follow this instructions and train one model 

demo dataset to understand better

generatw the code to train one advanced model on this dataset and test will all the matrices

you can use any advanced technique to train but metrices should be good

## UPI Synthetic Data Hackathon Instruction Manual

## Overview

Welcome to the UPI Fraud Detection Hackathon! In this event, you will be
tasked with building a fraud detection model using machine learning algorithms on the synthetic data generated from the UPI data. The model will be tested on how accurately it can predict fraudulent transactions from the synthetic data.
<br/>

The synthetic data was generated using a Generative AI model, which was trained on a curated sample of UPI data.
UPI interface facilitates inter-bank peer-to-peer and person-to-merchant
transactions. It is used on Mobile devices to instantly transfer funds
between two bank accounts. UPI also lets you make payments by scanning
QR codes at your nearby stores. UPI is designed to promote financial
inclusion and provide access to banking services for individuals who may
not have access to traditional banking services.

## Participants in UPI Transaction:
1. Remitter bank
2. Beneficiary bank
3. Payer PSP
4. Payee PSP
5. NPCI
6. Payer/Payee

## UPI has specific functionalities such as below:
1. **One time mandate:**  The one-time mandate gives you the facility
to schedule a payment in the future date.
2. **Recurring mandate :** The autopay allows users to make recurring
transactions automatically through UPI apps.
3. **E-RUPI:** It's a digital voucher which is issued to the end user
by any sponsor with the help of the certified bank happening in UPI
platform. The e-RUPI would be shared with the users for a specific
use by organisations via SMS or QR code.
4. **PPI on UPI:** UPI transactions are real-time transactions between
two bank accounts, whereas PPI transactions involve prepaid payment
instruments like mobile wallets, gift cards, and other virtual
payment modes.
5. **123Pay (voice-based payments):** The UPI 123PAY
functionality allows you to make UPI payments over a phone call
through bank's IVR number 9188-123-123 i.e. no need to have
smartphone or internet connectivity.
6. **UPI Lite (Single FA payments):** With UPI Lite, you can make
payments of up to ₹200 INR without the use of a UPI PIN on the
TPAPs.
7. **UDIR (Unified Dispute and Issue Resolution) mechanism:** To
raise dispute regarding transactions if any.
8. **Credit card on UPI:** Credit cards on UPI gives our customers
access to the ease and convenience of transacting on UPI while they
continue to enjoy the benefits of a credit card. They do not even
have to carry the card with them., etc.


## UPI Fraud Model
The NPCI helps the banks and customers to carry out secure payment transactions by identifying and detecting fraud that can take place on the UPI network. At a high level, there are primarily two ways that UPI fraud occurs.

1. **Social Engineering Frauds**
2. **Technical Frauds**

The NPCI makes predictions about a transaction that will be fraudulent
or not and stops the transaction if it is fraudulent. This helps in
regulating such types of fraud and preventing frauds from taking place
through UPI. Scammers misuse the payment request option in UPI-enabled
apps to source the PIN or OTP necessary to authorize a transaction. They
initiate a payment request and accordingly contacts the individual to
ask for the OTP or PIN, which they say is needed on their end to
complete a transaction.

#### Social Engineering Frauds <hr/>
People can be tricked into disclosing their bank information, such as
card numbers and UPI pins, by engaging in social engineering fraud.
Typically, this is done by calling the target and persuading them to
disclose the information, or by installing screen sharing software on
the target's phone and trying to extract the information.


#### Technical Frauds <hr/>
Technical types of frauds are those frauds that can arise when there are
some vulnerabilities in the devices or apps are certain components
within the system, fraudsters try to leverage these loopholes to fraud
the victims.
<br/>

## Dataset

The dataset for this hackathon includes a set of anonymized synthetic transaction records, labelled as either fraudulent (Y=1) or genuine (Y=0). 

The dataset contains a mix of profiling-features and transaction level raw features. The features such as: txn_id, trndate, payee_bank, payee_tpap, txn_type, initiation_mode, payer_requested_amount, payer_tpap, payer_bank, payee_account_number, payer_address, etc. are the transaction level features. 
The profiling features are the features that were created from the historical data of the payee or the the payer for difference scenarios.  

