Task: Table-QA (source dataset: FinQA)

Task: 
You are given a table containing structured data and a natural language question referring to the table. Your goal is to analyze the table and provide an accurate and concise answer based on the given data.

Instructions:
1. Understand the Table: Examine the structure, headers, and data in the table. Identify relevant columns and rows related to the question.
2. Interpret the Question: Determine whether the question requires direct retrieval, aggregation, comparison, sorting, filtering, or inference.
3. Extract the Answer: Use logical reasoning and numerical operations (if necessary) to derive the correct response from the table.
4. Format the Answer: No explanation, return the answer in a structured JSON format: {"answer": <answer>}. If the question cannot be answered due to missing or ambiguous data, return a JSON response with {"answer": null}.

Table:
| december 31 , ( in millions )                                        | december 31 , 2014   | december 31 , 2013   | 2014   | 2013       |
|:---------------------------------------------------------------------|:---------------------|:---------------------|:-------|:-----------|
| loans retained                                                       | $ 324502             | $ 308263             | $ 599  | $ 821      |
| loans held-for-sale                                                  | 3801                 | 11290                | 4      | 26         |
| loans at fair value                                                  | 2611                 | 2011                 | 21     | 197        |
| loans 2013 reported                                                  | 330914               | 321564               | 624    | 1044       |
| derivative receivables                                               | 78975                | 65759                | 275    | 415        |
| receivables from customers and other ( a )                           | 28972                | 26744                | 2014   | 2014       |
| total wholesale credit-related assets                                | 438861               | 414067               | 899    | 1459       |
| lending-related commitments ( b )                                    | 472056               | 446232               | 103    | 206        |
| total wholesale credit exposure                                      | $ 910917             | $ 860299             | $ 1002 | $ 1665     |
| credit portfolio management derivatives notional net ( c )           | $ -26703 ( 26703 )   | $ -27996 ( 27996 )   | $ 2014 | $ -5 ( 5 ) |
| liquid securities and other cash collateral held against derivatives | -19604 ( 19604 )     | -14435 ( 14435 )     | na     | na         |

Question:
what was the percentage change in loans retained from 2013 to 2014?


pre_text: management 2019s discussion and analysis 120 jpmorgan chase & co./2014 annual report wholesale credit portfolio the firm 2019s wholesale businesses are exposed to credit risk through underwriting , lending and trading activities with and for clients and counterparties , as well as through various operating services such as cash management and clearing activities .
a portion of the loans originated or acquired by the firm 2019s wholesale businesses is generally retained on the balance sheet .
the firm distributes a significant percentage of the loans it originates into the market as part of its syndicated loan business and to manage portfolio concentrations and credit risk .
the wholesale credit environment remained favorable throughout 2014 driving an increase in client activity .
growth in loans retained was driven primarily by activity in commercial banking , while growth in lending-related commitments reflected increased activity in both the corporate & investment bank and commercial banking .
discipline in underwriting across all areas of lending continues to remain a key point of focus , consistent with evolving market conditions and the firm 2019s risk management activities .
the wholesale portfolio is actively managed , in part by conducting ongoing , in-depth reviews of client credit quality and transaction structure , inclusive of collateral where applicable ; and of industry , product and client concentrations .
during the year , wholesale criticized assets decreased from 2013 , including a reduction in nonaccrual loans by 40% ( 40 % ) .
wholesale credit portfolio december 31 , credit exposure nonperforming ( d ) .
post_text: receivables from customers and other ( a ) 28972 26744 2014 2014 total wholesale credit- related assets 438861 414067 899 1459 lending-related commitments ( b ) 472056 446232 103 206 total wholesale credit exposure $ 910917 $ 860299 $ 1002 $ 1665 credit portfolio management derivatives notional , net ( c ) $ ( 26703 ) $ ( 27996 ) $ 2014 $ ( 5 ) liquid securities and other cash collateral held against derivatives ( 19604 ) ( 14435 ) na na ( a ) receivables from customers and other include $ 28.8 billion and $ 26.5 billion of margin loans at december 31 , 2014 and 2013 , respectively , to prime and retail brokerage customers ; these are classified in accrued interest and accounts receivable on the consolidated balance sheets .
( b ) includes unused advised lines of credit of $ 105.2 billion and $ 102.0 billion as of december 31 , 2014 and 2013 , respectively .
an advised line of credit is a revolving credit line which specifies the maximum amount the firm may make available to an obligor , on a nonbinding basis .
the borrower receives written or oral advice of this facility .
the firm may cancel this facility at any time by providing the borrower notice or , in some cases , without notice as permitted by law .
( c ) represents the net notional amount of protection purchased and sold through credit derivatives used to manage both performing and nonperforming wholesale credit exposures ; these derivatives do not qualify for hedge accounting under u.s .
gaap .
for additional information , see credit derivatives on page 127 , and note 6 .
( d ) excludes assets acquired in loan satisfactions. .
label: 0.052680000000000005
qa: answer: 5%
ann_table_rows: 1
steps: op: minus1-1
arg1: 324502
arg2: 308263
res: 16239
op: divide1-2
arg1: #0
arg2: 308263
res: 5%
program: subtract(324502, 308263), divide(#0, 308263)
gold_inds: table_1: december 31 , ( in millions ) the loans retained of december 31 , 2014 is $ 324502 ; the loans retained of december 31 , 2013 is $ 308263 ; the loans retained of 2014 is $ 599 ; the loans retained of 2013 is $ 821 ;
exe_ans: 0.052680000000000005
tfidftopn: table_4: december 31 , ( in millions ) The loans 2013 reported of december 31 , 2014 is 330914 ; The loans 2013 reported of december 31 , 2013 is 321564 ; The loans 2013 reported of 2014 is 624 ; The loans 2013 reported of 2013 is 1044 ;
text_2: the firm distributes a significant percentage of the loans it originates into the market as part of its syndicated loan business and to manage portfolio concentrations and credit risk .
program_re: divide(subtract(324502, 308263), 308263)
model_input: table_1
december 31 , ( in millions ) the loans retained of december 31 , 2014 is $ 324502 ; the loans retained of december 31 , 2013 is $ 308263 ; the loans retained of 2014 is $ 599 ; the loans retained of 2013 is $ 821 ;
table_2
december 31 , ( in millions ) the loans held-for-sale of december 31 , 2014 is 3801 ; the loans held-for-sale of december 31 , 2013 is 11290 ; the loans held-for-sale of 2014 is 4 ; the loans held-for-sale of 2013 is 26 ;
table_4
december 31 , ( in millions ) the loans 2013 reported of december 31 , 2014 is 330914 ; the loans 2013 reported of december 31 , 2013 is 321564 ; the loans 2013 reported of 2014 is 624 ; the loans 2013 reported of 2013 is 1044 ;