according to policy.O*NET Task ID 3413 | 1.0 |
Compute payment schedules.O*NET Task ID 3414 | 1.0 |
Prepare reports to send to customers whose accounts are delinquent, and forward irreconcilable accounts for collector action.O*NET Task ID 3426 | 1.0 |
Authorize or sign mail collection letters.O*NET Task ID 21636 | 1.0 |
Review billing for accuracy.O*NET Task ID 21647 | 1.0 |
Approve loans within specified limits, and refer loan applications outside those limits to management for approval.O*NET Task ID 3407 | 0.5 |
Meet with applicants to obtain information for loan applications and to answer questions about the process.O*NET Task ID 3408 | 0.5 |
Analyze applicants' financial status, credit, and property evaluations to determine feasibility of granting loans.O*NET Task ID 3409 | 0.5 |
Obtain and compile copies of loan applicants' credit histories, corporate financial statements, and other financial information.O*NET Task ID 3411 | 0.5 |
Supervise loan personnel.O*NET Task ID 3422 | 0.0 |
β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.
Data sources & licenses — O*NET®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page