The data is provided in a CSV format and includes the following variables. Their description are as follows:
<br/>

| **Features**              | **Description** |
| :---------------- | :------ | 
|txn_id| Serial Number|
|trndate|Completion Timestamp of transaction|
|payee_bank|The payee/s bank|
|payee_tpap|Third party app used by the payee|
|txn_type|Type of transaction (Pay or Collect)|
|initiation_mode|Additional condition to identify variants of UPI initmode = '6'  refers to UPI Tap and Pay|
|payer_requested_amount|Transaction amount|
|payer_tpap|Third party app used by the payer|
|payer_bank|The payer's bank|
|payee_account_number|The payee's account number|
|payer_address|The payers vpa address|
|fraud|Target column. If the fraud flag is 1, The particular transaction has been marked as fraud.|
|py_min_amt_payee|Minimum transaction amount of a payee account has as a payee in last 90 days|
|py_max_amt_payee|Maximum transaction amount of a payee account has as a payee in last 90 days|
|py_cnt_error_u16_payee|Count of No of U16 Error a payer account has as payee in last 90 days|
|py_cnt_error_u30_payee|Count of No of U30 error codes a payer account has as payee in last 90 days|
|nft_reqregmob_cnt|Separate NFT table based on mobile number (last 24 hours)|
|pr_min_amt_payee|Minimum transaction amount of a payee account has as a payer in last 90 days|
|pr_max_amt_payee|Maximum transaction amount of a payee account has as a payer in last 90 days|
|py_min_amt_payer|Minimum transaction amount a payer account has as a payee in last 90 days|
|py_max_amt_payer|Maximum transaction amount payer account has as a payee in last 90 days|
|py_avg_amt_payer|Average of transaction amount a payer account has as a payee in last 90 days|
|mas_deviceid_txncnt|Count of no. of transaction done with that device id in last 90 days|
|mas_deviceid_act_days|Count active days for that device id in last 90 days|
|mas_vpa_py_txncnt_payer|Count of transactions for that VPA of a payer account as payee in last 90 days|
|mas_bnkifsc_txncnt_prpy_pypr|Count of transactions between the payee and payer in last 90 days|
|mas_vpa_pr_cnt_days_payer|Count of active days for that VPA of a payer account as payee in last 90 days|
|mas_med_amt_mob_payer|Median of transaction amount of the payer account for the mobile number as a payer in last 90 days|
|mas_cnt_days_mob_payee|Count of distinct active days a payee account has as a payer for the payer mobile number in last 90 days|
|bad_trust_rank_payer|Bad score for remitter/payer generated from trust rank algorithm using graph|
|good_trust_rank_payer|Good score for remitter/payer generated from trust rank algorithm using graph|
|bad_trust_rank_payee|Bad score for beneficiary/payee generated from trust rank algorithm using graph|
|good_trust_rank_payee|Good score for beneficiary/payee generated from trust rank algorithm using graph|
|fail_by_sec_txn_ratio_payer|The ratio of total fail count to total success count as a payee by the payer|
|fail_by_sec_amt_ratio_payer|The ratio of total fail amount to total success amount as a payee by the payer|
|less5rs_by_act_ratio_payer|The ratio of count of less than 5rs transactions  received as a payee by payer|
|reg_txn_amts_payer|The regular transaction amount count (mode count of the transaction amount) as a payee by the payer|
|py_12_17_cnt_gain_rate_payer|The ratio of total count of successful transactions done in between 12pm to 17 pm  to the active days in last 90 days as payee by the payer|
|py_17_22_cnt_gain_rate_payer|The ratio of total count of successful transactions done in between 17pm to 22 pm  to the active days in last 90 days as payee by the payer|
|pr_max_amt_payer|Maximum of transaction amount a payer account has as a payer in the last 90 days|
|pr_cnt_zm_payee|Count of ZM declines as payer by the payee|
|p2p_p2m_inter_cnt_payee|Count of all the payer side interactions as payee|
|less5rs_by_act_ratio_payee|The ratio of count of less than 5rs transactions  received as a payee by payee|
|reg_txn_amts_payee|The regular transaction amount count (mode count of the transaction amount) as a payee by the payee|
|pr_med_amt_payer|Median of transaction amount for included pay and collect a payer account has as payer in last 90 days|
|pr_cnt_days_payer|Count of No of distinct Days a payer account has as payer in last 90 days|
|pr_cnt_paid_payer|Count of Distinct payee accounts a payer account has as a payer in the last 90 days|
|mas_vpa_py_txncnt_payee|Count of transactions for that VPA of a payee account as payer in last 90 days|
|mas_vpa_py_cnt_days_payee|Count of distinct days for that VPA of a payee account as payer in last 90 days|
|py_07_12_amt_gain_rate_payee|The ratio of total sum of successful transaction amounts done in between 12pm to 17 pm  to the active days in last 90 days as payee by the payee|
|py_12_17_cnt_gain_rate_payee|The ratio of total count of successful transactions done in between 12pm to 17 pm  to the active days in last 90 days as payee by the payee|
|py_17_22_amt_gain_rate_payee|The ratio of total sum of successful transaction amounts done in between 17pm to 2 pm  to the active days in last 90 days as payee by the payee|
|py_07_12_cnt_gain_rate_payee|The ratio of total count of successful transactions done in between 07am to 12 pm  to the active days in last 90 days as payee by the payee|
|py_cnt_days_payee|Count of no. of Active Days a payee has as a payee in last 90 days|
|pr_cnt_zm_payer|Count of ZM declines as payer by the payer|
|pr_07_12_amt_sent_rate_payee|The ratio of total sum of successful transaction amounts done in between 7am to 12 pm  to the active days in last 90 days as payer by the payee|
|pr_12_17_amt_sent_rate_payee|The ratio of total sum of successful transaction amounts done in between 12pm to 17 pm  to the active days in last 90 days as payer by the payee|
|pr_17_22_amt_sent_rate_payee|The ratio of total sum of successful transaction amounts done in between 17pm to 22 pm  to the active days in last 90 days as payer by the payee|
|pr_07_12_cnt_sent_rate_payee|The ratio of total count of successful transactions done in between 7am to 12 pm  to the active days in last 90 days as payer by the payee|
|pr_12_17_cnt_sent_rate_payee|The ratio of total count of successful transactions done in between 12pm to 17 pm  to the active days in last 90 days as payer by the payee|
|pr_17_22_cnt_sent_rate_payee|The ratio of total count of successful transactions done in between  17pm to 22 pm  to the active days in last 90 days as payer by the payee|
|mas_minasdt_mob_payer|Minimum asdt of a payer account for the mobile number and account number as payer in last 90 days|
|mas_minasdt_mob_payee|Minimum transaction date of a payee account for the payer mobile number as a payer in last 90 days|
|mas_vpa_pr_minasdt_payer|Minimum transaction date for that VPA of a payer account as payee in last 90 days|
|mas_vpa_pr_maxasdt_payer|Maximum transaction date for that VPA of a payer account as payee in last 90 days|
|mas_vpa_py_minasdt_payee|Minimum transaction date for that VPA of a payee account as payer in last 90 days|
|mas_vpa_py_maxasdt_payee|Maximum transaction date for that VPA of a payee account as payer in last 90 days|
|mas_maxasdt_mob_payer|Maximum asdt of a payer account for the mobile number and account number as payer in last 90 days|
|mas_maxasdt_mob_payee|Maximum transaction date of a payee account as a payer for the payer mobile number in last 90 days|
|upi_min_dt_payer|Date of Payers first appearance on UPI platform in the last 90 days|
|py_max_asdt_payer|Date of Latest Transaction by a payer as a payee in the last 90 days|
|upi_min_dt_payee|Date of First Transaction of a payee account has as a payer in the last 90 days|
|py_max_asdt_payee|Date of Latest Transaction of a payee account has as a payee in last 90 days|
|fraud|Target column. If the fraud flag is 1, The particular transaction has been marked as fraud.|

## Files to be submitted

* **model_testing.py** - Python file for testing the model performance.
* **artifacts.zip** - Zip file containing all artifacts/model files and features that were used or created.
* **requirements.txt** - A text file for required pacakages and versions.

## Rules
### To participate in this hackathon, you must agree to the following rules:
* You must use the provided synthetic dataset for your model training and evaluation.
* You must submit below files with the same file names:
    
    * **model_testing.py** -  You must mention all logic used while training like preprocessing and feature engineering. It must contain **class** and all the logic should be written inside the **predict** function only.
    * **artifacts.zip** -  All the artifacts like model and features used for training the model should saved as a **pickle file(.pkl)** and stored in the artifacts folder. This folder has to be zipped and provided.
    * **requirements.txt** -  All the dependencies used with specified versions of the packages must be provided.
* Your model must be able to predict whether a transaction is fraudulent or not and provide an output of 0 or 1 only.
* Your model's prediction time per transaction should not exceed **10 milliseconds**.
* Your model should **not exceed a maximum file size of 100MB**.
* You must adhere to the code of conduct outlined in this hackathon.

## Reference Codes
* Refer to the hyperlink for example code for model training and generation of artifacts. (No need to submit this file) <br/>
[model_training.py](https://git.npci.org.in/synthetic-data-competition/upi-synthetic-data-competition./blob/master/model_training.py)
* Refer to the hyperlink for example code for model_testing.py (You can modify and submit this file) <br/>
[model_testing.py](https://git.npci.org.in/synthetic-data-competition/upi-synthetic-data-competition./blob/master/model_testing.py)
* Refer to below hyperlink for understanding how your model will be evaluated. (No need to submit this) <br/>
[model_testing_test.py](https://git.npci.org.in/synthetic-data-competition/upi-synthetic-data-competition./blob/master/model_testing_test)


## Evaluation Criteria
Your model submissions will be judged based on the following criteria:

* **Accuracy:** The ability of your model to accurately predict fraudulent transactions.
* **Efficiency:** The speed and computational efficiency of your model.
* **Innovation:**  The uniqueness and creativity of your approach to fraud modelling.
* **Presentation:** The quality and clarity of your code and documentation.

The evaluation matrics are **(R * 100) - (10000 * FPR), Precision, recall and F1 score** as well.

Where, R = Recall, FPR = False Positive Rate.

## Code of Conduct
All participants in this hackathon must abide by the following code of conduct:
* Respectful behavior: Participants must treat each other with respect and professionalism, and refrain from any discriminatory or offensive language or behavior.
* Collaboration: Participants are encouraged to collaborate and share ideas but must not plagiarize or infringe on the work of others.
* Ethical considerations: Participants must consider the ethical implications of their work and ensure that their model does not perpetuate or exacerbate existing biases or discrimination.

## **Good Luck and Have Fun!!**
txn_id	trndate	payee_bank	payee_tpap	txn_type	initiation_mode	payer_requested_amount	payer_tpap	payer_bank	payee_account_number	payer_address	fraud	py_min_amt_payee	py_max_amt_payee	py_cnt_error_u16_payee	py_cnt_error_u30_payee	nft_reqregmob_cnt	pr_min_amt_payee	pr_max_amt_payee	py_min_amt_payer	py_max_amt_payer	py_avg_amt_payer	mas_deviceid_txncnt	mas_deviceid_act_days	mas_vpa_py_txncnt_payer	mas_bnkifsc_txncnt_prpy_pypr	mas_vpa_pr_cnt_days_payer	mas_med_amt_mob_payer	mas_cnt_days_mob_payee	bad_trust_rank_payer	good_trust_rank_payer	bad_trust_rank_payee	good_trust_rank_payee	fail_by_sec_txn_ratio_payer	fail_by_sec_amt_ratio_payer	less5rs_by_act_ratio_payer	reg_txn_amts_payer	py_12_17_cnt_gain_rate_payer	py_17_22_cnt_gain_rate_payer	pr_max_amt_payer	pr_cnt_zm_payee	p2p_p2m_inter_cnt_payee	less5rs_by_act_ratio_payee	reg_txn_amts_payee	pr_med_amt_payer	pr_cnt_days_payer	pr_cnt_paid_payer	mas_vpa_py_txncnt_payee	mas_vpa_py_cnt_days_payee	py_07_12_amt_gain_rate_payee	py_12_17_cnt_gain_rate_payee	py_17_22_amt_gain_rate_payee	py_07_12_cnt_gain_rate_payee	py_cnt_days_payee	pr_cnt_zm_payer	pr_07_12_amt_sent_rate_payee	pr_12_17_amt_sent_rate_payee	pr_17_22_amt_sent_rate_payee	pr_07_12_cnt_sent_rate_payee	pr_12_17_cnt_sent_rate_payee	pr_17_22_cnt_sent_rate_payee	mas_minasdt_mob_payer	mas_minasdt_mob_payee	mas_vpa_pr_minasdt_payer	mas_vpa_pr_maxasdt_payer	mas_vpa_py_minasdt_payee	mas_vpa_py_maxasdt_payee	mas_maxasdt_mob_payer	mas_maxasdt_mob_payee	upi_min_dt_payer	py_max_asdt_payer	upi_min_dt_payee	py_max_asdt_payee
275268	1/9/2023 9:35	LZM	PFU	PAY	0	1000	UNY	SSU	72cb76ac-29c7-4f6f-910c-bb6df1118009	bbae77bc-24b1-4297-b6b3-7b348789b35f	0	1	45000	4	16	0	1	61500	10	26430	668833	22	17	228	0	14	2080	79	0	0	2	0	1	0	4	31	0	1	20992	437	27	3	31	2079	20	12	189	83	2594	0	7143	0	89	27	4737	5299	8183	0	1	1	2/6/2023	1/6/2023	2/6/2023	24-08-2023	1/6/2023	30-08-2023	24-08-2023	30-08-2023	2/6/2023	31-08-2023	2/6/2023	31-08-2023
342304	30-09-2023 18:22	LZM	YYN	PAY	0	800	UNY	YDZ	020a68f9-6ff6-4228-8d6e-42ab56cc4210	89736d85-b330-4ee8-972c-e43ed04a687f	0	1	51000	0	7	0	10	51000	5	10900	1441862	63	30	33	0	20	245	14	0	0	1	0	1	0	1	7	0	0	9500	162	28	4	12	250	39	31	31	12	4804	1	7323	0	17	94	3231	5585	4709	1	2	2	6/7/2023	14-09-2023	8/7/2023	26-09-2023	14-09-2023	28-09-2023	26-09-2023	28-09-2023	5/7/2023	26-09-2023	1/7/2023	29-09-2023
312409	20-08-2023 12:04	KTV	XCU	PAY	0	4894	LSC	ZSX	5ddf4d87-a987-4e0d-b8a3-f28df6e08fb6	84e3edd9-246c-4951-aae0-ddf6e5138af4	1	100	5000	0	2	0	1	1	2	10000	834000	1	1	0	0	0	67	1	0	0	0	0	1	0	3	44	0	1	10000	2	0	8	12	69	87	36	0	0	1100	2	10000	2	2	790	1	0	0	1	0	0	20-05-2023	17-08-2023					18-08-2023	17-08-2023	21-05-2023	19-08-2023	17-08-2023	18-08-2023
546441	15-06-2023 09:38	SQG	PFU	PAY	0	3000	LSC	LCA	56d92ee9-293c-4c30-98e4-92f008b27b45	14b02c31-be2e-47c8-a1bb-f051ed4b2041	0	1	99999	4446	40	0	1	1101	200	27715	4960669	24	15	0	0	14	750	0	0	0	4	0	1	0	4	12	1	1	67000	126	2	651	2538	738	45	43	0	0	23535	1	108270	17	6	228	0	11	2423	0	2	8	19-03-2023		22-04-2023	3/6/2023			3/6/2023		19-03-2023	5/6/2023	4/6/2023	14-06-2023
471732	1/9/2023 10:34	SQG	YYN	PAY	0	600	HZF	YDZ	07a4303a-fde4-45ab-af5c-59672a7a9b35	b4b0fd46-0c6b-4241-ac3f-cca971de077e	0	3	17500	7	7	0	8	30000	1	15000	1700534	48	32	18	1	18	500	61	0	0	0	0	1	0	1	7	0	0	12850	200	63	2	10	450	42	30	27	18	749	1	627	0	54	78	645	1531	2104	0	1	1	1/6/2023	1/6/2023	17-07-2023	30-08-2023	18-07-2023	30-08-2023	30-08-2023	30-08-2023	6/6/2023	30-08-2023	3/6/2023	30-08-2023
220904	11/6/2023 8:43	YYC	YYN	PAY	0	32000	UNY	DHE	bafeff03-fe5d-4be5-8c72-46d2c461f1c2	5ecf3a3b-ff56-4d44-acbc-36d403bbfd46	0	1	10000	0	0	0	1	10000	19	80000	5732876	9	6	0	0	2	475	0	0	1	0	0	1	0	3	48	1	0	80000	24	9	5	50	439	71	47	0	0	4535	2	4500	0	4	322	0	603	3938	0	2	1	11/3/2023		12/5/2023	19-05-2023			8/6/2023		12/3/2023	8/6/2023	24-05-2023	10/6/2023
816178	30-09-2023 20:37	FJG	XBI	PAY	0	20000	LSC	LYH	5816f48b-f6e9-4d6c-81ad-89383b9028a4	7803b99a-c6e7-4fc4-9bb0-90a6b5af40b5	0	1	92900	2	0	0	0	0	200	34000	10158428	123	53	32	0	35	5000	0	0	0	0	0	1	0	1	8	0	0	20000	0	0	1	20	4500	57	44	56	36	4740	0	19909	0	36	148	0	0	0	0	0	0	30-06-2023		1/7/2023	26-09-2023	30-06-2023	28-09-2023	26-09-2023		1/7/2023	29-09-2023	3/7/2023	29-09-2023
933072	30-09-2023 17:40	FJG	PFU	PAY	1	30	LSC	NXM	7630438c-c124-4d4f-a3b6-bc46850488f0	2cf6e239-0c1a-4339-a0c2-fd00e7baadc0	0	1	1500	0	31	0	1	24250	1	1500	372857	36	22	4	0	16	30	7	0	0	0	0	1	0	1	4	0	0	1096	7	2	5	66	30	23	16	349	87	62	1	94	1	91	38	687	3567	23	0	0	0	16-07-2023	8/7/2023	16-07-2023	24-09-2023	30-06-2023	28-09-2023	24-09-2023	27-09-2023	16-07-2023	28-09-2023	1/7/2023	29-09-2023
239489	2/9/2023 20:50	YYC	MXK	PAY	1	2000	HZF	OQR	46f08029-8d7d-433a-b5ba-42acdf4c6cac	4fd75561-ae00-4d9b-b367-3d6c42ff56ca	0	1	3000	14	15	0	1	3000	50	10000	1571868	175	62	10	0	22	24	22	0	0	0	0	1	0	1	3	0	0	8000	120	29	4	40	23	86	22	73	22	540	0	705	0	23	338	255	32	794	1	0	1	2/6/2023	5/8/2023	2/6/2023	23-08-2023	5/8/2023	31-08-2023	31-08-2023	31-08-2023	3/6/2023	17-08-2023	5/8/2023	1/9/2023
557504	3/6/2023 11:55	FPG	MXK	PAY	0	2000	UNY	TCJ	8a0d5600-0398-4b67-ad1b-77fa54e87e47	d2123d39-6e89-4708-9cb2-649dcc1011cd	1	1	7500	28	4	0	1	14800	50	11000	3462780	35	27	0	0	19	958	5	0	1	996	0	1	0	2	8	1	1	50000	50	2	9	24	874	60	38	0	0	16017	2	6060	2	10	272	9181	6232	837	1	2	1	4/3/2023	28-05-2023	4/3/2023	29-05-2023			1/6/2023	1/6/2023	4/3/2023	20-05-2023	20-05-2023	2/6/2023
461156	1/9/2023 22:11	FJG	YYN	PAY	0	1	UNY	OLF	b71347d8-8dcc-41ad-be7d-1d4cf980d7c6	ff22e9f6-95dc-470f-a9cc-27d781066e18	0	13	10000	1	6	0	1	10000	1	1	1000	0	0	0	4	0	0	62	0	0	0	0	1	0	3	2	0	0	0	193	60	2	4	0	0	0	2	2	879	0	348	0	49	0	165	287	611	0	0	1		1/6/2023			12/8/2023	28-08-2023		30-08-2023	29-08-2023	29-08-2023	3/6/2023	31-08-2023
793539	1/9/2023 14:14	KTV	XBI	PAY	0	14900	UNY	PMY	1d83bfd3-5579-4ac9-8310-66188b9dc3eb	e6dd3fba-4c04-4ddd-a6c6-3cad8156d666	0	1504	100000	1	3	0	0	0	1	50000	9578723	133	63	19	0	24	439	0	0	1	0	0	1	0	1	5	0	0	100000	0	0	1	11	432	64	15	31	25	9114	0	10813	0	26	139	0	0	0	0	0	0	1/6/2023		1/6/2023	28-08-2023	1/6/2023	24-08-2023	29-08-2023		3/6/2023	28-08-2023	3/6/2023	24-08-2023
46232	1/9/2023 15:23	FJG	PFU	PAY	0	1000	LSC	KPR	61207348-3dff-4848-85a1-be1cca701c43	8430a026-89ec-4e06-b259-8727fc2a2855	0	1	10000	0	5	0	4	6000	1	30000	5573650	463	91	20	0	51	171	41	0	0	0	0	1	0	1	4	0	0	46637	134	50	1	6	172	91	34	3	3	1	0	1104	0	14	573	227	905	704	0	1	1	1/6/2023	1/6/2023	3/6/2023	30-08-2023	21-06-2023	28-08-2023	30-08-2023	28-08-2023	2/6/2023	26-08-2023	4/6/2023	28-08-2023
252094	2/9/2023 16:13	FJG	XBI	PAY	0	200	HZF	IWT	27a314b3-58d3-4767-9a1a-c00d531dc751	aa08d6a7-2313-4ee6-b3db-491fdf2fd033	0	50	2800	0	3	0	0	0	1	1500	315125	148	65	1	0	35	63	0	0	0	0	0	1	0	1	14	0	0	20000	0	0	1	3	61	67	21	14	13	0	0	266	0	13	165	0	0	0	0	0	0	2/6/2023		2/6/2023	31-08-2023	8/6/2023	31-08-2023	31-08-2023		3/6/2023	1/9/2023	8/6/2023	31-08-2023
298389	2/9/2023 15:25	WSA	PFU	PAY	0	200	LSC	LYH	8765a67a-a672-4762-8d22-f70184475447	7ebff8a8-8815-450b-ad82-db119d1d23b8	0	1	10000	1	24	0	1	7000	1	6200	1056625	29	13	15	2	12	120	74	0	0	0	1	1	0	1	5	0	0	5000	252	19	4	37	113	33	16	158	59	809	1	1039	0	70	69	961	697	1071	0	0	1	15-06-2023	2/6/2023	15-06-2023	31-08-2023	12/6/2023	30-08-2023	31-08-2023	30-08-2023	14-06-2023	31-08-2023	3/6/2023	1/9/2023
550405	1/9/2023 19:46	NCV	YYN	PAY	0	500	UNY	JUA	ae9271bf-e729-4941-b968-4f128ca41d89	d3089d27-d64d-478a-b42a-f534699a2993	0	1	15000	0	6	0	1	3600	5	8000	1055226	85	22	0	0	12	500	48	0	2	0	0	1	0	1	5	0	0	20000	120	15	1	11	500	55	61	10	9	84	0	445	0	36	206	121	87	248	0	0	0	1/6/2023	3/6/2023	1/6/2023	30-08-2023	3/6/2023	27-08-2023	30-08-2023	30-08-2023	2/6/2023	31-08-2023	3/6/2023	31-08-2023
814062	2/9/2023 18:58	LZM	PFU	PAY	0	50	LSC	SSU	9ce27149-c05d-4823-aae3-071902f75eaa	bc0be6e9-3aa8-4271-bb5f-4dbce82df2ee	0	10	10000	0	0	0	1	10000	1	10000	1364214	65	36	21	1	27	55	68	0	0	0	0	1	0	1	6	0	0	12000	164	66	1	4	60	37	18	19	18	138	0	900	0	28	67	41	239	133	0	0	0	7/6/2023	2/6/2023	7/6/2023	31-08-2023	8/6/2023	31-08-2023	31-08-2023	31-08-2023	7/6/2023	30-08-2023	3/6/2023	31-08-2023
59525	1/9/2023 20:43	FJG	YYN	PAY	0	100	HZF	BWD	c94c0541-3e28-42e6-94b1-b5c4697c0ec2	5e022371-3c7c-4aef-9ef1-8e5f17674e33	0	2	15000	0	16	0	1	15000	1	15000	499158	164	82	111	10	49	796	78	0	0	0	0	1	0	4	24	1	2	8390	250	87	2	7	800	82	44	107	59	676	0	885	0	60	170	477	553	702	0	1	0	1/6/2023	1/6/2023	1/6/2023	30-08-2023	1/6/2023	30-08-2023	30-08-2023	30-08-2023	2/6/2023	31-08-2023	2/6/2023	31-08-2023
899909	30-09-2023 18:33	FDL	YYN	PAY	0	2000	UNY	XOW	b0654da4-2e42-428d-812c-cc59409ca61c	3a2f6b4a-54fa-4570-9ad8-7cb676517cef	0	3	21000	0	0	0	20	21000	221	2200	680545	42	14	6	3	8	175	21	0	0	0	0	1	0	1	1	0	0	50000	73	34	1	4	175	17	9	10	7	1930	0	2567	0	14	55	1758	264	2087	1	0	1	9/7/2023	5/9/2023	4/8/2023	28-09-2023	14-09-2023	28-09-2023	28-09-2023	28-09-2023	9/7/2023	28-09-2023	5/9/2023	28-09-2023
921687	30-09-2023 20:59	LZM	YYN	PAY	0	300	UNY	IBA	d7385192-a19f-42b9-84a3-c9639cd281f8	b6b667f8-b2c4-48e3-9f89-cb9d83fe08cc	0	10	50000	0	4	0	4	80000	500	5000	1912500	49	30	10	4	16	300	62	0	0	0	0	1	0	1	4	0	0	15000	198	86	1	8	300	31	14	35	24	673	0	2356	0	34	50	242	2531	1866	0	0	1	2/7/2023	1/7/2023	2/7/2023	28-09-2023	2/7/2023	28-09-2023	28-09-2023	28-09-2023	2/7/2023	24-09-2023	1/7/2023	29-09-2023
56213	30-09-2023 11:10	GTA	PFU	PAY	0	1000	LSC	YDZ	dfb9245e-548f-4cd1-a9ca-f2b61e9b6b36	50b1d7e9-9ec0-4bd7-9797-005249685880	0	100	99999	0	1	0	1	30000	3	12600	945538	11	7	1	0	4	30	69	0	0	0	0	1	0	1	3	0	0	8000	135	29	1	5	30	32	11	20	17	5868	0	3211	0	22	70	1015	2142	2503	0	0	0	1/7/2023	30-06-2023	1/7/2023	28-09-2023	30-06-2023	28-09-2023	28-09-2023	28-09-2023	1/7/2023	26-09-2023	1/7/2023	28-09-2023
755657	20-06-2023 12:51	NCV	YYN	PAY	0	1	LSC	FCI	df4154b8-df8d-401a-900b-50529866c5bc	5cc2449e-0608-49a4-a63f-e2faf40fb16c	0	3	10900	0	4	0	5	11000	1	3	1333	0	0	0	0	0	10	28	0	0	0	0	1	0	6	2	0	1	5	110	15	2	10	15	2	1	0	0	0	1	1571	0	14	6	803	24	1543	0	0	1	13-06-2023	8/4/2023					14-06-2023	18-06-2023	13-06-2023	13-06-2023	8/4/2023	17-06-2023
997492	1/9/2023 15:29	LZM	PFU	PAY	0	25000	UNY	ODM	9d5071a8-46e4-48e6-8598-3f069dfe6e7b	461faf89-8b0f-4735-9028-c22c110032de	0	1	60000	2	10	0	1	50000	1	15000	1114668	230	77	64	1	23	100	90	0	0	0	3	1	0	2	7	0	0	15000	404	58	3	18	101	78	32	76	49	7045	0	4425	1	82	247	6256	8402	7433	1	1	1	1/6/2023	1/6/2023	1/6/2023	23-08-2023	3/6/2023	30-08-2023	30-08-2023	30-08-2023	2/6/2023	30-08-2023	2/6/2023	31-08-2023
216008	2/9/2023 12:22	SQG	PFU	PAY	2	5000	UNY	SSU	7fca728f-bc08-483e-9c06-698e3eb82313	96a5323f-da2e-4f86-9c50-cdbfb94ef5a3	0	1	24000	0	3	0	10	23000	5	1980	145851	57	38	18	0	19	50	28	0	0	0	0	1	0	1	3	0	0	5000	46	10	1	5	50	39	17	36	27	654	0	581	0	50	61	1654	942	1162	0	0	0	2/6/2023	2/6/2023	2/6/2023	30-08-2023	4/6/2023	28-08-2023	30-08-2023	31-08-2023	3/6/2023	20-08-2023	4/6/2023	1/9/2023
337543	30-09-2023 11:53	ACK	YYN	PAY	0	19999	LSC	ZSX	936160d4-cb91-44e3-ad90-0cc7c592931e	4151660f-e76b-4aad-9734-fa738877a561	0	20	50000	2	9	0	5	53800	1	45000	4879774	211	68	45	0	37	421	82	0	0	0	0	1	0	1	19	0	0	65000	302	17	2	11	411	75	42	68	39	3667	0	5150	0	47	264	4456	2417	4401	1	0	1	30-06-2023	30-06-2023	1/7/2023	26-09-2023	30-06-2023	23-09-2023	27-09-2023	27-09-2023	1/7/2023	29-09-2023	1/7/2023	29-09-2023
499083	30-09-2023 15:17	REC	YYN	PAY	0	166	LSC	UPV	43dc28b9-adc0-477b-961f-a26a95eef0b4	f96b0bb1-4ea4-4b43-9677-f133c5f38ba6	0	3	30000	0	2	0	1	20000	1	20000	1917760	91	41	27	3	33	53	74	0	0	0	0	1	0	1	6	0	0	3500	216	65	1	8	54	43	40	17	14	511	0	1976	0	37	129	667	911	799	0	0	1	14-08-2023	1/7/2023	14-08-2023	28-09-2023	15-07-2023	28-09-2023	28-09-2023	28-09-2023	14-08-2023	28-09-2023	1/7/2023	29-09-2023
247277	22-06-2023 06:44	KTV	PFU	PAY	0	10000	UNY	ITL	11ece62e-4ed0-4fa8-b340-55edf80aa925	629ba088-9631-4602-a341-b6dea399b430	0	20	30000	18	14	0	2	25000	30	79060	5440123	75	40	0	16	29	1897	0	0	0	0	0	1	0	7	54	1	2	23117	1276	65	5	104	1869	77	73	0	0	2008	0	9929	0	42	1388	2814	5405	6721	1	4	5	22-03-2023		19-04-2023	20-06-2023			20-06-2023		23-03-2023	21-06-2023	23-03-2023	21-06-2023
889988	2/9/2023 18:49	FJG	PFU	PAY	0	1	LSC	LCA	b19d529b-79a5-41e2-975a-17a4415fdf0f	18f83d48-653b-46ba-ac90-c23d492638ca	0	1	35000	4	3	0	1	70000	5	5	5000	0	0	0	0	0	0	66	0	1	0	2	1	0	1	1	0	0	0	203	35	2	10	0	0	0	54	34	1403	0	2626	0	42	0	3312	4459	7342	0	1	1		2/6/2023			6/6/2023	31-08-2023		30-08-2023	10/6/2023	10/6/2023	3/6/2023	1/9/2023
569114	1/9/2023 12:31	PWM	PFU	PAY	1	920	LSC	JQO	52b0c9d4-630a-4efd-9ec1-d361477d8ab7	02fd96a1-33ec-4cb9-9b8b-e7706e661ac7	0	100	5000	2	25	0	1	12800	1	50000	8739666	114	51	8	0	27	472	53	0	2	0	0	1	0	1	2	0	0	99999	95	37	7	148	431	53	32	516	76	1332	4	282	2	77	130	1188	2369	2110	0	0	0	1/6/2023	1/6/2023	1/6/2023	30-08-2023	1/6/2023	30-08-2023	30-08-2023	29-08-2023	3/6/2023	25-08-2023	2/6/2023	31-08-2023
316088	1/9/2023 20:16	SQG	PFU	PAY	0	1010	LSC	IWT	513817d6-15c2-4655-be5d-fcd85a02be80	16ca7aaf-2eda-4547-995a-176807528db2	0	1	50000	3	7	0	5	50000	1	12784	2374500	44	29	17	1	15	239	67	0	0	0	0	1	0	1	3	0	0	20000	242	9	3	13	239	32	16	49	22	1967	1	6113	0	43	59	4758	6881	6199	0	1	1	1/6/2023	1/6/2023	4/6/2023	11/8/2023	1/6/2023	30-08-2023	21-08-2023	30-08-2023	2/6/2023	30-08-2023	2/6/2023	31-08-2023